Method, apparatus, and system for wireless sensing measurements and reporting

Abstract

To provide a method, system and apparatus for wireless sensing measurement and reporting.SOLUTION: A wireless data communication network system comprises: a transmitter configured to transmit a time-series wireless sounding signal (WSS) on the basis of a wireless protocol associated with a wireless data communication network; and a receiver. The wireless data communication network comprises a physical (PHY) layer, a medium access control (MAC) layer, and at least one higher layer. The receiver is configured to receive the time-series WSS (TSWSS) based on the wireless protocol through a wireless channel of a venue, and perform a plurality of wireless sensing measurements on the basis of the received TSWSS to obtain sensing measurement results. The PHY layer or the MAC layer of the receiver provides the sensing measurement results to the at least one higher layer of the receiver. At least one higher layer of the receiver performs a sensing-based task on the basis of the sensing measurement results.SELECTED DRAWING: Figure 18

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application incorporates by reference the entire disclosure of each of the following cases and claims priority thereto: (a) U.S. Provisional Patent Application No. 63 / 253,083, entitled "Method, Apparatus, and System for Wireless Sensing, Detection, and Tracking," filed October 6, 2021; (b) U.S. Provisional Patent Application No. 63 / 276,652, entitled "Method, Apparatus, and System for Wirelessly Monitoring Vertical Signs and Peripheral Activity," filed November 7, 2021; (c) U.S. Provisional Patent Application No. 63 / 281,043, entitled "Sensing Method, Apparatus, and System," filed November 18, 2021; (d) U.S. Provisional Patent Application No. 63 / 293,065, entitled "Method, Apparatus, and System for Speed ​​Enhancement and Separation," filed December 22, 2021; (e) U.S. Provisional Patent Application No. 63 / 300,042, entitled "Method, Apparatus, and System for Wireless Sensing and Sleep Tracking," filed January 16, 2022; (f) U.S. Provisional Patent Application No. 63 / 308,927, entitled "Method, Apparatus, and System for Wireless Sensing Based on Multiple Groups of Wireless Devices," filed February 10, 2022; (g) U.S. Provisional Patent Application No. 63 / 332,658, entitled "Method, Apparatus, and System for Wireless Sensing," filed April 19, 2022; (h) U.S. Patent Application No. 17 / 827,902, entitled "Method, Apparatus, and System for Speed ​​Enhancement and Separation Based on Voice and Wireless Signals," filed May 30, 2022; (i) U.S. Provisional Patent Application No. 63 / 349,082, entitled "Method, Apparatus, and System for Wireless Sensing Voice Activity Detection," filed June 4, 2022; (j) U.S. Patent Application No. 17 / 838,228, entitled "Method, Apparatus, and System for Wireless Sensing Based on Channel Information," filed June 12, 2022; (k) U.S. Patent Application No. 17 / 838,231, entitled "Method, Apparatus, and System for Identifying and Quantifying Devices for Wireless Sensing," filed June 12, 2022; (l) U.S. Patent Application No. 17 / 838,244, entitled "Method, Apparatus, and System for Wireless Sensing Based on Link-Wise Operational Statistics," filed June 12, 2022; (m) U.S. Provisional Patent Application No. 63 / 354,184, entitled "Method, Apparatus, and System for Motion Localization and Outlier Removal," filed June 21, 2022; (n) U.S. Provisional Patent Application No. 63 / 388,625, entitled "Wireless Sensing and Indoor Positioning Method, Apparatus, and System," filed July 12, 2022; (o) U.S. Patent Application No. 17 / 888,429, entitled "Method, Apparatus, and System for Wireless-Based Sleep Tracking," filed August 15, 2022; (p) U.S. Patent Application No. 17 / 891,037, entitled "Method, Apparatus, and System for Map Reconstruction Based on Wireless Tracking," filed August 18, 2022; (q) U.S. Patent Application No. 17 / 945,995, entitled "Method, Apparatus, and System for Wireless Biomedical Monitoring Using Radio Frequency Signals," filed September 15, 2022.

[0002] The present teachings relate generally to wireless sensing and, more particularly, to methods, systems, and apparatus for performing wireless sensing measurements and reporting. [Background technology]

[0003] As Internet of Things (IoT) applications become more widespread, billions of home appliances, phones, smart devices, security systems, environmental sensors, vehicles, buildings, and other wirelessly connected devices transmit data and communicate with each other and with people, enabling everything to be measured and tracked at all times. Among various approaches to measuring what is happening in the surrounding environment, wireless sensing has attracted increasing attention in recent years due to the ubiquitous deployment of wireless devices. Furthermore, because human activity affects the propagation of wireless signals, understanding and analyzing how wireless signals respond to human activity can reveal a wealth of information about those activities. As more bandwidth becomes available in new generations of wireless systems, wireless sensing will soon enable many smart IoT applications that we can only imagine today. This is because greater bandwidth allows us to see more multipaths, even in scattering-rich environments like indoors or metropolitan areas, and treat them as hundreds of virtual antennas / sensors. Although several technology standards, such as IEEE 802.11bf, support wireless sensing, many details of wireless sensing, such as how wireless sensing measurements and reporting are performed, have yet to be standardized. Therefore, an efficient and effective method for wireless sensing measurement and reporting is desirable. Summary of the Invention

[0004] The present teachings relate generally to wireless sensing and, more particularly, to methods, systems, and apparatus for performing wireless sensing measurements and reporting.

[0005] In one embodiment, a system for wireless sensing in a wireless data communication network is described. The system includes a transmitter configured to transmit a time-series wireless sounding signal (WSS) based on a wireless protocol associated with the wireless data communication network, and a receiver. The wireless data communication network is comprised of a physical (PHY) layer, a medium access control (MAC) layer, and at least one upper layer. The receiver is configured to receive the time-series WSS (TSWSS) based on the wireless protocol via a wireless channel of a venue and perform multiple wireless sensing measurements based on the received TSWSS to obtain sensing measurement results. The receiver is configured to receive the time-series WSS (TSWSS) based on the wireless protocol via a wireless channel of a venue and perform multiple wireless sensing measurements based on the received TSWSS to obtain sensing measurement results. The PHY layer or MAC layer of the receiver reports the sensing measurement results to at least one upper layer of the receiver. The at least one upper layer of the receiver performs a sensing-based task based on the sensing measurement results.

[0006] In another embodiment, a wireless device in a wireless data communication network for wireless sensing is described. The wireless device includes a processor, a memory communicatively coupled to the processor, and a receiver communicatively coupled to the processor. An additional wireless device in the wireless data communication network is configured to transmit a time-series wireless sounding signal (WSS) based on a wireless protocol associated with the wireless data communication network. The wireless data communication network includes a physical (PHY) layer, a medium access control (MAC) layer, and at least one upper layer. The receiver is configured to receive the time-series WSS (TSWSS) based on the wireless protocol via a wireless channel of a venue and perform multiple wireless sensing measurements based on the received TSWSS to obtain sensing measurement results. The PHY layer or MAC layer of the receiver reports the sensing measurement results to at least one upper layer of the receiver. The PHY layer or MAC layer of the receiver reports the sensing measurement results to at least one upper layer of the receiver. The at least one upper layer of the receiver performs a sensing-based task based on the sensing measurement results.

[0007] In yet another embodiment, a method of wireless sensing is described, the method including: transmitting, by a transmitter in a wireless data communication network, a time-series wireless sounding signal (WSS) based on a wireless protocol associated with the wireless data communication network, the wireless data communication network having a physical (PHY) layer, a medium access control (MAC) layer, and at least one upper layer; receiving, by a receiver in the wireless data communication network, the time-series WSS (TSWSS) based on the wireless protocol via a wireless channel of a venue; performing, by the receiver, a plurality of wireless sensing measurements based on the received TSWSS to obtain sensing measurement results; reporting, by the PHY layer or the MAC layer of the receiver, the sensing measurement results to at least one upper layer of the receiver; and performing, by the at least one upper layer of the receiver, a sensing-based task based on the sensing measurement results.

[0008] Other concepts relate to software for implementing the present teachings regarding wireless sensing measurement and reporting. Concepts relate to software for implementing the present teachings regarding wireless sensing measurement and reporting. Additional novel features are set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following description and the accompanying drawings, or may be learned by the manufacture or operation of the embodiments. The novel features of the present teachings may be realized and attained by practice or use of various aspects of the methods, instrumentalities and combinations described in the detailed embodiments which follow. [Brief explanation of the drawings]

[0009] The methods, systems, and / or devices described herein will be further explained in terms of exemplary embodiments, which will be described in detail with reference to the drawings, which are non-limiting exemplary embodiments, and in which like reference numerals represent like structure throughout the several views of the drawings.

[0010] [Figure 1]1 illustrates an example of a wireless sensing procedure, according to some embodiments of the present disclosure.

[0011] [Figure 2] 10 illustrates another example of a wireless sensing procedure according to some embodiments of the present disclosure.

[0012] [Figure 3] 1 illustrates an example of a trigger-based wireless sensing measurement instance, according to some embodiments of the present disclosure.

[0013] [Figure 4] 1 illustrates various example use cases for wireless sensing and reporting, according to various embodiments of the present disclosure. [Figure 5] 1 illustrates various example use cases for wireless sensing and reporting, according to various embodiments of the present disclosure. [Figure 6] 1 illustrates various example use cases for wireless sensing and reporting, according to various embodiments of the present disclosure. [Figure 7] 1 illustrates various example use cases for wireless sensing and reporting, according to various embodiments of the present disclosure. [Figure 8] 1 illustrates various example use cases for wireless sensing and reporting, according to various embodiments of the present disclosure. [Figure 9] 1 illustrates various example use cases for wireless sensing and reporting, according to various embodiments of the present disclosure. [Figure 10] 1 illustrates various example use cases for wireless sensing and reporting, according to various embodiments of the present disclosure. [Figure 11] 1 illustrates various example use cases for wireless sensing and reporting, according to various embodiments of the present disclosure. [Figure 12] 1 illustrates various example use cases for wireless sensing and reporting, according to various embodiments of the present disclosure. [Figure 13] 1 illustrates various example use cases for wireless sensing and reporting, according to various embodiments of the present disclosure.

[0014] [Figure 14] FIG. 1 illustrates an example of measurement instance sharing within a wireless sensing session, according to some embodiments of the present disclosure.

[0015] [Figure 15] 1 illustrates an example of measurement instance sharing across wireless sensing sessions, in accordance with some embodiments of the present disclosure.

[0016] [Figure 16] 1 is an example block diagram of a first wireless device of a system for wireless sensing according to some embodiments of the present disclosure.

[0017] [Figure 17] FIG. 10 is an example block diagram of a second wireless device of a system for wireless sensing, according to some embodiments of the present disclosure.

[0018] [Figure 18] 1 illustrates a flowchart of an exemplary method for identifying a device used for wireless sensing, according to some embodiments of the present disclosure.

[0019] [Figure 19] 1 illustrates an example of two-way responder-to-responder sensing, according to some embodiments of the present disclosure.

[0020] [Figure 20] 1 illustrates a number of stations (STAs) in a non-infrastructure mode forming an ad-hoc network, according to some embodiments of the present disclosure.

[0021] [Figure 21] 1 illustrates various use cases for non-infrastructure mode sensing according to some embodiments of the present disclosure. [Figure 22]1 illustrates various use cases for non-infrastructure mode sensing according to some embodiments of the present disclosure. [Figure 23] 1 illustrates various use cases for non-infrastructure mode sensing according to some embodiments of the present disclosure. [Figure 24] 1 illustrates various use cases for non-infrastructure mode sensing according to some embodiments of the present disclosure. [Figure 25] 1 illustrates various use cases for non-infrastructure mode sensing according to some embodiments of the present disclosure.

[0022] [Figure 26] 1 illustrates various use cases for updating Sensing by Proxy (SBP) procedures according to some embodiments of the present disclosure. [Figure 27] 1 illustrates various use cases for updating Sensing by Proxy (SBP) procedures according to some embodiments of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0023] In one embodiment, the present teachings disclose a method, apparatus, device, system, and / or software (method / apparatus / device / system / software) for a wireless monitoring system. Time-series channel information (CI) of a wireless multipath channel (channel) may be obtained (e.g., dynamically) using a processor, a memory communicatively coupled to the processor, and a set of instructions stored in the memory. The time-series CI (TSCI) may be extracted from wireless signals (signals) transmitted between a type-1 heterogeneous wireless device (e.g., a wireless traffic light, TX) and a type-2 heterogeneous wireless device (e.g., a wireless receiver, RX) in a venue through the channel. The channel may be affected by the representation (e.g., motion, movement, representation, and / or change in position / pose / shape / representation) of an object in the venue. The object's characteristics and / or spatial-temporal information (STI, e.g., motion information) and / or the object's motion may be monitored based on the TSCI. A task may be performed based on the characteristics and / or STI. A presentation associated with a task may be generated in a user interface (UI) on a user's device. A TSCI may be a wireless signal stream. A TSCI or each CI may be pre-processed. A device may be a station (STA). The symbol "A / B" means "A and / or B" in the present teachings.

[0024] An expression may include placement, placement of moving parts, location, position, orientation, identifiable place, area, spatial coordinates, presentation, state, static representation, size, length, width, height, angle, scale, shape, curve, surface, area, volume, pose, posture, manifestation, body language, dynamic representation, movement, movement sequence, gesture, stretch, contraction, deformation, body representation (e.g., head, face, eyes, mouth, tongue, hair, voice, neck, limbs, arms, hands, legs, feet, muscles, moving parts), surface representation (e.g., shape, texture, material, color, electromagnetic (EM) properties, visual pattern, wetness, reflectivity, translucency, flexibility), material properties (e.g., biological tissue, hair, cloth, metal, wood, leather, plastic, artificial material, solid, liquid, gas, temperature), movement, activity, behavior, change in representation, and / or any combination.

[0025] The wireless signals may include transmit / receive signals, EM emissions, RF signals / transmissions, signals in licensed / unlicensed / ISM bands, band-limited signals, baseband signals, wireless / mobile / cellular communication signals, mesh signals, optical signals / communications, downlink / uplink signals, unicast / multicast / broadcast signals, standard (e.g., WLAN, WWAN, WBAN, international, industry, de facto, IEEE 802, 802.11 / 15 / 16, WiFi, 802.11n / ac / ax / be, 3G / 4G / LTE / 5G / 7G / 8G, 3GPP, Bluetooth, BLE, Zigbee, RFID, UWB, WiMax) compliant signals, standard frames, beacon / pilot / probe / inquiry / handshake / synchronization signals, management / control / data frames, management / control / data signals, standardized wireless / cellular communication protocols, reference signals, source signals, operational probe / detection / sensing signals, and / or sequences of signals. The wireless signal may include a line-of-sight (LOS) component and / or a non-LOS component (or path / link). Each CI may be extracted / generated / calculated / sensed at a layer of a Type 2 device (e.g., the PHY / MAC layer in the OSI model) and acquired by an application (e.g., software, firmware, driver, app, wireless monitoring software / system).

[0026] A wireless multipath channel may include a communication channel, an analog frequency channel (e.g., with analog carrier frequencies around 700 / 800 / 900 MHz, 1.8 / 1.8 / 2.4 / 3 / 5 / 6 / 27 / 60 GHz), a coded channel (e.g., in CDMA), and / or a channel of a wireless network / system (e.g., WLAN, WiFi, mesh, LTE, 4G / 5G, Bluetooth, Zigbee, UWB, RFID, microwave). It may include two or more channels. The channels may be contiguous (e.g., with adjacent / overlapping bands) or non-contiguous (e.g., non-overlapping WiFi channels, one at 2.4 GHz and one at 5 GHz).

[0027] The TSCI may be extracted from a wireless signal at a layer of a type-2 device (e.g., a layer of the OSI reference model, a physical layer, a data link layer, a logical link control layer, a media access control (MAC) layer, a network layer, a transport layer, a session layer, a presentation layer, an application layer, a TCP / IP layer, an Internet layer, or a link layer). The TSCI may be extracted from a derived signal (e.g., a baseband signal, a motion detection signal, or a motion sensing signal) derived from a wireless signal (e.g., an RF signal). It may be a (wireless) measurement sensed by a communication protocol (e.g., a standardized protocol) using an existing mechanism (e.g., a wireless / cellular communication standard / network, 3G / LTE / 4G / 5G / 6G / 7G / 8G, WiFi, IEEE 802.11 / 15 / 16). The motion detection signal may include a packet having at least one of a preamble, a header, and a payload (e.g., for data / control / management in a wireless link / network). The TSCI may be extracted from a probe signal (e.g., training sequence, STF, LTF, L-STF, L-LTF, L-SIG, HE-STF, HE-LTF, HE-SIG-A, HE-SIG-B, CEF) within a packet. The motion detection / sensing signal may be recognized / identified based on the probe signal. The packet may be a standard-compliant protocol frame, a management frame, a control frame, a data frame, a sounding frame, an excitation frame, an illumination frame, a null data frame, a beacon frame, a pilot frame, a probe frame, a request frame, a response frame, an association frame, a reassociation frame, a disassociation frame, an authentication frame, an action frame, a report frame, a poll frame, an announcement frame, an extension frame, an inquiry frame, an acknowledgement frame, an RTS frame, a CTS frame, a QoS frame, a CF-Poll frame, a CF-Ack frame, a block acknowledgement frame, a reference frame, a training frame, and / or a synchronization frame.

[0028] The packet may include control data and / or motion detection probes. Data (e.g., Type 1 device ID / parameters / characteristics / settings / control signals / commands / instructions / notifications / broadcast-related information) may be obtained from the payload. A wireless signal may be transmitted by a Type 1 device. It may be received by a Type 2 device. A database (e.g., in a local server, hub device, cloud server, storage network) may be used to store TSCI, characteristics, STI, signatures, patterns, behaviors, trends, parameters, analysis, output responses, identification information, user information, device information, channel information, venue (e.g., map, environment model, network, proximity device / network) information, task information, class / category information, presentation (e.g., UI) information, and / or other information.

[0029] A Type 1 / Type 2 device may include at least one of electronics, circuitry, transmitter (TX) / receiver (RX) / transceiver, RF interface, "Origin Satellite" / "Tracker Bot", unicast / multicast / broadcast device, wireless source device, source / destination device, wireless node, hub device, target device, motion detection device, sensor device, remote / wireless sensor device, wireless communication device, wireless enabled device, standard compliant device, and / or receiver. A Type 1 (or Type 2) device may be heterogeneous, because multiple instances of a Type 1 (or Type 2) device may have different circuits, enclosures, structures, purposes, auxiliary functions, chips / ICs, processors, memory, software, firmware, network connectivity, antennas, brands, models, appearances, forms, shapes, colors, materials, and / or specifications. A Type 1 / Type 2 device may include an access point, a router, a mesh router, an Internet of Things (IoT) device, a wireless terminal, one or more radio / RF subsystems / radio interfaces (e.g., 2.4 GHz radio, 5 GHz radio, fronthaul radio, backhaul radio), a modem, an RF front end, an RF / radio chip, or an integrated circuit (IC).

[0030] At least one of Type 1 devices, Type 2 devices, links between them, objects, characteristics, STI, motion monitoring, and tasks may be associated with an identification (ID) such as a UUID. Type 1, Type 2, and other devices may acquire, store, retrieve, access, preprocess, condition, process, analyze, monitor, and apply TSCI. Type 1 and Type 2 devices may exchange network traffic over other channels (e.g., Ethernet, HDMI, USB, Bluetooth, BLE, WiFi, LTE, other networks, wireless multipath channels) in parallel with wireless signals. Type 2 devices may passively observe, monitor, or receive wireless signals from Type 1 devices over wireless multipath channels without establishing a connection (e.g., association / authentication) with or requesting service from the Type 1 devices.

[0031] A transmitter (i.e., Type 1 device) can temporarily, sporadically, continuously, repeatedly, interchangeably, alternatingly, simultaneously, concurrently, and / or contemporaneously function as a receiver (i.e., Type 2 device), and vice versa. A device can temporarily, sporadically, continuously, repeatedly, simultaneously, concurrently, and / or contemporaneously function as a Type 1 device (transmitter) and / or a Type 2 device (receiver). There may be multiple wireless nodes, each of which is a Type 1 (TX) and / or a Type 2 (RX) device. A TSCI may be obtained for each two nodes as they exchange / transmit wireless signals. An object's characteristics and / or STI may be monitored individually based on the TSCI or jointly based on two or more (e.g., all) TSCIs.

[0032] The movement of an object can be monitored actively (in Type 1 devices, Type 2 devices, or both, wearable / associated with the object) and / or passively (both Type 1 and Type 2 devices are not wearable / associated with the object). It can be passive because the object may not be associated with Type 1 and / or Type 2 devices. The object (e.g., a user, an automated guided vehicle, or an AGV) may not need to carry / attach any wearable / fixture (i.e., Type 1 and Type 2 devices are not wearable / attached devices that the object needs to carry to perform a task). The object can be active because it can be associated with either Type 1 and / or Type 2 devices. The object can carry (or have) a wearable / fixture (e.g., a Type 1 device, a Type 2 device, or a device communicatively coupled to either a Type 1 device or a Type 2 device).

[0033] The presentation may be visual, audio, image, video, animation, graphical presentation, text, etc. The computation of the tasks may be performed by a processor (or logic unit) of the Type 1 device, a processor (or logic unit) of the IC of the Type 1 device, a processor (or logic unit) of the Type 2 device, a processor (or logic unit) of the IC of the Type 2 device, a local server, a cloud server, a data analysis subsystem, a signal analysis subsystem, and / or another processor. The tasks may be performed with or without reference to a radio fingerprint or baseline (e.g., collected, processed, computed, transmitted, and / or stored in a training phase / survey / current survey / previous survey / recent survey / initial radio survey, passive fingerprint), training, profile, trained profile, static profile, survey, initial radio survey, initial setup, installation, retraining, update, and reset.

[0034] A Type 1 device (TX device) may comprise at least one heterogeneous radio transmitter. A Type 2 device (RX device) may comprise at least one heterogeneous radio receiver. A Type 1 device and a Type 2 device may be co-located. A Type 1 device and a Type 2 device may be the same device. Any device may have a data processing unit / apparatus, a computing unit / system, a network unit / system, a processor (e.g., a logic unit), a memory communicatively connected to the processor, and a set of instructions stored in the memory that are executed by the processor. Some processors, memories, and instruction sets may be coordinated.

[0035] There may be multiple Type 1 devices interacting (e.g., communicating, exchanging signals / control / notification / other data) with the same Type 2 device (or multiple Type 2 devices) and / or there may be multiple Type 2 devices interacting with the same Type 1 device. Multiple Type 1 / Type 2 devices may be synchronous and / or asynchronous with the same / different window width / size and / or time shift, the same / different synchronization start time, synchronization end time, etc. Wireless signals transmitted by multiple Type 1 devices may be sporadic, intermittent, continuous, repetitive, synchronous, simultaneous, and / or concurrent. Multiple Type 1 / Type 2 devices may operate independently and / or cooperatively. Type 1 and / or Type 2 devices may have / be equipped with / be heterogeneous hardware circuits (e.g., heterogeneous chips or heterogeneous ICs capable of generating / receiving wireless signals, extracting CI from received signals, or making CI available). They may be communicatively connected to the same or different servers (e.g., cloud servers, edge servers, local servers, hub devices).

[0036] The operation of one device may be based on the operation, state, internal state, storage, processor, memory output, physical location, computing resources, or network of another device. Different devices may communicate directly and / or through another device / server / hub device / cloud server. A device may be associated with one or more users with associated settings. Settings may be selected once, pre-programmed, and / or changed (e.g., adjusted, modified, revised) / changed over time. A method may have additional steps. Method steps and / or additional steps may be performed in the order shown or in a different order. Any steps may be performed in parallel, iteratively, or in other ways. A user may be a human, adult, elderly, male, female, young, child, baby, pet, animal, living being, machine, computer module / software, etc.

[0037] For one or more Type 1 devices interacting with one or more Type 2 devices, any processing (e.g., time domain, frequency domain) may be different for different devices and may be based on location, orientation, direction, role, user-related characteristics, settings, configuration, available resources, available bandwidth, network connection, hardware, software, processor, co-processor, memory, battery life, available power, antenna, antenna type, directional / omnidirectional characteristics of antenna, power settings, and / or other parameters / characteristics of the device.

[0038] A wireless receiver (e.g., a Type 2 device) may receive a signal and / or another signal from a wireless transmitter (e.g., a Type 1 device). The wireless receiver may receive another signal from another wireless transmitter (e.g., a second Type 1 device). The wireless transmitter may transmit a signal and / or another signal to another wireless receiver (e.g., a second Type 2 device). The wireless transmitter, the wireless receiver, another wireless receiver, and / or another wireless transmitter may be moving with the object and / or another object. The other object may be tracked.

[0039] A Type 1 and / or Type 2 device may be capable of wirelessly connecting with at least two Type 2 and / or Type 1 devices. The Type 1 device may be caused / controlled to switch / establish a wireless connection (e.g., association, authentication) from the Type 2 device to a second Type 2 device at another location within the venue. Similarly, the Type 2 device may be caused / controlled to switch / establish a wireless connection from the Type 1 device to a second Type 1 device at yet another location within the venue. The switching may be controlled by a server (or hub device), a processor, the Type 1 device, the Type 2 device, and / or another device. The radio used before and after switching may be different. A second radio signal (second signal) may be transmitted between the Type 1 device and the second Type 2 device (or between the Type 2 device and the second Type 1 device) over the channel. A second TSCI of the channel extracted from the second signal may be obtained. The second signal may be the first signal. A property, STI, and / or another quantity of the object may be monitored based on the second TSCI. The Type 1 device and the Type 2 device may be the same. The property, STI, and / or another quantity with different timestamps may form a waveform. The waveform may be displayed in a presentation.

[0040] The wireless signal and / or another signal may have embedded data. The wireless signal may be a sequence of probe signals (e.g., repeated transmission of probe signals, reuse of one or more probe signals). The probe signal may change / vary over time. The probe signal may be a standard-compliant signal, a protocol signal, a standardized wireless protocol signal, a control signal, a data signal, a wireless communication network signal, a cellular network signal, a WiFi signal, an LTE / 5G / 6G / 7G signal, a reference signal, a beacon signal, a motion detection signal, and / or a motion sensing signal. The probe signal may be formatted according to a wireless network standard (e.g., WiFi), a cellular network standard (e.g., LTE / 5G / 6G), or another standard. The probe signal may include a packet having a header and a payload. The probe signal may have embedded data. The payload may include data. The probe signal may be replaced by a data signal. The probe signal may be embedded in a data signal. The wireless receiver, the wireless transmitter, another wireless receiver, and / or another wireless transmitter may be associated with at least one processor, a memory communicatively connected to the respective processor, and / or a respective set of instructions stored in the memory that, when executed, cause the processor to perform any and / or all steps required to determine the object's STI (e.g., motion information), initial STI, initial time, direction, instantaneous location, instantaneous angle, and / or velocity.

[0041] The processor, memory, and / or set of instructions may be associated with a Type 1 device, one of at least one Type 2 device, an object, a device associated with the object, another device associated with the venue, a cloud server, a hub device, and / or another server.

[0042] A Type 1 device may transmit a signal to at least one Type 2 device in a broadcast manner over a channel within the venue. The signal is transmitted without the Type 1 device establishing a wireless connection (e.g., association, authentication) with any Type 2 device and without the Type 2 device requesting service from the Type 1 device. A Type 1 device may transmit to a specific media access control (MAC) address common to two or more Type 2 devices. Each Type 2 device may adjust its MAC address to the specific MAC address. The specific MAC address may be associated with the venue. The association may be recorded in an association table in an association server (e.g., a hub device). The venue may be identified by a Type 1 device, a Type 2 device, and / or another device based on the specific MAC address, the sequence of the probe signal, and / or at least one TSCI extracted from the probe signal.

[0043] For example, a Type 2 device may be moved to a new location within a venue (e.g., from another venue). A Type 1 device may be newly set up at a venue such that the Type 1 and Type 2 devices are unaware of each other. During setup, the Type 1 device may be commanded / guided / controlled (e.g., using a dummy receiver, using a hardware pin configuration / connection, using a saved configuration, using a local configuration, using a remote configuration, using a downloaded configuration, using a hub device, or using a server) to send a sequence of probe signals to a specific MAC address. Upon powering up, the Type 2 device may scan for probe signals according to a table of MAC addresses (e.g., stored in a designated source, server, hub device, cloud server) that may be used to broadcast in different locations (e.g., homes, offices, enclosures, floors, multi-story buildings, stores, airports, malls, stadiums, halls, stations, subways, blocks, areas, zones, regions, provinces, cities, countries, continents). When the Type 2 device detects a probe signal sent to a specific MAC address, it can use the table to identify the venue based on the MAC address.

[0044] The location of the Type 2 device at the venue may be calculated based on the particular MAC address, the sequence of probe signals, and / or at least one TSCI obtained by the Type 2 device from the probe signals. The calculation may be performed by the Type 2 device.

[0045] The specific MAC address may be changed (e.g., adjusted, varied, modified) over time. It may be changed according to a time table, rule, policy, mode, condition, situation, and / or change. The specific MAC address may be selected based on MAC address availability, a preselected list, collision patterns, traffic patterns, data traffic between the Type 1 device and another device, available bandwidth, random selection, and / or a MAC address switching plan. The specific MAC address may be the MAC address of a second wireless device (e.g., a dummy receiver or a receiver acting as a dummy receiver).

[0046] The Type 1 device may transmit a probe signal on a channel selected from the set of channels, and at least one CI of the selected channel may be obtained by each Type 2 device from the probe signal transmitted on the selected channel.

[0047] The selected channel may be changed (e.g., adjusted, varied, modified) over time. The change may be according to a time table, rule, policy, mode, condition, situation, and / or change. The selected channel may be selected based on channel availability, random selection, a preselected list, co-channel interference, inter-channel interference, channel traffic patterns, data traffic between the Type 1 device and another device, effective bandwidth associated with the channel, security criteria, channel switching plans, criteria, quality criteria, signal quality conditions, and / or considerations.

[0048] The specific MAC address and / or selected channel information may be communicated between the Type 1 device and a server (e.g., a hub device) over a network. The specific MAC address and / or selected channel information may further be communicated between the Type 2 device and a server (e.g., a hub device) over another network. A Type 2 device may communicate the specific MAC address and / or selected channel information to another Type 2 device (e.g., via a mesh network, Bluetooth, WiFi, NFC, ZigBee, etc.). The specific MAC address and / or selected channel may be selected by a server (e.g., a hub device). The specific MAC address and / or selected channel may be signaled on an announcement channel by the Type 1 device, the Type 2 device, and / or the server (e.g., a hub device). Any information may be preprocessed before communication occurs.

[0049] A wireless connection (e.g., association, authentication) between a Type 1 device and another wireless device may be established (e.g., using a signal handshake). The Type 1 device may send a first handshake signal (e.g., a sounding frame, a probe signal, a request-to-send (RTS)) to the other device. The other device may respond by sending a second handshake signal (e.g., a command or a clear-to-send (CTS)) to the Type 1 device, triggering the Type 1 device to transmit a signal (e.g., a sequence of probe signals) to multiple Type 2 devices in a broadcast manner without establishing a connection with the Type 2 device. The second handshake signal may be a response or acknowledgment (e.g., an ACK) to the first handshake signal. The second handshake signal may include data having information about the venue and / or the Type 1 device. The other device may be a dummy device having a purpose (e.g., a primary purpose, a secondary purpose) to establish a wireless connection with the Type 1 device, receive a first signal, and / or transmit a second signal. Another device may be physically attached to a Type 1 device.

[0050] In another example, another device may send a third handshake signal to the Type-1 device that triggers the Type-1 device to broadcast a signal (e.g., a sequence of probe signals) to multiple Type-2 devices without establishing a connection (e.g., association, authentication) with any Type-2 devices. The Type-1 device may respond to the third special signal by sending a fourth handshake signal to the other device. The other device may be used to trigger two or more Type-1 devices to broadcast. The triggering may be sequential, partially sequential, partially parallel, or fully parallel. The other device may have two or more radio circuits for triggering multiple transmitters in parallel. Parallel triggering may also be achieved using at least one additional device to perform a trigger (similar to what the other device does) in parallel with the other device. The other device may not communicate with the Type-1 device (or may suspend communication) after establishing a connection with the Type-1 device. The suspended communication may be resumed. The other device may transition to an inactive mode, hibernate mode, sleep mode, standby mode, low power mode, off mode, and / or power-down mode after establishing a connection with the Type-1 device. The other device may have a specific MAC address such that the Type 1 device sends signals to the specific MAC address. The Type 1 device and / or the other device may be controlled and / or coordinated by a first processor associated with the Type 1 device, a second processor associated with the other device, a third processor associated with the designated source, and / or a fourth processor associated with the other device. The first and second processors may coordinate with each other.

[0051] A first sequence of probe signals may be transmitted by a first antenna of the Type 1 device to at least one first Type 2 device over a first channel at a first venue. A second sequence of probe signals may be transmitted by a second antenna of the Type 1 device to at least one second Type 2 device over a second channel at a second venue. The first and second sequences may or may not be different. The at least one first Type 2 device may / may not be different from the at least one second Type 2 device. The first and / or second sequences of probe signals may be broadcast without an established connection (e.g., association, authentication) between the Type 1 device and any Type 2 device. The first and second antennas may be the same or different.

[0052] The two venues may have different sizes, shapes, and multipath characteristics. The first and second venues may overlap. The respective surrounding areas around the first and second antennas may overlap. The first and second channels may be the same or different. For example, the first may be WiFi and the second may be LTE. Alternatively, both may be WiFi, but the first may be 2.4 GHz WiFi and the second may be 5 GHz WiFi. Alternatively, both may be 2.4 GHz WiFi, but may have different channel numbers, SSID names, and / or WiFi settings.

[0053] Each Type 2 device may obtain at least one TSCI from its respective series of probe signals. The CI is for an individual channel between the Type 2 device and the Type 1 device. Some first Type 2 devices and some second Type 2 devices may be the same. The first and second series of probe signals may be synchronous / asynchronous. The probe signals may be transmitted together with data or may be replaced by data signals. The first and second antennas may be the same.

[0054] A first series of probe signals may be transmitted at a first rate (e.g., 30 Hz). A second series of probe signals may be transmitted at a second rate (e.g., 200 Hz). The first and second rates may be the same or different. The first rate and / or the second rate may be changed (e.g., adjusted, varied, modified) over time. The change may be according to a time table, rule, policy, mode, condition, situation, and / or change. Any rate may be changed (e.g., adjusted, varied, modified) over time.

[0055] The first and / or second series of probe signals may be transmitted to a first MAC address and / or a second MAC address, respectively. The two MAC addresses may be the same or different. The first series of probe signals may be transmitted on a first channel. The second series of probe signals may be transmitted on a second channel. The two channels may be the same or different. The first or second MAC address, the first or second channel may be changed over time. Any change may be according to a time table, a rule, a policy, a mode, a condition, a situation, and / or a change.

[0056] The Type 1 device and another device may control and / or coordinate, may be physically attached, or may be / be within a common device. They may be controlled / connected by a common data processor or connected to a common bus interconnect / network / LAN / Bluetooth network / NFC network / BLE network / wired network / wireless network / mesh network / mobile network / cloud. They may share common memory or be associated with a common user, user device, profile, account, identity (ID), identifier, home, house, physical address, location, geographic coordinates, IP subnet, SSID, home device, office device, and / or manufacturing device.

[0057] Each Type 1 device may be a signal source for a respective set of Type 2 devices (i.e., transmit a respective signal (e.g., a respective sequence of probe signals) to a respective set of Type 2 devices). Each individual Type 2 device selects a Type 1 device from among all Type 1 devices as its signal source. Each Type 2 device may make the selection asynchronously. At least one TSCI may be obtained by each individual Type 2 device from a respective sequence of probe signals from the Type 1 devices. The TSCI is a channel between the Type 2 device and the Type 1 device.

[0058] An individual Type 2 device selects a Type 1 device as its signal source from among all Type 1 devices based on the Type 1 / Type 2 device's identification (ID) or identifier, the task being performed, past signal sources, history (e.g., of past signal sources, the Type 1 device, another Type 1 device, the individual Type 2 receiver, and / or another Type 2 receiver), switching signal source thresholds, and / or user information, account, access information, parameters, characteristics, and / or signal strength (e.g., associated with the Type 1 device and / or the individual Type 2 receiver).

[0059] Initially, a Type 1 device may be a signal source for a set of initial individual Type 2 devices (i.e., the Type 1 device transmits individual signals (sequences of probe signals) to the set of initial individual Type 2 devices), with each initial individual Type 2 device selecting a Type 1 device from among all Type 1 devices as its signal source.

[0060] A particular Type 2 device's signal source (Type 1 device) may be altered (e.g., adjusted, changed, modified) if (1) the time interval between two adjacent probe signals (e.g., between the current probe signal and the most recent probe signal, or between the next probe signal and the current probe signal) received from the Type 2 device's current signal source exceeds a first threshold, (2) the signal strength associated with the Type 2 device's current signal source falls below a second threshold, (3) the processed signal strength associated with the Type 2 device's current signal source falls below a third threshold, where the signal strength has been processed with a low-pass filter, band-pass filter, median filter, moving average filter, weighted average filter, linear filter, and / or nonlinear filter, and / or (4) the signal strength (or processed signal strength) associated with the Type 2 device's current signal source falls below a fourth threshold for a significant percentage (e.g., 70%, 80%, 90%) of a recent time window, which percentage may exceed a fifth threshold. The first, second, third, fourth, and / or fifth thresholds may be time-varying.

[0061] Condition (1) can occur when a Type 1 device and a Type 2 device gradually move away from each other, causing some probe signals from the Type 1 device to become too weak and not be received by the Type 2 device. Conditions (2)-(4) can occur when the two devices move far away from each other so that the signal strength becomes very weak.

[0062] The signal source of a Type 2 device may not change if another Type 1 device has a signal strength weaker than a factor (eg, 1, 1.1, 1.2, or 1.5) of the current signal source.

[0063] If the signal source is changed (e.g., adjusted, modified, or modified), the new signal source may become effective at a time in the near future (e.g., each next time). The new signal source may be the Type 1 device with the strongest signal strength and / or processed signal strength. The current and new signal sources may be the same / different.

[0064] A list of available Type 1 devices may be initialized and maintained by each Type 2 device. The list may be updated by examining signal strengths and / or processed signal strengths associated with each set of Type 1 devices. The Type 2 devices may select between a first series of probe signals from a first Type 1 device and a second series of probe signals from a second Type 1 device based on individual probe signal rates, MAC addresses, channels, characteristics / properties / status, tasks performed by the Type 2 devices, signal strengths of the first and second series, and / or other considerations.

[0065] The sequence of probe signals may be transmitted at a regular rate (e.g., 100 Hz). The sequence of probe signals may also be scaled at regular intervals (e.g., 0.01 seconds for 100 Hz), although each probe signal may experience small time perturbations, possibly due to timing requirements, timing control, network control, handshaking, message passing, collision avoidance, carrier sensing, congestion, resource availability, and / or other considerations.

[0066] The rate may be changed (e.g., adjusted, modified, or altered). The change may be according to a time table (e.g., changed hourly), a rule, a policy, a mode, a condition, and / or a change (e.g., changed whenever some event occurs). For example, the rate may be 100 Hz normally, but may be changed to 1000 Hz in demanding situations, or to 1 Hz in low power / standby states. The probe signal may be transmitted in bursts.

[0067] The probe signal rate may vary based on the task performed by the Type 1 or Type 2 device (e.g., a task may require 100 Hz normal and 1000 Hz momentarily for 20 seconds). In one example, transmitters (Type 1 devices), receivers (Type 2 devices), and associated tasks may be adaptively (and / or dynamically) associated with classes (e.g., classes that are low priority, high priority, urgent, critical, regular, privileged, non-subscription, subscription, payment, and / or non-payment). The (transmitter's) rate may be adjusted for some classes (e.g., high priority classes). When the needs of that class change, the rate may be changed (e.g., adjusted, modified, modified). If the receiver has very low power, the rate may be reduced to reduce the receiver's power consumption to respond to the probe signal. In one example, the probe signal may be used to wirelessly transfer power to the receiver (Type 2 device), and the rate may be adjusted to control the amount of power transferred to the receiver.

[0068] The rate may be changed by (or based on) the server (e.g., hub device), the Type 1 devices, and / or the Type 2 devices. Control signals may be communicated between them. The server may monitor, track, predict, and / or anticipate the needs of the Type 2 devices and / or tasks performed by the Type 2 devices and may control the Type 1 devices to change the rate. The server may make scheduled changes to the rate according to a timetable. The server may detect an emergency situation and change the rate immediately. The server may detect a developing condition and gradually adjust the rate.

[0069] Characteristics and / or STI (e.g., movement information) may be monitored individually based on TSCI associated with a particular Type 1 device and a particular Type 2 device, and / or jointly based on any TSCI associated with a particular Type 1 device and any Type 2 device, and / or jointly based on any TSCI associated with a particular Type 2 device and any Type 1 device, and / or globally based on any TSCI associated with any Type 1 device and any Type 2 device. Any joint monitoring may be associated with a user, user account, profile, household, venue map, venue environment model, and / or user history, etc.

[0070] A first channel between a Type 1 device and a Type 2 device may be different from a second channel between another Type 1 device and another Type 2 device, and the two channels may be associated with different frequency bands, bandwidths, carrier frequencies, modulations, wireless standards, coding, encryption, payload characteristics, networks, network IDs, SSIDs, network characteristics, network settings, and / or network parameters, etc.

[0071] The two channels may be associated with different types of wireless systems (e.g., systems such as WiFi, LTE, LTE-A, LTE-U, 2.5G, 3G, 3.5G, 4G, Beyond 4G, 5G, 6G, 7G, cellular network standards, UMTS, 3GPP, GSM, EDGE, TDMA, FDMA, CDMA, WCDMA, TD-SCDMA, 802.11 systems, 802.15 systems, 802.16 systems, mesh networks, Zigbee, NFC, WiMax, Bluetooth, BLE, RFID, UWB, microwave systems, and radar). For example, one channel may be WiFi and the other may be LTE.

[0072] The two channels may be associated with similar types of wireless systems but within different networks. For example, a first channel may be associated with a WiFi network called "Pizza and Pizza" in the 2.4 GHz band with a bandwidth of 20 MHz, and a second channel may be associated with a WiFi network with an SSID of "StarBud hotspot" in the 5 GHz band with a bandwidth of 40 MHz. The two channels may be different channels within the same network (e.g., the "StarBud hotspot" network).

[0073] In one embodiment, the wireless monitoring system may include training a classifier for multiple events in a venue based on training TSCIs associated with the multiple events. The CIs or TSCIs associated with an event may be considered / configured to include wireless samples / characteristics / fingerprints (and / or venues, environments, objects, object movements, states / emotional states / mental states / situations / stages / gestures / gaits / behaviors / movements / activities / daily activities / history / events of an object, etc.) associated with the event.

[0074] For each of a plurality of known events occurring at a venue within an individual training (e.g., survey, radio survey, initial radio survey) period associated with the known event, an individual training radio signal (e.g., an individual series of training probe signals) may be transmitted by the first type 1 heterogeneous wireless device antenna through a wireless multipath channel at the venue within the individual training period to at least one first type 2 heterogeneous wireless device using a processor, memory, and set of instructions of the first type 1 device.

[0075] At least one separate time series of training CIs (training TSCIs) may be asynchronously acquired by each of the at least one first Type-2 device from the (separate) training signal. The CIs may be CIs of a channel between the first Type-2 device and the first Type-1 device during a training period associated with a known event. The at least one training TSCI may be pre-processed. The training may be a radio survey (e.g., during installation of the Type-1 and / or Type-2 devices).

[0076] For a current event occurring at a venue in a current time period, a current wireless signal (e.g., a current series of probe signals) may be transmitted by at least one second type 2 heterogeneous wireless device, an antenna of the second type 1 heterogeneous wireless device, over a channel of the venue in a current time period related to the current event using a processor, a memory, and a set of instructions of the second type 1 device.

[0077] At least one time series of current CIs (current TSCIs) may be asynchronously obtained by each of the at least one second Type-2 device from a current signal (e.g., a sequence of current probe signals). The CIs may be CIs of a channel between the second Type-2 device and the second Type-1 device during a current time period associated with a current event. The at least one current TSCI may be preprocessed.

[0078] The classifier may be applied to classify at least one current TSCI obtained from a sequence of current probe signals by at least one second Type 2 device, to classify at least one portion of a particular current TSCI, and / or to classify a combination of at least one portion of a particular current TSCI with another portion of another TSCI. The classifier may divide the TSCIs (or characteristics / STIs or other analytical values ​​or output responses) into clusters and associate the clusters with particular events / objects / subjects / locations / movements / activities. Labels / tags may be generated for the clusters. The clusters may be stored and retrieved. A classifier may be applied to associate the current TSCI (or characteristic / STI or other analysis / output response, possibly related to the current event) with a cluster, a known / specific event, a class / category / group / cluster / set of known events / objects / locations / movements / activities, an unknown event, a class / category / group / group / list / cluster / set of unknown events / objects / locations / movements / activities, and / or another event / object / location / movement / activity / class / category / group / group / list / cluster / set. Each TSCI may include at least one CI, each associated with a respective timestamp. Two TSCIs associated with two Type 2 devices may differ in start time, duration, stop time, amount of CIs, sampling frequency, and sampling period. The CIs may have different characteristics. The first and second Type 1 devices may be in the same rocket within a venue. They may be the same device. At least one second Type 2 device (or their location) may be a replacement for at least one first Type 2 device (or their location). The particular second Type 2 device and the particular first Type 2 device may be the same device.

[0079] The subset of first Type 2 devices and the subset of second Type 2 devices may be the same. At least one second Type 2 device and / or the subset of at least one second Type 2 device may be a subset of at least one first Type 2 device. At least one first Type 2 device and / or the subset of at least one first Type 2 device may be a replacement for a subset of at least one second Type 2 device. At least one second Type 2 device and / or the subset of at least one second Type 2 device may be a replacement for a subset of at least one first Type 2 device. At least one second Type 2 device and / or the subset of at least one second Type 2 device may be in the same respective locations as the subset of at least one first Type 2 device. At least one first Type 2 device and / or the subset of at least one first Type 2 device may be in the same respective locations as the subset of at least one second Type 2 device.

[0080] The antenna of the Type 1 device and the antenna of the second Type 1 device may be in the same location within the venue. The antenna of at least one second Type 2 device and / or the antenna of a subset of at least one second Type 2 device may be in the same respective location as each antenna of the subset of at least one first Type 2 device. The antenna of at least one first Type 2 device and / or the antenna of the subset of at least one first Type 2 device may be in the same respective location as each antenna of the subset of at least one second Type 2 device.

[0081] A first section of a first duration of a first TSCI and a second section of a second duration of a second TSCI may be aligned. A map between items of the first section and items of the second section may be computed. The first section may include a first segment (e.g., a subset) of the first TSCI having a first start / end time and / or another segment (e.g., a subset) of the processed first TSCI. The processed first TSCI may be the first TSCI processed by the first operation. The second section may include a second segment (e.g., a subset) of the second TSCI having a second start time and a second end time and another segment (e.g., a subset) of the processed second TSCI. The processed second TSCI may be the second TSCI processed by the second operation. The first operation and / or the second operation may include sub-sampling, re-sampling, interpolation, filtering, transformation, feature extraction, pre-processing, and / or another operation.

[0082] A first item in a first section may be mapped to a second item in a second section. A first item in a first section may also be mapped to another item in a second section. Another item in a first section may also be mapped to a second item in a second section. The mapping may be one-to-one, one-to-many, many-to-one, or many-to-many. At least one function of the first item in a first section of a first TSCI, another item in a first TSCI, a timestamp of the first item, a time difference of the first item, an adjacent timestamp of the first item, an adjacent timestamp of the first item, another timestamp associated with the first item, a second item in a second section of a second TSCI, a timestamp of the second item, a time difference of the second item, a time difference of the second item, an adjacent timestamp of the second item, and another timestamp associated with the second item may satisfy at least one constraint.

[0083] One constraint may be that the difference between the timestamp of the first item and the timestamp of the second item is bounded upper by an adaptive (and / or dynamically adjusted) upper threshold and bounded lower by an adaptive lower threshold.

[0084] The first section may be the entire first TSCI. The second section may be the entire second TSCI. The first duration may be equal to the second duration. The section duration of the TSCI may be determined adaptively (and / or dynamically). A provisional section of the TSCI may be computed. A start time and an end time of a section (e.g., provisional section, section) may be determined. This section may be determined by removing the beginning and end portions of the provisional section. The beginning of the provisional section may be determined as follows: Iteratively, an item in the provisional section with an increasing timestamp may be considered the current item, one item at a time.

[0085] In each iteration, at least one activity measure / indicator may be calculated and / or considered. The at least one activity measure may be associated with at least one of a current item associated with a current timestamp, a past item in the interim section having a timestamp not greater than the current timestamp, and / or a future item in the interim section having a timestamp not less than the current timestamp. The current item may be added to the beginning of the interim section if at least one criterion (e.g., quality criterion, signal quality condition) associated with the at least one activity measure is met.

[0086] At least one criterion associated with the activity measure is (a) the activity measure is less than an adaptive (e.g., dynamically adjusted) upper threshold, (b) the activity measure is greater than an adaptive lower threshold, (c) the activity measure is less than the adaptive upper threshold continuously for at least a predetermined amount of consecutive timestamps, (d) the activity measure is greater than the adaptive lower threshold continuously for at least another predetermined amount of consecutive timestamps, (e) the activity measure is less than the adaptive upper threshold continuously for a predetermined amount of at least the predetermined amount of consecutive timestamps, or (f) the activity measure is less than the adaptive upper threshold continuously for at least another predetermined amount of consecutive timestamps. (g) another activity measure associated with another timestamp associated with the current timestamp is less than another adaptive upper threshold and greater than another adaptive lower threshold; (h) at least one activity measure associated with at least one individual timestamp associated with the current timestamp is less than a respective upper threshold and greater than a respective lower threshold; (i) in the set of timestamps associated with the current timestamp, the percentage of timestamps associated with activity measures less than a respective upper threshold and greater than a respective lower threshold exceeds a threshold; and (j) another criterion (e.g., quality criterion, signal quality condition).

[0087] The activity measure / index associated with an item at time T1 may comprise at least one of: (1) a first function of the item at time T1 and the item at time T1-D1, where D1 is a predetermined positive quantity (e.g., a fixed time offset); (2) a second function of the item at time T1 and the item at time T1+D1; (3) a third function of the item at time T1 and the item at time T2, where T2 is a predetermined quantity (e.g., a fixed initial reference time; T2 may be changed (e.g., adjusted, modified, corrected) over time; T2 may be updated periodically; T2 may be the beginning of a period and T1 may be a sliding time in the period); and (4) a fourth function of the item at time T1 and another item.

[0088] At least one of the first function, the second function, the third function, and / or the fourth function may be a function (e.g., F(X,Y,...)) having at least two arguments X and Y. The two arguments may be scalars. The function (e.g., F) may be at least one of X, Y, (XY), (YX), abs(XY), X^a, Y^b, abs(X^aY^b), (XY)^a, (X / Y), (X+a) / (Y+b), (X^a / Y^b), and ((X / Y)^ab), where a and b may be some predetermined quantities. For example, the function may simply be abs(XY), or (XY)^2, (XY)^4. The function may be a robust function. For example, the function may be (XY)^2 when abs(XY) is less than a threshold T, and (XY)+a when abs(XY) is greater than T. Alternatively, the function may be a constant when abs(XY) is greater than T. The function may also be bounded by a slowly increasing function when abs(Xy) is greater than T, so that outliers cannot seriously affect the results. Another example of a function may be (abs(X / Y)-a), where a=1. In this way, when X=Y (i.e., no change or no activity), the function yields a value of 0. When X is greater than Y, (X / Y) is greater than 1 (when X and Y are positive), and the function is positive. And when X is less than Y, (X / Y) is less than 1, and the function is negative. In another example, the function may be at least one of X=(X_1-X_2-...-Y_1-...-Y_n), X_i, (Y_i), abs_X_i-Y_i, X_i^b, abs_X_i^a-Y_i^b, (X_i-Y_i)^a, (X_i+a) / (Y_i+b), (X_i^a / Y_i^b), and ((X_i / Y_i)^ab), where i is the n-tuple X and Y and 1≦i≦n, e.g., the component index of X_1 is i=1 and the component index of X_2 is i=2.The function may include a component-wise summation of at least one other function among X_i, Y_i, (Y_i-i), (X_i-Y_i), X_i, Y_i^b, abs_X_i^a-Y_i^b, (X_i-Y_i)^a, (X_i+a) / (Y_i +b), (X_i^a / Y_i^b), and ((X_i / Y_i)^ab), where i is a component index of the n-tuples X and Y. The function may be of the form sum_{i=1}^n(abs(X_i / Y_i)-1) / n, or sum_{i=1}^n w_i*(abs(X_i / Y_i)-1), where w_i is some weight for component i.

[0089] The map may be computed using dynamic time warping (DTW). The DTW may comprise constraints on at least one of the map, the items of the first TSCI, the items of the second TSCI, the first duration, the second duration, the first section, and / or the second section. In the map, suppose the i-th domain item is mapped to the j-th range item. The constraint may be an allowable combination of i and j (a constraint on the relationship between i and j). A mismatch cost between a first section of a first duration of the first TSCI and a second section of a second duration of the second TSCI may be computed.

[0090] The first section and the second section may be aligned such that a map including two or more links may be established between a first item of the first TSCI and a second item of the second TSCI. At each link, one of the first items having a first timestamp may be associated with one of the second items having a second timestamp. A mismatch cost between the aligned first section and the aligned second section may be calculated. The mismatch cost may comprise a function of the item-wise cost between the first item and the second item associated by a particular link of the map and the link-wise cost associated with the particular link of the map.

[0091] The aligned first section and the aligned second section may be represented as a first vector and a second vector, respectively, of the same vector length. The mismatch cost may include at least one of a dot product, a dot product-like measure, a correlation-based measure, a correlation index, a covariance-based measure, a discrimination score, a distance, a Euclidean distance, an absolute distance, an Lk distance (e.g., L1, L2, ...), a weighted distance, a distance-like measure, and / or another similarity value between the first vector and the second vector. The mismatch cost may be normalized by the respective vector lengths.

[0092] A parameter derived from the mismatch cost between a first section of a first duration of a first TSCI and a second section of a second duration of a second TSCI can be modeled using a statistical distribution, and at least one of a scale parameter, a location parameter, and / or another parameter of the statistical distribution can be estimated.

[0093] The first section of the first duration of the first TSCI may be a sliding section of the first TSCI, and the second section of the second duration of the second TSCI may be a sliding section of the second TSCI.

[0094] A first sliding window may be applied to a first TSCI, and a corresponding second sliding window may be applied to a second TSCI, and the first sliding window of the first TSCI and the corresponding second sliding window of the second TSCI may be aligned.

[0095] A mismatch cost between the aligned first sliding window of the first TSCI and the corresponding aligned second sliding window of the second TSCI may be calculated, and the current event may be associated with at least one of a known event, an unknown event, and / or another event based on the mismatch cost.

[0096] The classifier may be applied to at least one of each first section of the first duration of the first TSCI and / or each second section of the second duration of the second TSCI to obtain at least one provisional classification result, each provisional classification result being associated with a respective first section and a respective second section.

[0097] The current event may be associated with at least one of a known event, an unknown event, a class / category / group / grouping / list / set of unknown events, and / or another event based on the mismatch cost. The current event may be associated with at least one of a known event, an unknown event, and / or another event based on the maximum number of provisional classification results corresponding to two or more sections of the first TSCI and two or more sections of the second TSCI. For example, the current event may be associated with a specific known event if the mismatch cost points to the specific known event N consecutive times (e.g., N=10). In another example, the current event may be associated with a specific known event if the percentage of mismatch costs within the last N consecutive N times that point to the specific known event exceeds a specific threshold (e.g., >80%).

[0098] In another example, the current event may be associated with a known event that achieves the lowest mismatch cost for most of the time within a certain period of time. The current event may be associated with a known event that achieves the lowest overall mismatch cost in a weighted average of at least one mismatch cost associated with at least one first section. The current event may be associated with a particular known event that achieves the lowest of the other overall costs. If no known event achieves a mismatch cost lower than a first threshold T1 in a sufficient percentage of at least one first section, the current event may be associated with an "unknown event." The current event may also be associated with an "unknown event" if none of the events achieves an overall mismatch cost lower than a second threshold T2. The current event may be associated with at least one of a known event, an unknown event, and / or another event based on the mismatch cost and additional mismatch cost associated with at least one additional section of the first TSCI and at least one additional section of the second TSCI. The known events may include at least one of a door close event, a door open event, a window close event, a window open event, a multi-state event, an on state event, an off state event, an intermediate state event, a continuous state event, a discrete state event, a human presence event, a human absence event, an indication of a living body presence event, and / or an indication of a living body absence event.

[0099] The projection for each CI may be trained using a dimension reduction method based on the training TSCI. The dimension reduction method may include at least one of principal component analysis (PCA), PCA with different kernels, independent component analysis (ICA), Fisher linear discriminant analysis, vector quantization, supervised learning, unsupervised learning, self-organizing maps, autoencoders, neural networks, deep neural networks, and / or another method. The projection may be applied to at least one of the training TSCI associated with at least one event and / or the current TSCI for the classifier.

[0100] A classifier for at least one event may be trained based on a projection and a training TSCI associated with the at least one event. At least one current TSCI may be classified / classified based on the projection and the current TSCI. The projection may be retrained using at least one of a dimensionality reduction method and another dimensionality reduction method based on at least one of the training TSCI, the at least one current TSCI before retraining the projection, and / or additional training TSCI. The other dimensionality reduction method may include at least one of principal component analysis (PCA), PCA with different kernels, independent component analysis (ICA), Fisher linear discriminant analysis, vector quantization, supervised learning, unsupervised learning, self-organizing maps, autoencoders, neural networks, deep neural networks, and / or yet another method. The classifier for at least one event may be retrained based on at least one of the retrained projection, the training TSCI associated with the at least one event, and / or the at least one current TSCI. At least one current TSCI may be classified based on the retrained projections, the retrained classifier, and / or the current TSCI.

[0101] Each CI may include a vector of complex values. Each complex value may be preprocessed to provide a magnitude of the complex value. Each CI may be preprocessed to provide a vector of non-negative real numbers including the magnitude of the corresponding complex value. Each training TSCI may be weighted in training the projection. A projection may include two or more projection components. A projection may include at least one top-level projection component. A projection may include at least one projection component that may be useful to the classifier.

[0102] Channel / Channel information / Venue / Spatial-temporal information / Movement / Object

[0103] Channel information (CI) may be associated with / include: signal strength, signal amplitude, signal phase, spectral power measurements, modem parameters (e.g., used in connection with modulation / demodulation in digital communication systems such as WiFi, 4G / LTE, etc.), dynamic beamforming information (including feedback or steering matrices generated by wireless communication devices according to a standardized process such as IEEE 802.11 or another standard), transfer function components, radio conditions (e.g., used in digital communication systems to decode digital data), measurable variables, sensing data, layer coarse / fine-grained information (e.g., physical layer, data link layer, MAC layer, etc.), digital settings, gain settings, RF filter settings, RF front-end switch settings, DC offset settings, DC correction settings, IQ compensation settings, effects on wireless signals due to the environment (e.g., venue) during propagation, input signals Conversion of (wireless signal transmitted by Type 1 device) to output signal (wireless signal received by Type 2 device), steady state behavior of the environment, condition profile, wireless channel measurements, received signal strength indicator (RSSI), channel state information (CSI), channel impulse response (CIR), channel frequency response (CFR), characteristics of frequency components (e.g., subcarriers) in the bandwidth, channel filter response, timestamps, auxiliary information, data, metadata, user data, account data, access data, security data, session data, status data, supervision data, home data, identity (ID), device data, network data, neighborhood data, environmental data, real-time data, sensor data, stored data, encrypted data, compressed data, protected data, and / or other channel information. Each CI may be associated with a timestamp and / or an arrival time. The CSI may be used to demodulate a signal similar to a signal transmitted by a transmitter through a multipath channel, or to equalize / cancel / minimize / reduce a multipath channel effect (of a transmission channel). The CI may be associated with information related to a frequency band, a frequency signature, a frequency phase, a frequency amplitude, a frequency trend, a frequency characteristic, a frequency similarity characteristic, a time domain element, a frequency domain element, a time-frequency domain element, an orthogonal decomposition characteristic, and / or a non-orthogonal decomposition characteristic of a signal passing through a channel. The TSCI may be a stream of wireless signals (e.g., a CI).

[0104] The CI may be pre-processed, processed, post-processed, stored (e.g., in a local memory, a portable / mobile memory, a removable memory, a storage network, a cloud memory, in a volatile manner, in a non-volatile manner), retrieved, transmitted, and / or received. One or more modem parameters and / or radio condition parameters may be held constant. The modem parameters may be applied to a radio subsystem. The modem parameters may represent radio conditions. A motion detection signal (e.g., a baseband signal and / or packets decoded / demodulated from the baseband signal, etc.) may be obtained by processing (e.g., downconverting) a first radio signal (e.g., an RF / WiFi / LTE / 5G signal) by the radio subsystem using radio conditions represented by the stored modem parameters. The modem parameters / radio conditions may be updated (e.g., using previous modem parameters or previous radio conditions). Both the previous modem parameters / radio conditions and the updated modem parameters / radio conditions may be applied to a radio subsystem in a digital communication system. Both the previous modem parameters / radio conditions and the updated modem parameters / radio conditions may be compared / analyzed / processed / monitored in the task.

[0105] The channel information may also be modem parameters (e.g., stored or newly calculated) used to process the wireless signal. The wireless signal may include multiple probe signals. The same modem parameters may be used to process two or more probe signals. The same modem parameters may also be used to process two or more wireless signals. The modem parameters may include parameters indicating settings or overall configurations for operation of the radio subsystem or baseband subsystem (or both) of the wireless sensor device. The modem parameters may include one or more of gain settings, RF filter settings, RF front-end switch settings, DC offset settings, or IQ compensation settings, or digital DC correction settings, digital gain settings, and / or digital filtering settings (e.g., for the baseband subsystem) for the radio subsystem. The CI may also be associated with information related to the signal's period, time signature, time stamp, time amplitude, time phase, time trend, and / or time characteristics. The CI may be associated with information related to the signal's time-frequency division, signature, amplitude, phase, trend, and / or characteristics. The CI may be associated with signal decomposition. A CI may be associated with information related to the direction, angle of arrival (AoA), angle of a directional antenna, and / or phase of a signal passing through a channel. A CI may be associated with an attenuation pattern of a signal passing through a channel. Each CI may be associated with a Type 1 device and a Type 2 device. Each CI may be associated with an antenna of a Type 1 device and an antenna of a Type 2 device.

[0106] The CI may be obtained from communication hardware (e.g., a Type 2 device or a Type 1 device) that can provide the CI. The communication hardware may be a WiFi-enabled chip / IC (integrated circuit), a chip conforming to 802.11 or 802.16 or another wireless / wireless standard, a next-generation WiFi-enabled chip, an LTE-enabled chip, a 5G-enabled chip, a 6G / 7G / 8G-enabled chip, a Bluetooth-enabled chip, an NFC-enabled chip, a BLE-enabled chip, a UWB chip, another communication chip (e.g., Zigbee, WiMax, mesh network), etc. The communication hardware computes the CI, stores the CI in a buffer memory, and makes the CI available for extraction. The CI may comprise data related to channel state information (CSI) and / or at least one matrix. The at least one matrix may be used for channel equalization, beamforming, etc. The channel may be associated with a venue. Attenuation can be due to signal propagation in the venue, signal propagation through / around the air (e.g., venue air), reflection, refraction, diffraction, and refractive media / reflective surfaces such as walls, doors, furniture, obstacles, and / or barriers. Attenuation can be due to reflections on surfaces and obstacles (e.g., reflective surfaces, obstacles) such as floors, ceilings, furniture, fixtures, objects, people, pets, etc. Each CI can be associated with a timestamp. Each CI can include N1 components (e.g., N1 frequency-domain components in the CFR, N1 time-domain components in the CIR, or N1 decomposed components). Each component can be associated with a component index. Each component can be a real, imaginary, or complex number, magnitude, phase, flag, and / or set. Each CI can comprise a vector or matrix of complex numbers, a set of mixed quantities, and / or a multidimensional collection of at least one complex number.

[0107] Components of the TSCI associated with a particular component index may form respective component time series associated with the respective index. The TSCI may be divided into N component time series. Each component time series is associated with a respective component index. Object motion characteristics / STI may be monitored based on the component time series. In one example, one or more ranges of CI components (e.g., one range from component 11 to component 23, a second range from component 44 to component 50, and a third range having only one component) may be selected for further processing based on some criteria / cost function / signal quality metric (e.g., based on signal-to-noise ratio and / or interference level).

[0108] A characteristic for each component of the component feature time series of the TSCI may be calculated. The characteristic for each component may be a scalar (e.g., energy) or a function with domain and range (e.g., autocorrelation function, transform, inverse transform). The characteristic / STI of the object motion may be monitored based on the characteristic for each component. An overall characteristic (e.g., total characteristic) of the TSCI may be calculated based on the characteristic for each component of each component time series of the TSCI. The overall characteristic may be a weighted average of the characteristic for each component. The characteristic / STI of the object motion may be monitored based on the overall characteristic. The total amount may be a weighted average of the individual amounts.

[0109] Type 1 devices and Type 2 devices may support WiFi, WiMax, beyond 3G, 4G / 4G, LTE, LTE-A, 5G, 6G, 7G, Bluetooth, NFC, BLE, Zigbee, UWB, UMTS, 3GPP, GSM, EDGE, TDMA, FDMA, CDMA, WCDMA, TD-SCDMA, mesh networks, proprietary wireless systems, IEEE 802.11 standards, 802.15 standards, 802.16 standards, 3GPP standards, and / or other wireless systems.

[0110] A common wireless system and / or a common wireless channel may be shared by a Type 1 transceiver and / or at least one Type 2 transceiver. The at least one Type 2 transceiver may transmit their respective signals simultaneously (or asynchronously, synchronously, sporadically, continuously, repeatedly, simultaneously, contemporaneously, and / or temporarily) using the common wireless system and / or the common wireless channel. The Type 1 transceiver may transmit signals to the at least one Type 2 transceiver using the common wireless system and / or the common wireless channel.

[0111] Each Type 1 device and Type 2 device may have at least one transmit / receive antenna. Each CI may be associated with one of the transmit antennas of the Type 1 device and one of the receive antennas of the Type 2 device. Each pair of transmit and receive antennas may be associated with a link, path, communication path, signal hardware path, etc. For example, if the Type 1 device has M (e.g., 3) transmit antennas and the Type 2 device has N (e.g., 2) receive antennas, there may be MxN (e.g., 3x2=6) links or paths. Each link or path may be associated with a TSCI.

[0112] At least one TSCI may correspond to various antenna pairs between the Type 1 device and the Type 2 device. The Type 1 device may have at least one antenna. The Type 2 device may also have at least one antenna. Each TSCI may be associated with an antenna of the Type 1 device and an antenna of the Type 2 device. Averaging or weighted averaging across antenna links may be performed. The averaging or weighted averaging may be performed across the at least one TSCI. The averaging may optionally be performed over a subset of the at least one TSCI corresponding to a subset of the antenna pairs.

[0113] The timestamps of some CIs of a TSCI may be irregular and may be corrected so that the corrected timestamps of the time-corrected CIs may be uniformly spaced in time. In the case of multiple Type 1 devices and / or multiple Type 2 devices, the corrected timestamps may be with respect to the same or different clocks. An original timestamp associated with each of the CIs may be determined. The original timestamps may not be uniformly spaced in time. The original timestamps of all CIs of a particular portion of a particular TSCI within the current sliding time window may be corrected so that the corrected timestamps of the time-corrected CIs may be uniformly spaced in time.

[0114] The characteristics and / or STI (e.g., motion information) include: Position,Position,Changed Position,New Position,New Position,Position,Vertical Position,Distance,Distance,Movement,Acceleration,Acceleration,Rotational Speed,Acceleration,Direction of Movement,Azimuth,Rotation,Direction of Movement,Rotation,Path,Deformation,Reduction,Expansion,Walking,Expansion,Walking,Periodic Movement,Head Movement,Repetitive Movement,Periodic Movement,Pseudo-Periodic Movement,Impact Movement,Sudden Movement,Falling Movement,Falling Movement,Transient Movement,Transient Behavior,Movement Period,Movement Frequency,Temporal Profile,Temporal Characteristics,Temporal Characteristics,Occurrence,Change,Temporal Change,CI Change,Change in Frequency,Change in Timing,Change in Gait Cycle,Change in Timing,Gait Period period change, timing, start time, start time, end time, duration, movement history, movement type, movement classification, frequency, frequency spectrum, object configuration, object configuration, approach, approach, identification, approach, approach, head movement velocity, head movement, respiration rate, respiration rate, respiration time, respiration depth, exhalation time, inhalation time, exhalation time, exhalation time, ventilation time, ventilation interval, heart rate variability, hand movement direction, hand movement, leg movement, walking speed, hand movement velocity, hand movement velocity, position features, features related to object movement (e.g., position / position change), tool movement, machine movement, complex movement, and / or complex Number of motion combinations, events, signal statistics, signal dynamics, anomalies, motion statistics, motion parameters, motion indications, motion magnitude, motion phase, similarity score, distance score, Euclidean distance, weighted distance, L_1 norm, L_2 norm, L_k norm for k>2, statistical distance, correlation, correlation indicator, autocorrelation, autocovariance, cross-covariance, dot product, cross product, motion signal transformation, motion features, motion presence, motion absence, motion localization, motion identification, motion recognition, object presence, object absence, object entry / exit, object change, motion cycle, motion count, walking cycle le,Movement cycle,Movement rhythm,Movement,Movement rhythm,Deformation movement,Gesture,Draft,Head movement,Mouth movement,Cardiac movement,Visceral movement,Movement tendency,Size,Volume,Volume,Shape,Shape,Tag,Start / start position,End position,Start / start amount,End amount,Event,Fall event,Security event,Accident event,Home event,Office event,Factory event,Warehouse event,Manufacturing event,Line assembly event,Maintenance event,Car-related event,Navigation event,Event tracking event,Door event,Door open event,Door close event,Window event, window open event, window close event, repeatable event, one-time event, consumption, unconsumption, state, physical state, health state, welfare state, emotional state, mental state, other event, analysis, output response, and / or other information. Characteristics and / or STIs may be computed / monitored based on features computed from the CI or TSCI (e.g., feature computation / extraction). Static segments or profiles (and / or dynamic segments / profiles) may be identified / computed / analyzed / monitored / extracted / obtained / captured / marked / presented / highlighted / stored / communicated based on analysis of features. Analysis may include motion detection / motion assessment / presence detection. Computational workload may be shared between the Type 1 device, the Type 2 device, and another processor.

[0115] The Type 1 device and / or the Type 2 device may be a local device, which may be a smartphone, a smart device, a TV, a set-top box, an access point, a router, a wireless repeater, a repeater, a router, a repeater, a wireless signal repeater / extender, a speaker, a fan, a refrigerator, a fan, a microwave, an oven, a coffee machine, a hot water kettle, a table, a chair, a light, a lamp, a door lock, a camera, a motion sensor, a motion sensor, a fire hydrant, a garage door, a switch, a power adapter, a computer, a dongle, a computer, a dongle, an electronic pad, a sofa, a tile, an accessory, a home device, a vehicle device, an office device, a building device, a manufacturing device, a clock, a watch, a television, an oven, an air conditioning, an accessory, a utility, an appliance, a smart machine, a smart vehicle, an internet-enabled device, a computer, a portable computer, a tablet, a smart house, a smart office, a smart parking lot, a smart system, and / or other devices.

[0116] Each Type 1 device may be associated with a respective identifier (e.g., ID). Each Type 2 device may also be associated with a respective identity (ID). The ID may include a code, a combination of text and code, a name, a password, an account, an account ID, a web link, a web address, an index to some information, and / or another ID. The ID may be assigned. The ID may be assigned by hardware (e.g., hardwired, via a dongle and / or other hardware), software, and / or firmware. The ID may be stored (e.g., in a database, in memory, on a server (e.g., a hub device), in the cloud, locally, remotely, persistently, or temporarily) and searchable. The ID may be associated with at least one record, account, user, household, address, phone number, Social Security number, customer number, another ID, another identifier, timestamp, and / or collection of data. The ID and / or a portion of the ID of the Type 1 device may be made available to the Type 2 device. The ID may be used by Type 1 and / or Type 2 devices for registration, initialization, communication, identification, verification, detection, recognition, authentication, access control, cloud access, networking, social networking, logging, recording, cataloging, classification, tagging, association, pairing, transactions, electronic transactions, and / or intellectual property management.

[0117] The object may be a person, user, object, passenger, child, elderly, baby, sleeping baby, baby in a car, patient, worker, high value worker, professional, expert, waiter, customer in a shopping mall, traveller at airport / train station / bus terminal / shipping terminal, staff / laborer / customer service person in factory / mall / supermarket / office / workplace, service person in sewer / ventilation system / lift well, lift in lift well, elevator, inmate, tracked / monitored person, animal, plant, living thing, pet, dog, cat, smartphone, phone accessory, computer, tablet, mobile computer, dongle, computer accessory, network device, WiFi device, IoT device, smart watch, smart glasses, smart device, speaker, key, smart key, wallet, handbag, backpack, goods, cargo, luggage, equipment, motor, machine, air conditioner, fan, HVAC equipment, lighting fixture. It can be a mobile lighting fixture, a television, a camera, audio / visual equipment, a stationary device, monitoring equipment, a part, a sign, a tool, a cart, a ticket, a parking pass, a toll pass, an airline ticket, a credit card, a plastic card, an access card, food packaging, a cookware, a table, a chair, a cleaning equipment / tool, a vehicle, an automobile, a vehicle in a parking lot, goods in a warehouse / store / supermarket / distribution center, a boat, a bicycle, an aircraft, a drone, a remote controlled car / plane / boat, a remote controlled airplane / boat, a drone, a drone, a drone, a remote controlled airplane / boat, a remote controlled car / plane / boat, a remote controlled car / plane / boat, a robot, manufacturing equipment, an assembly line, materials / unfinished parts / robots / trolleys / carts in a factory, a tracked object in an airport / shopping mart / supermarket, a non-object, an absence of an object, a presence of an object, an object with a shape, an object that changes shape, an object without a shape, a liquid mass, a gas mass / smoke, a fire, a flame, an electromagnetic (EM) source, an electromagnetic medium, and / or another object.

[0118] The object itself may be communicatively connected to several networks, such as WiFi, MiFi, 3G / 4G / LTE / 5G / 6G / 7G, Bluetooth, NFC, BLE, WiMax, Zigbee, UMTS, 3GPP, GSM, EDGE, TDMA, FDMA, CDMA, WCDMA, TD-SCDMA, mesh networks, ad-hoc networks, and / or other networks. The object itself may be bulky and AC-powered, but is moved during installation, cleaning, maintenance, renovation, etc. It may also be installed on a mobile platform, such as a lift, pad, mobile platform, elevator, conveyor belt, robot, drone, forklift, car, boat, vehicle, etc. The object may have multiple parts, each with a different motion (e.g., position / change of position). For example, the object may be a person walking forward. While walking, his left and right hands may move in different directions with different instantaneous speeds, accelerations, motions, etc.

[0119] The wireless transmitter (e.g., a Type 1 device), wireless receiver (e.g., a Type 2 device), another wireless transmitter, and / or another wireless receiver may travel with the object and / or another object (e.g., in a previous trip, a current trip, and / or a future trip). They may be communicatively coupled to one or more nearby devices. They may transmit TSCIs and / or information related to the TSCIs to nearby devices and / or to each other. They may be associated with nearby devices. The wireless transmitter and / or wireless receiver may be part of a small (e.g., coin-sized, cigarette-box-sized, or even smaller), lightweight, portable device. The portable device may be wirelessly coupled to nearby devices.

[0120] The nearby devices may be smartphones, iPhones, Android phones, smart devices, smart appliances, smart vehicles, smart gadgets, smart TVs, smart refrigerators, smart speakers, smart watches, smart glasses, smart pads, iPads, computers, wearable computers, notebook computers, gateways, etc. The nearby devices may be connected to a cloud server, a local server (e.g., a hub device), and / or other servers via the Internet, a wired Internet connection, and / or a wireless Internet connection. The nearby devices may also be portable. The portable device, nearby devices, local server (such as a hub device), and / or cloud server can share computation and / or storage for tasks (e.g., acquiring TSCI, determining object characteristics / STI related to object movement (e.g., position / change in position), computing time series of power (e.g., signal strength) information, determining / computing specific features, searching for local extrema, classification, identifying specific values ​​of time offset, denoising, processing, simplification, cleaning, wireless smart sensing tasks, CI extraction from signals, switching, segmentation, estimated trajectory / path / trajectory, processing maps, processing trajectory / path / trajectory based on environmental models / constraints / limits, correction, modification, adjustment, map-based (or model-based) correction, false detection, boundary hit, thresholding) and information. The nearby device can move / not move with the object. The nearby device may be portable / non-portable / mobile / not mobile. The nearby device may use battery power, solar power, AC power, and / or other power sources. The nearby device may have replaceable / non-replaceable and / or rechargeable / non-rechargeable batteries. The nearby device may be similar to the object. The nearby device may have the same (and / or similar) hardware and / or software as the object.The nearby devices may be smart devices, network-enabled devices, devices with connections to WiFi / 3G / 4G / 5G / 6G / Zigbee / Bluetooth / NFC / UMTS / 3GPP / GSM / EDGE / TDMA / FDMA / CDMA / WCDMA / TD-SCDMA / ad hoc networks / other networks, smart speakers, smart watches, smart clocks, smart appliances, smart machines, smart equipment, smart tools, smart vehicles, internet-enabled devices, internet-enabled devices, computers, portable computers, tablets, and other devices. At least one processor associated with the nearby devices and / or a wireless receiver, a wireless transmitter, another wireless receiver, another wireless transmitter, and / or a cloud server (in the cloud) may determine an initial STI of the object. Two or more of them may determine initial spatio-temporal information together. Two or more of them may share intermediate information in determining the initial STI (e.g., initial location).

[0121] In one example, a wireless transmitter (e.g., a Type 1 device or a tracker Bot) may move with an object. The wireless transmitter may send a signal to a wireless receiver (e.g., a Type 2 device or an Origin register) or determine the initial STI (e.g., the initial location) of the object. The wireless transmitter may also send a signal and / or another signal to another wireless receiver (e.g., another Type 2 device or another Origin register) to monitor the movement (spatio-temporal information) of the object. The wireless receiver may also receive a signal and / or another signal from the wireless transmitter and / or another wireless transmitter to monitor the movement of the object. The location of the wireless receiver and / or another wireless receiver may be known. In another example, a wireless receiver (e.g., a Type 2 device or a tracker Bot) may move with the object. The wireless receiver may receive a signal transmitted from the wireless transmitter (e.g., a Type 1 device or an Origin register) to determine the initial spatio-temporal information (e.g., the initial location) of the object. The wireless receiver may also receive a signal and / or another signal from another wireless transmitter (e.g., another Type 1 device or another Origin registration) to monitor the current movement (e.g., space-time information) of the object. The wireless transmitter may also transmit a signal and / or another signal to the wireless receiver and / or another wireless receiver (e.g., another Type 2 device or another Tracker Bot) to monitor the movement of the object. The location of the wireless transmitter and / or another wireless transmitter may be known.

[0122] A venue can be a sensing area, sensing area, room, house, office, property, workplace, corridor, passageway, lift, lift well, escalator, elevator, sewer, ventilation system, staircase, collection venue, duct, air duct, pipe, tube, enclosed space, closed structure, semi-enclosed structure, confined area, area with at least one wall, plant, machinery, engine, wooden structure, glass structure, metal structure, structure with walls, structure with doors, structure with gaps, structure with reflective surfaces, structure with fluid, building, rooftop, store, factory, assembly line, hotel room, museum, classroom, school, university, government building, warehouse, garage, mall, airport, train station, bus terminal, hub, transport hub, transport terminal, government facility, public facility, school, university, entertainment facility. Entertainment facilities, hospitals, pediatric and neonatal wards, nursing homes, elderly care facilities, community centers, stadiums, parks, athletic fields, sports facilities, swimming facilities, athletic fields, basketball courts, tennis courts, soccer stadiums, baseball fields, gymnasiums, halls, garages, shopping malls, supermarkets, manufacturing facilities, parking facilities, construction sites, mining facilities, etc. Transportation facilities, highways, roads, valleys, forests, timber, terrain, landscapes, study rooms, courtyards, land, paths, amusement parks, urban areas, rural areas, suburbs, metropolitan areas, gardens, squares, music halls, urban facilities, overhead facilities, semi-open facilities, enclosed spaces, train stations, logistics centers, warehouses, stores, distribution centers, storage facilities, underground facilities, spaces (e.g., above-ground exterior spaces), indoor facilities, outdoor facilities, outdoor facilities with walls, doors, and reflectors, open facilities, semi-open facilities, cars, trucks, buses, vans, containers, ships and boats, submersibles, trains, trams, airplanes, vehicles, mobile homes, caves, tunnels, pipes, waterways, metropolitan areas, etc. A venue may be a space such as a downtown area with relatively tall buildings, a valley, a well, a duct, a passageway, a gas pipe, an oil pipe, a water pipe, an interconnecting passageway / pathway / road / pipe / cave / pipe-like structure / air space / fluid space, a human body, an animal body, a body cavity, an organ, a bone, a tooth, a soft tissue, a hard tissue, a rigid tissue, a non-rigid tissue, a blood / fluid container, a wind pipe, an air duct, etc. A venue may be an indoor space, an outdoor space, or may include both the inside and outside of a space. For example, a venue may include both the inside and outside of a building. For example, a venue may be a building with one floor or multiple floors, and part of the building may be underground.The building shape may be, for example, circular, square, rectangular, triangular, or irregular. These are merely examples. The present disclosure may be used to detect events in other types of venues or spaces.

[0123] The wireless transmitter (e.g., a Type 1 device) and / or wireless receiver (e.g., a Type 2 device) can be embedded in a portable device (e.g., a module or a device with a module) that can move with the object (e.g., in a previous movement and / or a current movement). The portable device can have a wired connection (e.g., via USB, microUSB, Firewire, HDMI, serial port, parallel port, and other connectors) and / or a connection (e.g., Bluetooth, Bluetooth Low Energy (BLE)). The portable device can be a lightweight device. The portable device can be battery-powered, rechargeable battery-powered, and / or AC-powered. The portable device can be very small (e.g., on the sub-millimeter and / or sub-centimeter scale) and / or small (e.g., coin-sized, card-sized, pocket-sized, or larger). The portable device can be large, bulky, and / or heavy (e.g., heavy equipment installed).Portable devices include WiFi hotspots, Mobile WiFi (MiFi), Access points / Micro USB / Smartphones, Tablets, Computers, Smart devices, WiFi enabled devices, LTE enabled devices, Smart mirrors, Smart batteries, Smart lights, Smart pens, Smart rings, Smart doors, Smart clocks, Smart batteries, Smart belts, Smart handbags, Smart clothing, Smart packaging, Smart paper / books / magazines / printed materials / signs / displays / lighting systems, Smart keys / tools, Smart bracelets / chains / necklaces / wearables / accessories, Smart pads / cushions / blocks, bricks / building materials, Smart trash cans, Smart food carriages / storage, Smart balls / rackets, Smart chairs / sofas / beds, Smart shoes / carpets / mats / hand hats / handwear, Smart hats / makeup / stickers / tattoos, Smart mirrors, Smart pills, Smart pills, Smart The device may be a food bottle / food container, smart device, IoT device, WiFi enabled device, 3G / 4G / 6G enabled device, UMTS device, 3GPP device, EDGE device, TDMA device, CDMA device, WCDMA device, embeddable device, air conditioning, refrigerator, furnace, oven, cooking device, TV / set top box (STB) / DVD player / video player / remote control, hi-fi, audio device, speaker, lighting, door, roofing, roofing structure, equipment, installation, lawn mower, garden tool, machinery and equipment / garage can / 40ft / container, 20ft / garage container, factory / manufacturing equipment, repair tool, factory / production tool, machine, machinery, vehicle, cart, wagon, warehouse, vehicle, automobile, bicycle, boat, ship, basket / box / bucket / container, smart plate / cup / bowl / pot / mat / mat / cookware / kitchen tool / kitchen utensil / cabinet / table / chair / tile / lighting / water pipe / faucet / gas range / oven / dishwasher / , etc. The portable device may have a battery that may be replaceable, non-replaceable, rechargeable, and / or non-rechargeable. The portable device may be wirelessly charged.The portable device may be a smart payment card. The portable device may be a payment card used in parking lots, highways, entertainment parks, or other places / facilities requiring payment. The portable device may have an identity (ID) / identifier, as described above.

[0124] Events can be monitored based on the TSCI. Events can be an object (e.g., a person and / or a patient) falling, rolling, pausing, or impacting (e.g., a punching bag, a door, a bed, a chair, a table, a desk, a cabinet, a box, another person, an animal, a bird, a table, a fly, a table, a chair, a ball, a bowling ball, a tennis ball, a soccer ball, a baseball, a basketball, a basketball, a volleyball), the movement of two people's bodies (e.g., a person releasing a balloon, a person catching a fish, a person molding clay, a person writing on paper, a person typing on a computer), a car moving in a garage, a person carrying a smartphone and walking around an airport / mall / government / building / office / etc., an autonomously mobile object / machine moving around (e.g., a vacuum cleaner, a utility vehicle, a car, a drone, a self-driving car).

[0125] The tasks or wireless smart sensing tasks may include: object detection, presence detection, proximity detection, object recognition, activity recognition, object verification, daily activity monitoring, well-being monitoring, vital signs monitoring, health status monitoring, baby monitoring, elderly monitoring, sleep monitoring, sleep status monitoring, gait monitoring, movement monitoring, tool detection, tool recognition, tool verification, patient detection, patient monitoring, patient verification, machine detection, machine recognition, machine verification, human detection, human recognition, baby detection, baby recognition, baby verification, human breathing detection, human breathing recognition, human breathing estimation, human breathing verification, human heart rate detection, human heart rate recognition, human heart rate estimation, fall detection, fall recognition, fall verification, fall verification, emotion detection, emotion recognition, emotion estimation, emotion verification, motion recognition, motion estimation, motion verification, motion degree estimation, periodic motion detection, periodic motion recognition, periodic motion estimation, periodic motion verification, repetitive motion detection, repetitive motion recognition, repetitive motion estimation, repetitive motion verification, steady motion detection, steady motion recognition, steady motion estimation, steady motion verification, cyclo Steady motion detection, cyclo steady motion recognition, cyclo steady motion estimation, cyclo steady motion verification, transient motion detection, transient motion recognition, transient motion estimation, transient motion verification, trend detection, trend verification, breathing detection, breathing recognition, breathing estimation, human biometric detection, human biometric recognition, human biometric estimation, human biometric verification, environmental informatics detection, environmental informatics recognition, environmental informatics estimation, environmental informatics verification, gait detection, gait recognition, gait estimation, gait verification, gesture detection, gesture recognition, gesture estimation, gesture verification, machine learning, unsupervised learning, semi-supervised learning, cluster Ring, Feature Extraction, Feature Training, Principal Component Analysis, Eigenvalue Decomposition, Frequency Decomposition, Time Decomposition, Time-Frequency Decomposition, Functional Decomposition, Other Decomposition, Training, Fractional Training, Semi-Supervised Training, Unsupervised Training, Semi-Supervised Training, Neural Networks, Sudden Motion Detection, Fall Detection, Hazard Detection, Life Threat Detection, Steady Motion Detection, Steady Motion Detection, Cyclo-Steady Motion Detection, Intrusion Detection, Intrusion Motion Detection, Suspicious Motion Detection, Security, Safety Monitoring, Navigation, Guidance, Map-Based Processing, Map-Based Correction, Model-Based Processing / Correction,Irregularity detection, location detection, indoor sensing, tracking, multiple object tracking, indoor tracking, indoor location tracking, indoor navigation, energy management, power transfer, wireless power transfer, object counting, vehicle tracking in a parking lot, activation of devices / systems (e.g., security systems, access systems, alarms, sirens, speakers, televisions, entertainment systems, cameras, heating / air conditioning (HVAC) systems, ventilation systems, lighting systems, gaming systems, coffee machines, cooking devices, cleaning devices, housekeeping devices), shape estimation, augmented reality, wireless communication, data communication, signal broadcasting, networking, coordination, management, encryption, protection, cloud computing, other processing, and / or other tasks. The tasks may be performed by a Type 1 device, a Type 2 device, another Type 1 device, another Type 2 device, a nearby device, a local server (e.g., a hub device), an edge server, a cloud server, and / or another device. The tasks may be based on TSCI between any pair of Type 1 and Type 2 devices. A Type 2 device may also be a Type 1 device, and vice versa. A Type 2 device may temporarily, continuously, sporadically, simultaneously, and / or concurrently fulfill / perform the roles (e.g., functionality) of a Type 1 device, and vice versa. The first portion of the tasks may include at least one of the following: preprocessing, signal processing, signal processing, conditioning, signal processing, signal processing, adjustment, signal processing, mapping / continuous / mapping / continuous / adaptive / mapping / request, adjustment, feature extraction, encoding, encoding, modifying, encoding, modifying, motion detection, motion detection, motion change detection, motion detection pattern, motion detection pattern, motion recognition pattern, vital sign detection, vital sign estimation, vital sign recognition, periodic motion detection, periodic motion estimation, repetitive motion detection / breathing rate detection, breathing rate detection, breathing pattern detection, breathing pattern estimation, breathing pattern recognition, heart rate detection, heart rate estimation, heart rate pattern detection, heart rate pattern estimation, heart rate pattern recognition, gesture detection, gesture estimation, gesture recognition, velocity detection, velocity estimation, object location estimation, object tracking, navigation, acceleration estimation, acceleration detection, fall detection, change detection, intruder (and / or illicit activity) detection, baby detection, baby monitoring,Patient monitoring, object recognition, wireless power transfer, and / or wireless charging.

[0126] The second portion of the task may be a smart home task, a smart office task, a smart factory task (e.g., manufacturing using machines or assembly lines), a smart Internet of Things (IoT) task, a smart home operation, a smart office operation, a smart building operation (e.g., moving supplies / parts / raw materials to a machine / assembly line), an IoT operation, a smart system operation, turning on lights, controlling lights in at least one of the rooms, areas, and / or venues, playing a sound clip, playing a sound clip in at least one of the rooms, areas, and / or venues, playing at least one of a welcome, greeting, well-being, first message, and / or second message associated with the first portion of the task, turning on appliances, controlling equipment in the rooms, areas, and / or venues, or controlling equipment in a venue, controlling an electrical system, turning on a room, an electrical system, controlling an electrical system in a room, area, and / or venue, turning on a security system, turning off a security system, controlling a security system in a room, area, and / or venue, turning on a mechanical system, controlling a mechanical system, controlling a mechanical system in a room, area, and / or venue, and / or controlling at least one of an air conditioning system, a heating system, a ventilation system, a lighting system, a lighting device, a stove, an entertainment system, a door, a fence, a window, a garage, a computer system, a networked device, a networked device, a system, an appliance, an appliance, an office equipment, a lighting device, a robot (such as a robotic arm), a smart vehicle, a smart machine, an assembly line, a smart device, an Internet of Things (IoT) device, a smart home device, and / or a smart office device.

[0127] Tasks may include: detecting when a user comes home, detecting when a user moves from one room to another, detecting windows / garage doors / blinds / curtains / panels / solar panels / sunshades, detecting / monitoring when a user does something (e.g. sleeping on the sofa, running in the bedroom, cooking on the sofa, watching TV, eating in the kitchen, going up / down stairs, coming home in the break room), monitoring / detecting the location of a user / pet, automatically doing something when a user is detected, turning lights on / off, turning on music / radio / home entertainment system, turning on / off TV / HiFi / Set-STB / Home Entertainment System / Smart Speaker / Smart Device turning on / off / adjusting / controlling the air conditioning system, turning on / off / adjusting the ventilation system, turning on / off / adjusting the heating system, adjusting / controlling curtains / light shades, turning on / off / waking up the computer, turning on / off / preheating the coffee machine / hot water kettle, turning on / off / controlling / preheating the cooker / oven / microwave / other cooking device, turning on / off / adjusting the oven / microwave / other cooking device, checking / adjusting the temperature forecast, checking the phone message box, checking email, checking / adjusting the system, checking / adjusting / controlling the system / arm / safety protection system / baby monitor, checking / controlling the refrigerator (e.g. via speaker such as Google Home, Amazon Echo, on a display / screen, via a webpage / email).

[0128] For example, when a user arrives home in their car, the tasks may be to automatically detect that the user or their car is approaching, open the garage door upon detection, turn on the driveway / garage lights, turn on the air conditioner / heater / fan, etc. As the user approaches the garage, the tasks may include automatically turning on the entrance lights, turning off the driveway / garage lights, playing a greeting message welcoming the user, turning on music, turning on the user's preferred radio news channel, opening the curtains / blinds, monitoring the user's mood, adjusting the lighting and sound environment according to the user's mood or current / impending events (e.g., romantic lighting and music because the user is scheduled to have dinner with their girlfriend in an hour), warming up food in the microwave that the user prepared that morning, running diagnostic checks on all systems in the house, checking the weather forecast for tomorrow's tasks, checking news of interest to the user, checking the user's calendar and to-do list, playing reminders, and checking the phone answering system / messaging system / email. and give a verbal report using a dialogue system / speech synthesis (e.g., using a TV / entertainment system / computer / notebook / display / light / brightness / pattern / symbol, using a haptic tool / virtual reality tool / gesture / tool, using a smart device / appliance / material / equipment / appliance, using a web tool / server / server hub device / cloud server / cloud server / edge server / home network / mesh network, using a messaging tool / notification tool / communication tool / scheduling tool / email, using a user interface / GUI, using a scent / smell / aroma / taste, using a neural tool / neurological tool, using a combination), call the user and her on their mother's birthday, create a report, give the report (e.g., using a tool for recall as described above), give the report. Tasks can include proactively turning on an air conditioning / heating / ventilation system or proactively adjusting the temperature setting on a smart thermostat, etc.When the user moves from the entrance to the living room, the tasks may be to turn on the living room lights, open the living room curtains, open the window, turn off the entrance light behind the user, turn on the TV and set-top box, set the TV to the user's preferred channel, adjust the appliances according to the user's preferences and conditions / states (e.g., adjust the lighting and select / play music to create a romantic atmosphere), etc.

[0129] Another example is when a user wakes up in the morning, the tasks may be to detect the user moving around in the bedroom, open the blinds / curtains, open the windows, turn off the alarm clock, adjust the indoor temperature from a night temperature profile to a day temperature profile, turn on the bedroom light, turn on the bathroom light as the user approaches the bathroom, check the radio or streaming channels, play the morning news, turn on the coffee machine and preheat water, turn off the security system, etc. When the user walks from the bedroom to the kitchen, the tasks may be to turn on the kitchen and hallway lights, turn off the bedroom and bathroom lights, move music / messages / reminders from the bedroom to the kitchen, turn on the kitchen TV, change the TV to the morning news channel, lower the kitchen blinds, open the kitchen window to let in fresh air, unlock the back door for the user to check the back yard, adjust the kitchen temperature setting, etc. Another example is when a user leaves home for work, the tasks could be to detect the user leaving, play a farewell message, open / close the garage door, turn on / off the garage and driveway lights, turn off / dim lights to save energy (only if the user forgets), close / lock all windows / doors (only if the user forgets), turn off appliances (especially the stove, oven, microwave), turn on / arm the home security system to protect the home from intruders, adjust the air conditioning / heating / ventilation system to an "away from home" profile to save energy, send alerts / reports / updates to the user's smartphone, etc.

[0130] Motion may include at least one of the following: no motion, still motion, no motion, movement, change of place / location, deterministic motion, transient motion, falling motion, repetitive motion, periodic motion, quasi-periodic motion, periodic / repetitive motion associated with breathing, periodic / repetitive motion associated with heartbeat, periodic / repetitive motion associated with living things, periodic / repetitive motion associated with machines, periodic / repetitive motion associated with man-made objects, periodic / repetitive motion associated with nature, complex motion with transient and periodic elements, repetitive motion, non-deterministic motion, stochastic motion, chaotic motion, random motion, complex motion with non-deterministic and deterministic elements, stationary random motion, pseudo-stationary random motion, cyclo-stationary random motion, non-stationary random motion, periodic autocorrelation function (A CF), random motion with periodic ACF, periodic quasi-steady motion, random motion with quasi-periodic components whose instantaneous ACF is periodic, machine motion, mechanical motion, vehicle motion, drone motion, atmosphere-related motion, wind-related motion, weather-related motion, water-related motion, fluid-related motion, ground-related motion, electromagnetic property changes, underground motion, earthquake motion, plant motion, animal motion, human motion, normal motion, abnormal motion, dangerous motion, rain, fire, flood, tsunami, explosion, collision, near collision, human body motion, head motion, face motion, eye motion, mouth motion, tongue motion, neck motion, finger motion, hand motion, arm motion, shoulder motion, body motion, chest motion, abdominal motion, waist motion, leg motion, foot motion, body joint motion, knee motion, elbow motion, upper body motion, lower body motion, skin motion, subskin motion, subcutaneous tissue motion. Vascular movement, venous movement, organ movement, cardiac movement, pulmonary movement, stomach movement, intestinal movement, bowel movement, eating movement, breathing movement, facial expressions, eye expressions, mouth expressions, speaking movement, singing movement, eating movement, gestures, hand gestures, arm movements, keystrokes, typing strokes, user interface gestures, man-machine interaction, walking, dancing movement, coordination movement, and / or coordinated body movement.

[0131] The heterogeneous IC of the Type 1 device and / or any Type 2 receiver may include a low noise amplifier (LNA), a power amplifier, a transmit / receive switch, a media access controller, a baseband radio, a 2.4 GHz radio, a 3.65 GHz radio, a 4.9 GHz radio, a 5 GHz radio, a 5.9 GHz radio, a sub-6 GHz radio, a sub-60 GHz radio, and / or another radio. The heterogeneous IC may include a processor, a memory communicatively coupled to the processor, and a set of instructions stored in the memory to be executed by the processor. The IC and / or any processor may include at least one of a general-purpose processor, a special-purpose processor, a microprocessor, a multiprocessor, a multi-core processor, a parallel processor, a CISC processor, a RISC processor, a microcontroller, a central processing unit (CPU), a graphical processor unit (GPU), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), an embedded processor (e.g., ARM), a logic circuit, other programmable logic devices, discrete logic, and / or a combination. The heterogeneous IC may support a broadband network, a wireless network, a cellular network, a wireless local area network (WLAN), a wide area network (MAN), a WLAN standard, WiFi, LTE-A, LTE-U, an 802.11 standard, 802.11a, 802.11g, 802.11ac, 802.11ad, 802.11ah, 802.11ax, 802.11ay, a network mesh standard, an 802.16 standard, a cellular network standard, 3G, 3.5G, 4G, 5G, 6G, 7G, 8G, 9G, UMTS, 3GPP, GSM, EDGE, TDMA, CDMA, WCDMA, TD-SCDMA, Bluetooth Low Energy (BLE), NFC, Zigbee, WiMax, and / or another wireless network protocol.

[0132] The processor may comprise a general-purpose processor, a special-purpose processor, a microprocessor, a microcontroller, an embedded processor, a digital signal processor, a central processing unit (CPU), a graphical processing unit (GPU), a multiprocessor, a multi-core processor, and / or a processor with graphics capabilities, and / or a combination thereof. The memory may be volatile, non-volatile, random-access memory (RAM), read-only memory (ROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), a hard disk, flash memory, CD-ROM, DVD-ROM, magnetic storage, optical storage, organic storage, a storage system, a storage network, network storage, cloud storage, edge storage, local storage, external storage, internal storage, or any other form of non-transitory storage medium known to those skilled in the art. The set of instructions (machine-executable code) corresponding to the method steps may be embodied directly in hardware, software, firmware, or a combination thereof. The set of instructions may be embedded, pre-loaded, loaded at startup, loaded on-the-fly, loaded on-demand, pre-installed, installed, and / or downloaded.

[0133] The presentation can be audiovisual (e.g., using a combination of visuals, graphics, text, symbols, color, shade, video, animation, sound, speech, audio, etc.), graphical (e.g., using GUI, animation, video), textual (e.g., web pages with text, messages, animated text), symbolic (e.g., emoticons, signs, hand gestures), or mechanical (e.g., vibration, actuator movement, haptics, etc.) presentation.

[0134] Basic operations

[0135] The computational workload associated with the method is shared among the processor, the type 1 heterogeneous wireless device, the type 2 heterogeneous wireless device, a local server (eg, a hub device), a cloud server, and another processor.

[0136] Operations, pre-processing, processing, and / or post-processing may be applied to the data (e.g., TSCI, autocorrelation, TSCI features). Operations may be pre-processing, processing, and / or post-processing. Pre-processing, processing, and / or post-processing may be operations.Operations include pre-processing, post-processing, scaling, computing line-of-sight (LOS) quantities, computing quantities including LOS and NLOS, computing quantities for a single link (e.g., a path, a communications path, a link between a transmit antenna and a receive antenna), computing quantities including multiple links, computing functions of operands, linear filtering, nonlinear filtering, folding, energy computation, low-pass filtering, band-pass filtering, median filtering, quartile filtering, mode filtering, finite impulse response (FIR) subsampling, upsampling, time correction, time-based correction, amplitude correction, phase correction, phase cleaning, amplitude cleaning, matched filtering, enhancement, restoration, noise removal, smoothing, signal conditioning, enhancement, restoration, spectral analysis, linear transform, nonlinear transform, inverse transform, frequency transform, inverse transform, Fourier transform (FT), discrete-time FT (DFT), fast FT (FFT), wavelet transform, Hilbert transform, trigonometric transform, sine transform, cosine transform, DCT, power 2 transform, sparse transform, graph-based Transformation, Fast Transform, Zero Padding, Circular Padding, Zero Padding, Feature Extraction, Decomposition, Orthogonal Projection, Non-Complete Projection, Eigenvalue Decomposition (SVD), Principal Component Analysis (ICA), Grouping, Thresholding, Hard Thresholding, Clipping, First Derivative, Higher Order Derivative, Convolution, Multiplication, Least Squares, Local Deviation Minimization, Neural Networks, Recognition, Labeling, Unsupervised Learning, Semi-Supervised Learning, Comparison with Another TSCI, Similarity Score Operation, Quantization, Matching Pursuit, Compression, Encryption, Transmission, Normalization, Time Normalization, Frequency Domain Normalization, Classification, Labeling The operations may include filtering, labeling, learning, training, mapping, remapping, storing, searching, receiving, representing, merging, combining, tracking, matched filtering, Kalman filtering, interpolation error correction, performing, doing nothing, time-varying processing, regulated average, weighted average, arithmetic average, geometric average, harmonic average, average over selected frequencies, average over antenna links, logical operations, permutation, combination, sorting, AND, OR, XOR, union, intersection, vector addition, vector subtraction, vector multiplication, vector division, inverse, norm, distance, and / or another operation. The operations may be pre-processing, processing, and / or post-processing. The operations may be applied to multiple time series or functions together.

[0137] Functions (e.g., functions of operands) may include: scalar function, vector function, continuous function, magnitude function, trigonometric function, logic function, trigonometric function, linear function, piecewise function, real function, vector-valued function, inverse function, derivative of integral, derivative of function, one-to-one function, many-to-one function, many-to-many function, zero crossing, absolute function, indicator function, mean, mode, median, range, statistics, histogram, variance, deviation, divergence, range, total variation, absolute deviation, total deviation, arithmetic mean, geometric mean, trimmed mean, percentile, square root, multiplier, cosine, cosine , tangent, cotangent, secant, elliptic functions, parabolic functions, game functions, zeta functions, absolute value, threshold functions, floor functions, rounding functions, quantization, piecewise constant functions, composite functions, time functions processed in operations (e.g., probability functions, ergodic functions, probability functions, periodic functions, probability functions, inverse frequency transforms, discrete time transforms, Laplace transforms, sine transforms, cosine transforms, trigonometric transforms, wavelet transforms, integer transforms, power 2 transforms, sparse transforms, decomposition, PCA, independent component analysis (ICA), neural networks, feature extraction, moving window functions for time series, filtering functions, convolution functions, mean functions, histograms, variance / standard deviation functions, short-term transforms, discrete transforms , Discrete Fourier Transform, Discrete Cosine Transform, Eigenvalue Decomposition (SVD), Singular Value, Matching Pursuit, Sparse Transform, Graph-Based Transform, Graph Processing, Classification, Graph Signal Processing, Classification, Labeling, Machine Learning, Detection, Feature Extraction, Network Feature Extraction, Noise Reduction, Coding, Encryption, Remapping, Vector Quantization, High-Pass Filtering, Matched Filtering, Kalman Filtering, Preprocessing, Particle Filtering, FIR Filtering, Autoregressive (AR) Filtering, Adaptive Filtering, Higher Order Differentiation, Integration, Zero Crossing, Smoothing, Mode Filtering, Sampling, Random Sampling, Resampling Function, Downsampling, Upsampling, Interpolation, Importance Sampling, Monte Carlo Sampling, Compressed Sensing, Statistics, Short-Term Statistics, Long-Term Statistics, Autocorrelation Function, Cross-Correlation, Moment Generating Function, Time Average, Weighted Average, Special Function, Bessel Function, Error Function, Complementary Error Function, Beta Function, Gamma Function, Integral Function, Gaussian Function, Poisson Function, etc.

[0138] Machine learning, training, discriminative training, deep learning, neural networks, continuous time processing, distributed computing, distributed storage, acceleration using GPU / DSP / coprocessors / multi-core / multiprocessing may be applied to a step (or each step) of this disclosure.

[0139] The frequency transform may include a Fourier transform, a Laplace transform, a Hadamard transform, a Hilbert transform, a sine transform, a cosine transform, a trigonometric transform, a wavelet transform, an integer transform, a square transform, a combined zero-padding and transform, a Fourier transform with zero-padding, and / or another transform. Fast and / or approximate versions of the transform may be performed. The transform may be performed using floating-point and / or fixed-point arithmetic.

[0140] The inverse frequency transform may include an inverse Fourier transform, an inverse Laplace transform, an inverse Hadamard transform, an inverse Hilbert transform, an inverse sine transform, an inverse cosine transform, an inverse trigonometric transform, an inverse wavelet transform, an inverse integer transform, an inverse square transform, a combined zero-padding and transform, an inverse Fourier transform with zero-padding, and / or another transform. Fast and / or approximate versions of the transform may be performed. The transform may be performed using floating-point and / or fixed-point arithmetic.

[0141] Quantities / features from the TSCI may be computed. The quantities may include at least one of the following: movement, location, position, coordinates, speed, movement angle, movement amount, movement amount, pattern, time, trend, pattern, time pattern, repetitive pattern, time pattern, mutually exclusive pattern, association / correlation, cause / correlation, short term / impact, correlation, short term / impact, correlation, trend, tendency, statistics, typical behavior, typical behavior, time trend, time profile, periodic movement, periodic movement, repetition, repetition, movement, repetition, trend, change, sudden change, frequency, transient change, frequency, transient change, respiration, behavior, event, dangerous event, alarm, alert, warning, proximity, collision, power, signal, signal power, signal strength, signal strength, received signal strength indicator (RSSI), signal amplitude, signal, phase signal, frequency component. , signal frequency components, non-orthogonal statistics, cardiopulmonary statistics, power statistics, heart rate, statistics / analysis, daily activity statistics, tracking, heart rate, statistics / analysis, medical statistics / analysis, early (or immediate or simultaneous) indicator / indication / indicator / verifier / indication / suggestion / sign / detection / symptom, disease / condition / situation, biometric, baby, patient, machine, equipment, temperature, vehicle, parking lot, location, elevator, elevator shaft, space, fluid flow, home, room, office, house, building, warehouse, storage, system, ventilation, fan, duct, person, human, car, boat, truck, plane, drone, downtown, crowd, impulse event, cyclostatic, environment, vibration, material, surface, 3 dimensional, 2 dimensional, local, global, presence, and / or another measurable quantity / variable.

[0142] Sliding Window Algorithm

[0143] The sliding time window may have a time-varying window width, which may be initially smaller to allow for fast acquisition and may increase over time to a steady-state size. The steady-state size may be related to the frequency, repetitive motion, transient motion, and / or STI being monitored. Even in the steady state, the window size may be adaptively (and / or dynamically) changed (e.g., adjusted, changed, modified) based on battery life, power consumption, available computing power, changes in the amount of target, the nature of the motion to be monitored, etc.

[0144] The time shift between two sliding time windows at adjacent time instances can be constant / variable / locally adaptive / dynamically adjusted over time. When a shorter time shift is used, any monitoring updates can be more frequent, which can be used for rapidly changing conditions, object motion, and / or objects. A longer time shift can be used for slower conditions, object motion, and / or objects.

[0145] The window width / size and / or time shift may be changed (e.g., adjusted, changed, modified) according to user requests / selections. The time shift may be changed automatically (e.g., as controlled by a processor / computer / server / hub device / cloud server) and / or adaptively (and / or dynamically).

[0146] At least one characteristic (e.g., a characteristic value or characteristic point) of a function (e.g., an autocorrelation function, an autocovariance function, a cross-correlation function, a cross-covariance function, a power spectral density, a time function, a frequency domain function, a frequency transform) may be determined (e.g., by the object tracking server, a processor, a type 1 heterogeneous device, a type 2 heterogeneous device, and / or another device). The at least one characteristic of the function may include: a maximum, a minimum, an extremum, a limit, a local extremum with a positive time offset, a first extremum with a positive time offset, a local extremum with a negative time offset, an nth extremum, a constrained extremum, a constrained maximum, a significant extremum, a slope, a derivative, a maximum slope, a local extremum with a positive time offset, a local maximum slope, a constrained maximum slope, a maximum higher order derivative, a constrained higher order derivative, a constrained higher order derivative, a zero crossing with a positive time offset, an nth zero crossing with a negative time offset, an nth zero crossing with a negative time offset, a constrained zero crossing, a zero crossing of a slope, a zero crossing of a higher order derivative, and / or another characteristic. At least one argument of the function related to at least one characteristic of the function may be identified. Some quantity (e.g., spatiotemporal information of the object) may be determined based on the at least one argument of the function.

[0147] The characteristics (e.g., characteristics of the movement of an object at a venue) may include at least one of the following: instantaneous characteristics, short-term characteristics, repetition characteristics, temporal characteristics, amplitude characteristics, temporal characteristics, fluctuation characteristics, orthogonal decomposition characteristics, probability characteristics, stochastic characteristics, autocorrelation function (ACF), mean, variance, spread, deviation, divergence, range, absolute deviation, total deviation, statistics, duration, timing, trend, periodic characteristics, long-term characteristics, historical characteristics, current characteristics, past characteristics, predicted characteristics, position, distance, velocity, velocity, acceleration, angular velocity, change in angular velocity, change in object, angular acceleration, object direction, angle of rotation, deformation of object, shape of object, change in shape of object, change in size of object, change in structure of object, and / or change in characteristics of object.

[0148] At least one local maximum and at least one minimum of the function may be identified. At least one local signal-to-noise ratio-like (SNR-like) parameter may be calculated for each pair of adjacent local maximums and minima. The SNR-like parameter may be some function (e.g., linear, logarithmic, exponential, monotonic) of the amount (e.g., power, magnitude) of the local maximum over the same amount of the local minimum. It may also be a function of the difference between the amount of the local maximum and the same amount of the minimum. Significant local peaks may be identified or selected. Each significant local peak may be a local maximum with an SNR-like parameter greater than a threshold T1 and / or a local maximum with an amplitude greater than a threshold T2. At least one minimum and at least one minimum in the frequency domain may be identified / calculated using a persistence-based approach.

[0149] A set of selected significant local peaks may be selected from the set of identified significant local peaks based on selection criteria (e.g., quality criteria, signal quality conditions). An object characteristic / STI may be computed based on the selected set of significant local peaks and frequency values ​​associated with the selected set of significant local peaks. In one example, the selection criteria may correspond to always selecting the strongest peak in a range. The strongest peak may be selected, but peaks that are not selected may still be significant (fairly strong).

[0150] Unselected significant peaks may be stored and / or monitored as "reserved" peaks for use in future selections in future sliding time windows. As an example, a particular peak (at a particular frequency) may appear consistently over time. Initially, it may be significant but not selected (because other peaks may be stronger). However, later, the peak may become stronger and more dominant and may be selected. When it is "selected," it may be "selected" retroactively in time to an earlier time when it was significant but not selected. In such a case, the backtraced peak may replace the previously selected peak at an earlier time. The replaced peak may be a relatively weak peak or a peak that appears alone in time (i.e., appears only briefly in time).

[0151] In another example, the selection criteria may not correspond to selecting the most intense peak in the range: instead, it may consider not only the "intensity" of the peak, but also the "trace" of the peak (peaks that may have occurred in the past, especially peaks that have been identified for a long time).

[0152] For example, if a finite state machine (FSM) is used, it may select the peak(s) based on the state of the FSM, and the decision threshold may be adaptively (and / or dynamically) computed based on the state of the FSM.

[0153] The similarity score and / or component similarity score may be computed (e.g., by a server (e.g., a hub device), a processor, a Type 1 device, a Type 2 device, a local server, a cloud server, and / or another device) based on pairs of temporally adjacent CIs of a TSCI. The pairs may come from the same sliding window or two different sliding windows. The similarity score may also be based on pairs of temporally adjacent or non-adjacent CIs from two different TSCIs. The similarity score and / or component similarity score may be time-reversed resonance strength (TRRS), correlation, cross-correlation, autocorrelation, correlation index, covariance, cross-covariance, autocovariance, dot product of two vectors, distance score, norm, metric, quality metric, signal quality condition, statistical property, discrimination score, neural network, deep learning network, machine learning, training, discrimination, weighted averaging, preprocessing, noise removal, signal conditioning, filtering, time correction, timing compensation, phase offset compensation, transformation, component-wise operation, feature extraction, finite state machine, and / or another score. The characteristics and / or STIs may be determined / calculated based on the similarity scores.

[0154] Any threshold may be predetermined, adaptively (and / or dynamically) determined, and / or determined by a finite state machine. Adaptive determination may be based on time, space, location, antenna, path, link, condition, battery life, remaining battery life, available power, available computing resources, available network bandwidth, etc.

[0155] A threshold to be applied to a test statistic to distinguish between two events (or two conditions, or two situations, or two states) A ​​and B may be determined. Data (e.g., CI, channel state information (CSI), power parameters) may be collected under A and / or under B in a training situation. The test statistic may be computed based on the data. The distribution of the test statistic under A may be compared to the distribution of the test statistic under B (a reference distribution), and the threshold may be selected according to some criteria. The criteria may include maximum likelihood (ML), maximum a posteriori probability (MAP), discriminative training, minimum type 1 error for a given type 2 error, minimum type 2 error for a given type 1 error, and / or other criteria (e.g., quality criteria, signal quality conditions). The threshold may be adjusted to achieve different sensitivities to A, B, and / or other events / conditions / situations / states. The threshold adjustment may be automatic, semi-automatic, and / or manual. The threshold adjustment may be applied once, occasionally, frequently, periodically, repeatedly, occasionally, sporadically, and / or on-demand. Threshold adjustment may be adaptive (and / or dynamically adjusted) and may depend on the object, object movement / location / orientation / action, object characteristics / STI / size / characteristics / properties / habits / behavior, venue, features / fixtures / furniture / barriers / materials / machines / creatures / object boundaries / surfaces / media, map, map (or environment model) constraints, event / state / situation / condition, time, timing, duration, current state, past history, user, and / or personal preferences, etc.

[0156] A stopping criterion (or skip, bypass, blocking, pause, pass, or reject criterion) for an iterative algorithm may be that the change in the current parameter (e.g., offset value) in the update in an iteration is less than a threshold. The threshold may be 0.5, 1, 1.5, 2, or another number. The threshold may be adaptive (and / or dynamically adjusted) and may change as the iterations progress. For the offset value, the adaptive threshold may be determined based on the task, the specific value of the first time, the current time offset value, the regression window, the regression analysis, the regression function, the regression error, the convexity of the regression function, and / or the number of iterations.

[0157] The local extrema may be determined as a corresponding extremum of the regression function in the regression window. The local extrema may be determined based on a set of time offset values ​​within the regression window and a set of associated regression function values. Each of the set of associated regression function values ​​associated with the set of time offset values ​​may be within a range from the corresponding extremum of the regression function in the regression window.

[0158] Searching for local extrema may include: robust search, minimization, maximization, optimization, statistical optimization, binary optimization, constrained optimization, convex optimization, global optimization, local optimization, energy minimization, linear regression, quadratic regression, higher order regression, linear programming, nonlinear programming, stochastic programming, combinatorial optimization, constrained programming, constraint satisfaction, calculus of variations, optimal control, dynamic programming, mathematical programming, convex optimization, convex optimization, local optimization, convex optimization, local optimization, linear regression, quadratic regression Calculus of variations, optimal control, dynamic programming, mathematical programming, multi-objective optimization, multidimensional optimization, separable programming, space mapping, infinite dimensional optimization, heuristics, metaheuristics, convex programming, semidefinite programming, conic programming, integer programming, quadratic programming, fractional programming, numerical analysis, simplex methods, iterative methods, gradient descent, subgradient methods, coordinate descent, conjugate gradient methods, Newton's method, sequential quadratic programming, interior point methods, ellipsoid methods, reduced gradient methods, quasi-Newton methods, simultaneous perturbation stochastic approximation, interpolation methods, pattern search methods, line search, non-differential optimization, genetic algorithms, evolutionary algorithms, dynamic relaxation, hill climbing, particle swarm optimization, gravitational search algorithms, simulated annealing, mimetic algorithms, differential evolution, dynamic relaxation, stochastic tunneling, tabu search, reaction search optimization, curve fitting, least squares, simulation-based optimization, variations, and / or variates. The search for local extrema may be associated with an objective function, a loss function, a cost function, a utility function, a fitness function, an energy function, and / or an energy function.

[0159] The regression can be performed using a regression function to fit the sampled data (e.g., CIs, features of CIs, components of CIs) or another function (e.g., an autocorrelation function) to a regression window. In at least one iteration, the length of the regression window and / or the position of the regression window can be varied. The regression function can be a linear function, a quadratic function, a cubic function, a polynomial function, and / or another function.

[0160] The regression analysis may be performed using a number of different weights: error, total error, component error, error in the projection domain, error in a selected orthogonal axis, error in a selected orthogonal axis, absolute error, squared error, absolute deviation, squared deviation, squared deviation, higher order error (e.g., third order, fourth order), robust error (e.g., squared error for smaller errors, absolute error for larger error magnitudes, or first type of error for smaller error magnitudes and second type of error for larger error magnitudes), separate error, weighted sum (or weighted average) of absolute / squared errors (e.g., a wireless transmitter with multiple antennas and a wireless receiver with multiple antennas, where each pair of transmitter antenna and receiver antenna forms a link), mean absolute error, mean squared error, mean absolute deviation. Errors associated with different links may have different weights. One possibility is that some links and / or some components with greater noise or lower signal quality metrics may have smaller or larger weights. A weighted sum of squared errors, a weighted sum of higher-order errors, a weighted sum of robust errors, a weighted sum of alternative errors, an absolute cost, a squared cost, a higher-order cost, a robust cost, an alternative cost, a weighted sum of absolute costs, a weighted sum of squared costs, a weighted sum of higher-order costs, a weighted sum of robust costs, and / or a weighted sum of alternative costs.

[0161] The determined regression error may be an absolute error, a squared error, a higher order error, a robust error, a further error, a weighted sum of absolute errors, a weighted sum of squared errors, a weighted sum of higher order errors, a weighted sum of robust errors, and / or a weighted sum of further errors.

[0162] The time offset associated with the maximum regression error (or minimum regression error) of the regression function for a particular function within the regression window may become the current time offset updated in the iteration.

[0163] The local extremum may be searched for based on a quantity including the difference between two different errors (e.g., the difference between an absolute error and a squared error), where each of the two different errors may include an absolute error, a squared error, a higher-order error, a robust error, another error, a weighted sum of absolute errors, a weighted sum of squared errors, a weighted sum of higher-order errors, a weighted sum of robust errors, and / or a weighted sum of another error.

[0164] The quantity may be compared to reference data or a reference distribution, such as an F-distribution, a central F-distribution, another statistical distribution, a threshold, a threshold associated with a probability / histogram, a threshold associated with a probability / histogram of finding a false peak, a threshold associated with an F-distribution, a threshold associated with a central F-distribution, and / or a threshold associated with another statistical distribution.

[0165] The regression window may be determined based on at least one of the following: object motion (e.g., change in position / location), a quantity associated with the object, at least one characteristic and / or STI of the object associated with the object motion, an estimated location of a local extremum, noise characteristics, estimated noise characteristics, object motion (e.g., change in position / location), a quantity associated with the object, at least one characteristic and / or STI of the object associated with the object motion, an estimated location of a local extremum, noise characteristics, estimated noise characteristics, a signal quality metric, an F-distribution, a central F-distribution, another statistical distribution, a threshold, a preset threshold, a threshold associated with a probability / histogram, a threshold associated with a desired probability, a threshold associated with the probability of finding a false peak, a threshold associated with an F-distribution, a threshold associated with a central F-distribution, a threshold associated with another statistical distribution, a condition that the quantity at the window center is maximum within the regression window, a condition that the quantity at the window center is maximum within the regression window, a condition that only one of the following conditions exists: a local extremum of a particular function for a particular value of time first within the regression window, another regression window, and / or another condition.

[0166] The width of the regression window can be determined based on the specific extrema to be searched for. The extrema can include the following: a first extrema, a second extrema, a maximum extrema, a first extrema with a maximum extrema positive offset value, a second extrema with a maximum extrema positive offset value, a second extrema with a maximum extrema positive offset value, a first extrema with a maximum extrema negative offset value, a second extrema with a maximum extrema negative offset value, a first extrema with a maximum extrema negative offset value, a second extrema with a maximum extrema negative offset value, a first extrema with a maximum extrema negative offset value, a second extrema with a maximum extrema negative offset value, a first extrema with a maximum extrema positive offset value, a first extrema with a second extrema positive offset value, a second extrema with a positive offset value, a second extrema with a positive offset value, and a first extrema with a negative time offset value with a positive offset value.

[0167] The current parameter (e.g., time offset value) may be initialized based on a target value, a target profile, a trend, a past trend, a current trend, a target velocity, a target velocity profile, a target velocity profile, a past velocity trend, an object's motion or movement (e.g., position / change in position), at least one object characteristic and / or STI associated with the object's motion, an object's position quantity, an object's initial velocity associated with the object's motion, a predefined value, an initial regression window width, a time duration, a value based on the signal's carrier frequency, a value based on the signal's subcarrier frequency, a signal's bandwidth, an amount of antenna associated with the channel, noise characteristics, a signal h metric, and / or an adaptive (and / or dynamically adjusted) value. The current time offset may be at the center, left, right, and / or another fixed relative position of the regression window.

[0168] In the presentation, information may be displayed along with a map (or environmental model) of the venue. Information may include: location, zone, region, coverage area, corrected location, approximate location, location relative to the map of the venue, location relative to a segmentation of the venue, direction, route, trace (e.g., position within a time window such as the last 5 seconds or the last 10 seconds; time window duration may be adjusted adaptively (and / or dynamically); time window duration may be adjusted adaptively (and / or dynamically) with respect to speed, acceleration, etc.), route history, approximate regions / zones along the route, Past location history / summary, past location history of interest, frequently visited areas, customer traffic, crowd distribution, crowd behavior, crowd control information, which may include speed, acceleration, motion statistics, breathing rate, heart rate, presence / absence, movement of people, pets and objects, presence or absence of vital signs, behavior, gesture control (control of devices using gestures), location-based gesture control (control of devices using gestures), location-based behavior, respected identity (ID) or identifiers (pets, people, autonomous machines / devices, vehicles, drones, cars, vehicles, boats) , bicycle, bicycle, machine with fan, air conditioner, television, machine with moving parts), user identification information (person, etc.), user position / speed / acceleration / direction / movement / gesture / gesture control / motion trace, user ID or identifier, user activity, user state, user sleep / rest characteristics, user emotional state, user vital signs, venue environmental information, venue weather information, earthquake, explosion, storm, rain, fire, temperature, collision, event open, door event, event close, door event, event open, impact, event window window close, event fall down, burning event, freezing event, water related event, wind related event, air movement event, accident event, pseudo-periodic event (e.g. running on a treadmill, jumping up and down, jumping off a rope, artificial jumping, etc.), recurring event, crowd event, vehicle event, user gesture (e.g. hand gesture, arm gesture, foot gesture, leg gesture, body gesture, head gesture, face gesture, mouth gesture, eye gesture, etc.).

[0169] Location may be two-dimensional (e.g., having 2D coordinates), three-dimensional (e.g., having 3D coordinates). Location may be relative (e.g., a map or environmental model) or relational (e.g., halfway between point A and point B, around a corner, on the stairs, on a table, on the ceiling, on the floor, on a sofa, close to point A, distance R from point A, within radius R from point A, etc.). Location may be expressed in rectangular coordinates, polar coordinates, and / or another representation.

[0170] Information (e.g., location) may be marked with at least one symbol. The symbol may be time-varying. The symbol may flash and / or pulsate with or without changing color / intensity. The size may change over time. The orientation of the symbol may change over time. The symbol may be a number reflecting an instantaneous quantity (e.g., vital signs / respiratory rate / heart rate / gesture / status / user state / action / movement, temperature, network traffic, network connectivity, device / machine state, remaining device power, device status, etc.). The rate of change, size, orientation, color, intensity, and / or symbol may reflect the respective movement. Information may be presented visually and / or described verbally (e.g., using pre-recorded voice or speech synthesis). Information may be described textually. Information may also be presented in a mechanical manner (e.g., animated gadgets, moving moving parts).

[0171] The user interface (UI) device may be a smartphone (e.g., iPhone®, Android phone), a tablet (e.g., iPad®), a laptop (e.g., notebook computer), a personal computer (PC), a device with a graphical user interface (GUI), a smart speaker, a device with voice / audio / speaker functionality, a virtual reality (VR) device, an augmented reality (AR) device, a smart car, an in-car display, a voice assistant, an in-car voice assistant, etc.

[0172] The map (or environmental model) may be two-dimensional, three-dimensional, and / or higher dimensional (e.g., a time-varying 2D / 3D map / environment model). Walls, windows, doors, entrances, exits, and restricted areas may be marked on the map or model. The map may include a floor plan of the facility. The map or model may have one or more layers (overlays). The map / model may be a maintenance map / model including water pipes, gas pipes, cables, air ducts, crawl spaces, ceiling layout, and / or underground layout. The venue may be segmented / divided / subdivided / grouped into multiple zones / regions / geographical areas / sectors / sections / areas / neighborhoods / districts / areas / areas wide / wide areas, e.g., bedroom, living room, storage room, walkway, kitchen, dining room, owner, garage, first floor, second floor, break room, office, conference room, reception area, various office areas, various warehouse areas, various facility areas, etc. The segments / regions / areas may be presented on the map / model. The different regions may be color-coded. The different regions may be presented with characteristics (e.g., color, brightness, color intensity, texture, animation, blinking, blink rate, etc.) The logical segmentation of the venue may be performed using at least one heterogeneous Type-2 device, or server (e.g., hub device), or cloud server, etc.

[0173] Here are examples of the disclosed systems, devices, and methods. Stephen and his family want to install the disclosed wireless motion detection system to detect motion in their 2,000-square-foot, two-story townhouse in Seattle, Washington. Because his house has two staircases, Stephen decides to use one Type 2 device (named A) and two Type 1 devices (named B and C) on the first floor. The first floor primarily consists of three rooms arranged in a linear fashion: the kitchen, dining room, and living room, with the dining room in the center. The kitchen and living room are on opposite sides of the house. He places a Type 2 device (A) in the dining room, one Type 1 device (B) in the kitchen, and the other Type 1 device (C) in the living room. With this device arrangement, he is effectively using the motion detection system to divide the ground floor into three zones: the dining room, living room, and kitchen. When motion is detected by the A-B and A-C pairs, the system analyzes the motion information and associates the motion with one of the three zones.

[0174] When Stephen and his family go away for the weekend (e.g., to go camping for a long weekend), Stephen turns on the motion detection system using a mobile phone app (e.g., an Android phone app or an iPhone® app). When the system detects motion, an alert signal (e.g., an SMS text message, email, push message to the mobile phone app, etc.) is sent to Stephen. After Stephen pays a monthly fee (e.g., $10 / month), a service company (e.g., a security company) receives the alert signal over a wired network (e.g., broadband) or wireless network (e.g., home WiFi, LTE, 3G, 2.5G, etc.) and prompts Stephen to perform security procedures (e.g., calling him to confirm the problem, checking on the house, contacting the police on Stephen's behalf, etc.). Stephen loves his elderly mother and is concerned about her well-being when he is alone at home. While the rest of the family is out (e.g., going to work, shopping, or going on vacation), his mother uses his mobile app to turn on the motion detection system to ensure she is okay. He then uses the mobile app to monitor his mother's movements around the house. When Stephen uses the mobile app to watch his mother move around the house in three areas, according to her daily routine, Stephen knows his mother is doing well. Stephen is grateful that the motion detection system can help him monitor his mother's well-being while he is away from home.

[0175] On a typical day, Mom wakes up around 7:00 AM. She cooks breakfast in the kitchen for about 20 minutes. Then she eats breakfast in the dining room for about 30 minutes. She then does her daily exercise in the living room, sitting on the living room couch and watching her favorite TV show. The motion detection system allows Stephen to see the timing of movement in each of three areas of the house. If the movement matches her daily routine, Stephen knows that Mom should be feeling fine. However, if the movement pattern seems abnormal (e.g., no movement until 10:00 AM, spending too long in the kitchen, or not stopping for long periods of time), Stephen suspects something is wrong and calls Mom to check on her. Stephen can even have someone (e.g., family, neighbors, payers, friends, social workers, service providers) check on Mom.

[0176] Sometimes Stephen feels like relocating a Type 2 device. He simply unplugs the device from the original AC power plug and plugs it into another AC power plug. He's pleased that the wireless motion detection system is plug-and-play, and relocation doesn't affect the system's operation. It works as soon as he powers it on.

[0177] Later, Stephen discovers that the disclosed wireless motion detection system can indeed detect motion with very high accuracy and very low alarms, and he is convinced that he can actually use the mobile app to monitor motion on the ground floor. He decides to install a similar setup (i.e., one Type 2 device and two Type 1 devices) on the second floor to monitor the bedrooms there. Again, the system is very easy to set up; he simply plugs the Type 2 and Type 1 devices into the AC power plugs on the second floor. No special installation is required. He can also use the same mobile app to monitor motion on the first and second floors. Each Type 2 device on the first and second floors can interact with the Type 1 devices on both the first and second floors. Stephen is pleased to observe that doubling his investment in Type 1 and Type 2 devices more than doubles the capacity of his combined system.

[0178] According to various embodiments, each CI (CI) may include at least one of channel state information (CSI), frequency-domain CSI, frequency-domain CSI associated with at least one subband, frequency-domain CSI, time-domain CSI, channel response, estimated channel response, channel impulse response (CIR), channel frequency response (CFR), channel characteristics, channel filter response, CSI of a wireless multipath channel, information of the wireless multipath channel, timestamp, auxiliary information, data, metadata, user data, account data, access data, security data, session data, status data, supervision data, home data, identification information (ID), identifier, device data, network data, proximity data, environmental data, real-time data, sensor data, stored data, encrypted data, compressed data, protected data, and / or another CI. In one embodiment, the disclosed system includes hardware components (e.g., a wireless transmitter / receiver with an antenna, analog circuitry, a power supply, a processor, and a memory) and corresponding software components. According to various embodiments of the present teachings, the disclosed system includes a Bot (referred to as a Type 1 device) and an Origin (referred to as a Type 2 device) for vital sign detection and monitoring. Each device includes a transceiver, a processor, and a memory.

[0179] The disclosed system may be applicable in many situations. In one example, a Type 1 device (transmitter) may be a small WiFi-enabled device on a table. It may also be a WiFi-enabled television (TV), set-top box (STB), smart speaker (e.g., Amazon Echo), smart refrigerator, smart microwave, mesh network router, mesh network satellite, smartphone, computer, tablet, smart plug, etc. In one example, a Type 2 (receiver) may be a WiFi-enabled device on a table. It may also be a WiFi-enabled television (TV), set-top box (STB), smart speaker (e.g., Amazon Echo), smart refrigerator, smart microwave, mesh network router, mesh network satellite, smartphone, computer, tablet, smart plug, etc. Type 1 and Type 2 devices may be placed in or near a conference room for people counting. Type 1 and Type 2 devices may be in a health monitoring system for the elderly to monitor daily activities and any signs of symptoms (e.g., dementia, Alzheimer's disease). Type 1 and Type 2 devices may be used in an infant monitor to monitor the vital signs (breathing) of a living infant. Type 1 and Type 2 devices can be placed in bedrooms to monitor sleep quality and any sleep apnea. Type 1 and Type 2 devices can be placed in vehicles to monitor passenger and driver health, detect driver sleep, and detect infants left in the vehicle. Type 1 and Type 2 devices can be used in logistics to prevent human trafficking by monitoring people hidden in trucks and containers. Type 1 and Type 2 devices can be deployed by emergency services in disaster areas to search for victims trapped in debris. Type 1 and Type 2 devices can be deployed in an area to detect any intruder breathing. There are many applications for wireless respiratory monitoring without wearables.

[0180] The hardware modules can be built to include Type 1 transceivers and / or Type 2 transceivers. The hardware modules can be sold / used by variable brands to design, build, and sell final commercial products. Products that use the disclosed systems and / or methods can be home / office security products, WiFi products, STBs, entertainment products, TVs, entertainment products, HiFi, speakers, home appliances, ovens, tables, chairs, beds, tools, torches, vacuum cleaners, sofas, fans, doors, windows, door handles, locks, smoke detectors, car accessories, computing devices, office devices, air conditioners, heaters, connectors, monitoring cameras, access points, mobile devices, LTE devices, 3G / 4G / 6G devices, UMTS devices, GSM devices, EDGE devices, TDMA devices, CDMA devices, WCDMA devices, TD-SCDMA devices, gaming devices, eyeglasses, VR goggles, necklaces, watches, waistbands, belts, wallets, pens, hats, wearables, implantable devices, tags, parking tickets, smartphones, etc.

[0181] The summary may include an analysis, an output response, a selected time window, sub-sampling, a transformation, and / or a projection. Presenting may include presenting at least one of a month / week / day view, a simplified / detailed view, a cross-sectional view, a small / large form factor view, a color-coded view, a comparison view, a summary view, an animation, a web view, an audio announcement, and another presentation related to the cyclical / recurring nature of the repetitive behavior.

[0182] A Type 1 / Type 2 device can be: an antenna, a device having an antenna, a device with an antenna, a device with a housing (for a radio, antenna, data signal processor, radio IC, circuitry, etc.), a device with an interface to attach / connect / link an antenna, a device that interfaces / attaches / connects / links to other devices / systems / computers / phones / networks / data aggregators, a device with a user interface (UI) / graphical UI / display, a device with a wireless transceiver, a device with a wireless transmitter, a device with a wireless receiver, an IoT device, a device with a wireless network, a device with wired and wireless network capabilities, a device with a wireless integrated circuit (IC), a Wi-Fi device, a device with a Wi-Fi chip (e.g., compliant with 802.11a / b / g / n / ac / ax standards), a Wi-Fi access point (AP), a Wi-Fi client, a Wi-Fi router, a Wi-Fi Wi-Fi repeaters, Wi-Fi hubs, wireless mesh network routers / hubs / APs, ad hoc network routers, wireless mesh network equipment, mobile devices (e.g., 2G / 2.5G / 3G / 3.5G / 4G / LTE / 5G / 6G / 7G, UMTS, 3GPP, GSM, EDGE, TDMA, FDMA, CDMA, WCDMA, TD-SCDMA), mobile terminals, base stations, mobile network base stations, mobile network hubs, mobile network compatible terminals, LTE terminals, terminals equipped with LTE modules, mobile modules (e.g., boards equipped with mobile-enabled chips (ICs) such as Wi-Fi chips, LTE chips, BLE chips), devices equipped with Wi-Fi chips (ICs), LTE chips, BLE chips, or mobile modules, smartphones, companion devices for smartphones (dongles, attachments, plug-ins, etc.), dedicated devices, plug-in devices, AC-powered devices, battery-powered devices, devices with processors / memory / instruction sets, smart devices / gadgets / items.The following items may be included in the Type 1 and / or Type 2 devices: clocks, stationery, pens, user interfaces, paper, mats, cameras, televisions, set-top boxes, microphones, speakers, refrigerators, ovens, machines, phones, wallets, furniture, doors, windows, ceilings, floors, walls, tables, chairs, beds, nightstands, air conditioners, heaters, pipes, ducts, cables, carpets, decorative items, gadgets, USB devices, plugs, dongles, lamps / lights, tiles, ornaments, bottles, vehicles, automobiles, automated guided vehicles, robots, laptops, tablets, computers, hard disks, network cards, musical instruments, rackets, balls, shoes, wearables, clothing, glasses, hats, necklaces, food, pills, small devices that move within a living organism (e.g., within blood vessels, lymphatic fluid, digestive tract), and / or other devices. The Type 1 and / or Type 2 devices may be communicatively connected to the Internet, another device with access to the Internet (e.g., a smartphone), a cloud server (e.g., a hub device), an edge server, a local server, and / or storage. The Type 1 and / or Type 2 devices may operate under local control, may be controlled by another device via a wired / wireless connection, may operate automatically, or may be controlled remotely (e.g., away from the home) by a centralized system.

[0183] In one embodiment, a Type-B device may be a transceiver capable of performing both an Origin (Type-2 device, Rx device) and a Bot (Type-1 device, Tx device), i.e., a Type-B device may be both a Type-1 (Tx) and a Type-2 (Rx) device (e.g., simultaneously or alternatively), e.g., a mesh device, mesh router, etc. In one embodiment, a Type-A device may be a transceiver capable of functioning only as a Bot (Tx device), i.e., only as a Type-1 device, or only as a Tx, e.g., a simple IoT device. It may have the capabilities of an Origin (Type-2 device, Rx device), but in some embodiments, it functions only as a Bot. All Type-A and Type-B devices form a tree structure. The root may be a Type-B device with network (e.g., Internet) access. For example, it may be connected to the broadcast service through a wired connection (e.g., Ethernet, cable modem, ADSL / HDSL modem) or a wireless connection (e.g., LTE, 3G / 4G / 5G, WiFi, Bluetooth, microwave link, satellite link, etc.). In one embodiment, all Type A devices are leaf nodes. Each Type B device can be a root node, a non-leaf node, or a leaf node.

[0184] The Type 1 device (transmitter, or Tx) and Type 2 device (receiver, or Rx) may be on the same device (e.g., RF chip / IC), or may simply be on the same device. The device may operate in high frequency bands such as 28 GHz, 60 GHz, 77 GHz, etc. The RF chip may have dedicated Tx antennas (e.g., 32 antennas) and dedicated Rx antennas (e.g., another 32 antennas).

[0185] One Tx antenna can send a radio signal (e.g., a series of probing signals, perhaps at 100 Hz). Alternatively, all Tx antennas may be used (at Tx) to transmit radio signals using beamforming, so that the radio signals are focused in a direction (e.g., for energy efficiency, or to boost the signal-to-noise ratio in that direction, or for low-power operation when "scanning" that direction, or when an object is known to be in that direction).

[0186] The radio signal strikes objects (e.g., a living human being lying on a bed 4 feet away from the Tx / Rx antennas, breathing and heartbeat) in the venue (e.g., a room). Movement of the object (e.g., lung movement in response to breathing rate, or blood vessel movement in response to heartbeat) can affect / modulate the radio signal. All Rx antennas can be used to receive the radio signal.

[0187] Beamforming (in Rx and / or Tx) may be applied (digitally) to "scan" different directions. Many directions may be scanned or monitored simultaneously. In beamforming, a "sector" (e.g., direction, orientation, bearing, zone, region, segment) may be defined relative to the Type 2 device (e.g., relative to the center position of the antenna array). For each probe signal (e.g., pulse, ACK, control packet, etc.), channel information or CI (e.g., channel impulse response / CIR, CSI, CFR) is obtained / calculated (e.g., from the RF chip) for each sector. In sounding detection, CIR may be collected in a sliding window (e.g., 30 seconds; with a 100 Hz sounding / probing rate, there may be 3000 CIRs over 30 seconds).

[0188] The CIR may have many taps (e.g., N1 components / tap). Each tap may be associated with a time lag, or time of flight (tof, e.g., the time it takes to hit a person's back 4 feet away). When a person is breathing in a certain direction at a certain distance (e.g., 4 ft), the CIR for the "certain direction" may be searched for. Then, the tap corresponding to the "certain distance" may be searched for. Then, the respiration rate and heart rate may be calculated from the taps of that CIR.

[0189] Each tap within the sliding window (e.g., a 30-hour window of the "component time series") can be thought of as a time function (e.g., a "tap function," "component time series"). Each tap function can be examined in searching for strong periodic behavior (e.g., perhaps corresponding to respiration in the range 10 bpm to 40 bpm).

[0190] A Type 1 device and / or a Type 2 device may have external connections / links and / or internal connections / links. An external connection (e.g., connection 1110) may be associated with 2G / 2.5G / 3G / 3.5G / 4G / LTE / 5G / 6G / 7G / NBIoT, UWB, WiMax, Zigbee, 802.16, etc. Internal connections (e.g., 1114A and 1114B, 1118, 11120) may be associated with WiFi, IEEE 802.11 standards, 802.11a / b / g / n / ac / ag / af / ah / ai / aj / ax / ay, Bluetooth, Bluetooth 1.0 / 1.1 / 1.2 / 2.0 / 2.1 / 3.0 / 4.0 / 4.0 / 4.1 / 4.2 / 5, BLE, mesh networking, IEEE 802.16 / 1 / 1a / 1b / 2 / 2a / b / b / c / d / e / f / g / h / i / j / k / l / m / n / o / p standards, etc.

[0191] The Type 1 device and / or Type 2 device is powered by a battery (e.g., AA battery, AAA battery, coin cell battery, button cell battery, small battery, battery bank, power bank, car battery, hybrid battery, vehicle battery, container battery, non-rechargeable battery, secondary battery, NiCd battery, NiMH battery, lithium ion battery, zinc carbon battery, zinc chloride battery, lead acid battery, alkaline battery, battery with wireless charger, smart battery, solar cell, boat battery, plain battery, other battery, temporary energy storage device, capacitor, flywheel).

[0192] Any device may be powered by DC or direct current (e.g., from a battery, generator, power converter, solar panel, rectifier, DC-DC converter, having various voltages such as 1.2V, 1.5V, 3V, 5V, 6V, 9V, 12V, 24V, 40V, 42V, 48V, 110V, 220V, 380V, etc., as described above) and therefore may have a DC connector or a connector with at least one pin for DC power.

[0193] Any device may be powered by AC or alternating current (e.g., a domestic wall outlet, transformer, inverter, reshower, having various voltages such as 100V, 110V, 120V, 100-127V, 200V, 220V, 230V, 240V, 220-240V, 100-240V, 250V, 380V, 50Hz, 60Hz, etc.) and therefore may have an AC connector or a connector with at least one pin for AC power. Type 1 devices and / or Type 2 devices may be located (e.g., installed, positioned, moved) within or outside the venue.

[0194] For example, in a vehicle (e.g., automobile, truck, lorry, bus, specialty vehicle, tractor, excavator, excavator, shovel, teleporter, bulldozer, crane, forklift, electric trolley, AGV, emergency vehicle, cargo, freight car, rail car, trailer, container, boat, ferry, ship, submarine, aircraft, aircraft, lift, monorail, train, rail car, rail vehicle, etc.), the Type 1 device and / or Type 2 device may be an embedded device embedded in the vehicle or an add-on device (e.g., an aftermarket device) plugged into a port of the vehicle (e.g., OBD port / socket, USB port / socket, accessory port / socket, 12V auxiliary power outlet, and / or 12V cigarette lighter port / socket).

[0195] For example, one device (e.g., a Type 2 device) may be plugged into a 12V cigarette lighter / accessory port or an OBD port or a USB port (e.g., of a car / truck / vehicle), and the other device (e.g., a Type 1 device) may be plugged into a 12V cigarette lighter / accessory port or an OBD port or a USB port. The OBD port and / or USB port may provide power, signal, and / or network (of the car / truck / vehicle). The two devices may jointly monitor passengers, including children / babies, in the vehicle. They may be used to count passengers, recognize the driver, and detect the presence of a passenger in a specific seat / position in the vehicle.

[0196] In another example, one device may be plugged into a 12V cigarette lighter / accessory port or OBD port or USB port on a car / truck / vehicle, and the other device is a 12V cigarette lighter / accessory port or OBD port or another.

[0197] In another example, many Type A (e.g., Type 1 or Type 2) devices may exist in many heterogeneous vehicles / portable devices / smart gadgets (e.g., automated guided vehicles / AGVs, shopping / luggage / mobile carts, parking tickets, golf carts, bicycles, smartphones, tablets, cameras, recording devices, smartwatches, roller skates, shoes, jackets, goggles, hats, eyewear, wearables, Segways, scooters, luggage tags, sweepers, vacuum cleaners, pet tags / collars / wearables / implants), each connected to the vehicle's 12V accessory port / OBD port / USB port or built into the vehicle. Another Type B (e.g., if Type A is Type 2, then Type B is Type 1; if Type A is Type 1, then Type B is Type 2) device may be installed at scattered locations to cover a large area, such as gas stations, streetlights, street corners, tunnels, parking garages, factories / stadiums / train stations / shopping malls / construction sites, etc. Type A devices can be located, tracked, and monitored based on the TSCI.

[0198] The area / venue may not have local connectivity, e.g., broadband service, WiFi, etc. Type 1 and / or Type 2 devices may be portable. Type 1 and / or Type 2 devices may support plug and play.

[0199] Pairwise wireless links may be established between many pairs of devices forming a tree structure. In each pair (and associated link), one device (the second device) may be a non-leaf (Type B). The other device (the first device) may be a leaf (Type A or Type B) or a non-leaf (Type B). In the link, the first device acts as a bot (Type 1 device or Tx device) to transmit a wireless signal (e.g., a probe signal) to the second device over a wireless multipath channel. The second device may act as an Origin (Type 2 device or Rx device) to receive the wireless signal, obtain a TSCI, and compute "linkwise analytics" based on the TSCI.

[0200] In some embodiments, the present teachings disclose systems and methods for wireless sensing. In one embodiment, a Type 1 heterogeneous wireless device or a Type 2 heterogeneous wireless device is one of many heterogeneous wireless devices or stations (STAs) in space.

[0201] Roles in wireless sensing: A Type 1 device, a Type 2 device, or another STA functions as a sensing initiator. A sensing initiator is an STA that initiates a wireless sensing procedure (or a sensing procedure using WiFi, WLAN, 5G, UWB, mmWave, WiMax, WiGig, Bluetooth, or another wireless system). At least one STA (e.g., a Type 1 device, a Type 2 device, a sensing initiator, a sensing transmitter, a sensing receiver, or another STA) can function as a sensing responder. A sensing responder may be an STA that participates in a sensing procedure initiated by a sensing initiator. At least one STA (e.g., a Type 1 device, a Type 2 device, a sensing initiator, a sensing responder, a sensing receiver, or another STA) can function as a sensing transmitter. The sensing transmitter may be a STA that transmits a wireless signal used for sensing measurements in a wireless sensing procedure (e.g., a physical layer protocol data unit (PPDU), a data packet frame (NDP), an NDP announcement (NDPA) frame in WiFi, or some sounding signal). At least one STA (e.g., a Type 1 device, a Type 2 device, a sensing initiator, a sensing responder, a sensing transmitter, or another STA) can function as a sensing receiver. The sensing receiver may be a STA that receives the wireless signal transmitted by the sensing transmitter (e.g., a PPDU, an NDPA, an NDP, or some sounding signal in WiFi) and performs sensing measurements in a WLAN sensing procedure.

[0202] A STA can assume one or more possible roles (e.g., sensing initiator, sensing receiver, sensing transceiver, sensing receiver, sensing contributor, SBP requesting STA) in one (or more) sensing procedures. In a sensing procedure, a sensing initiator can be a sensing transmitter, a sensing receiver, both, or neither. In a sensing procedure, a sensing responder can be a sensing transmitter, a sensing receiver, or both.

[0203] Sensing Procedure: A sensing procedure enables a STA to perform sensing and obtain measurement results. A sensing procedure may consist of one or more of sensing session setup, sensing measurement setup, sensing measurement instance, sensing measurement setup termination, and sensing session termination. A sensing procedure may consist of one or more sensing measurement instances.

[0204] Sensing Session: A sensing session may be an agreement between a sensing initiator and a sensing responder to participate in a sensing procedure. A sensing procedure may consist of zero or at least one sensing measurement instance. Some examples of sensing procedures are shown in Figures 1 and 2.

[0205] The Measurement Setup ID can be used to identify the attributes of a sensing measurement instance. The Measurement Instance ID can be used to identify sensing measurement instances that use the attributes of the same Measurement Setup ID. The Dialog Token field may be used to contain both the Measurement Setup ID and the Measurement Instance ID. At least one type of sensing measurement result can be defined. The sensing transmitter and sensing receiver roles of the STA corresponding to the Measurement Setup ID may be fixed, unchanged, changed, modified, or adjusted as determined during the sensing measurement setup until the sensing measurement setup is terminated.

[0206] During the sensing session setup of the sensing procedure, a sensing session may be established and operating parameters related to the sensing session may be determined and exchanged between STAs. The sensing session may be pair-wise and may be identified by a MAC address, associated AID / UID, session ID, or another ID. A sensing initiator may maintain multiple sensing sessions. A STA may be the sensing initiator in one session and the sensing responder in another session.

[0207] An optional negotiation process in the sensing measurement setup may be defined to allow the sensing initiator and sensing responder to exchange and agree on operational attributes related to the sensing measurement instance, which may include the initiator and responder roles, the measurement report type (for non-local reporting, local reporting, or both), and other operational parameters.

[0208] In a sensing measurement instance of a sensing procedure, a sensing measurement may be performed to obtain a sensing measurement result. Multiple sensing responders may participate in a sensing measurement instance. There are at least two types of sensing measurement instances: (a) trigger-based (TB) sensing measurement instances and (b) non-TB sensing measurement instances.

[0209] TB Sensing Measurement: A TB sensing measurement instance may consist of a polling phase, an NDPA sounding phase, a trigger frame (TF) sounding phase, a reporting phase, and / or an LTF security update phase. The ordering between the sounding phases may be such that an NDPA sounding precedes a TF sounding or vice versa. The order may change over time.

[0210] Some examples of possible TB sensing measurement instances are shown in Figure 3. As shown in Figure 3, two sounding orders are shown in Examples 3 and 4. The reporting phase in Example 5 may be separated in time from the sounding phase. This may be delayed reporting. The polling of the reporting phase in Example 5 may be directed to responders other than the responder involved in the sounding.

[0211] Polling Phase: In the polling phase, an AP (WiFi access point, 3G / 4G / 5G / 6G base station, hub, etc.) may send a trigger frame to check the availability of a STA. If the STA is available, the STA may respond with a CTS-to-self.

[0212] NDPA Sounding: The NDPA sounding phase may be present in a TB sensing measurement instance if at least one STA that is a sensing receiver responds in the polling phase. The NDPA sounding phase may consist of (a) the transmission of a sensing NDP Announcement (NDPA) frame by the AP, and (b) the transmission of an NDP by the AP after the transmission of the sensing NDPA frame. The NDP may be used for channel measurements (e.g., CI, CSI, CIR, CFR, etc.) between the sensing transceiver and the sensing receiver (e.g., sub-7 GHz band).

[0213] TF Sounding: If at least one STA that is a sensing transmitter responds in the polling phase, a trigger frame (TF) sounding phase may be present in the TB sensing measurement instance. The TF sounding phase may consist of (a) the AP transmitting a trigger frame (TF) to solicit an NDP transmission from the STA, and (b) the STA transmitting an NDP after receiving the trigger frame. The NDP is used for channel measurements (e.g., CI, CSI, CIR, CFR, etc.) between the sensing transmitter and the sensing receiver (e.g., in the sub-7 GHz band).

[0214] Local / Non-Local Reporting: In the reporting phase of a sensing measurement instance, the sensing measurement results may be reported. Measurement results performed in a sensing procedure may be reported and / or obtained locally, non-locally, both (i.e., both locally and non-locally), or none (i.e., not reported, e.g., if the variation in CI is below a threshold that suggests the CI may be essentially the same as the previous CI).

[0215] When reported locally, the sensing measurements may be reported locally to the sensing receiver or at the location where the sensing measurements may be measured. Such local reporting may be achieved through some software interface, such as a Medium Access Control (MAC) Sublayer Management Entity (MLME) primitive or a firmware application program interface (or API). Some application or higher-level software may use the software interface (e.g., using a software interrupt) to obtain or read the sensing measurements.

[0216] If reported non-locally, the measurement results may be reported non-locally to other devices or STAs (e.g., at least one of a sensing initiator, a sensing responder, a sensing transmitter, a sensing receiver, a Type 1 device, a Type 2 device, a neighboring STA, another STA, or some local or cloud server).

[0217] Measurements may be reported both locally and non-locally (e.g., simultaneously, concurrently, alternating, selectively, adaptively, and / or in an on-demand / scheduled / planned manner). Within a measurement "span" (time period), measurement reports may consist of a combination of local and non-local reports (e.g., simultaneous local / non-local reporting, alternating local / non-local / both / none reporting, local / non-local / both / none reporting selected by a specific mechanism, adaptively determined local / non-local / both / none reporting, on-demand local / non-local / both / none reporting, scheduled local / non-local / both / none reporting, planned (e.g., threshold-based) local / non-local / both / none reporting in response to some situation / condition / event).

[0218] The settings (e.g., a combination of local and non-local reporting, any setup parameters, any session setup parameters, or one of the measurement setup parameters) may be applied to a "measurement span." A measurement span may include multiple sensing initiators, or sensing initiator identities, or sensing initiator IDs, or multiple sessions associated with one (or more) sensing initiators, or sessions, or session identities, or session IDs, or multiple measurement setups within a session, or measurement setups, or measurement setup IDs, or measurement setup IDs, or multiple measurement instances associated with a measurement setup (or measurement setup ID), or measurement instances associated with a measurement instance number.

[0219] In simultaneous reporting, both local and non-local reporting may be performed simultaneously or concurrently. In alternating reporting, measurement instances are partitioned into groups of consecutive sensing results, with the first group reported in a first manner, the second group reported in a second manner, the third group reported in a third manner, and so on, where each of the first, second, third, fourth, fifth, etc. methods can be either (a) only local, (b) only non-local, (c) both local and non-local, or (d) none (not reported).

[0220] The type / accuracy / processing / other specifications of measurement results reported non-locally in a sensing procedure / session / measurement instance may be determined (non-locally) by the sensing initiator. The type / accuracy / processing / other specifications of measurement results reported locally in a sensing procedure may be determined (locally) via a software interface (e.g., MLME primitives) at the sensing receiver or at the location where the results are measured. Local / non-local reporting can be enabled / disabled (non-locally) by the sensing initiator or by negotiation between the sensing initiator and the sensing responder. Switching between local and non-local reporting may be controlled entirely by the sensing initiator, or partly by the sensing initiator and partly via a software interface at the sensing responder.

[0221] Sensing Measurement Report Frame: A Sensing Measurement Report frame may be defined that allows a sensing receiver to report sensing measurements non-locally. This frame may include at least two fields: (a) a Measurement Report Control field that contains information necessary to interpret the Measurement Report field, and (b) a Measurement Report field that carries the sensing measurement results obtained by the sensing receiver (e.g., channel information, CI, CSI, CIR, CFR, RSSI, or some variant).

[0222] Each of the local and non-local reports may be initiated by the respective MLME. The transmission of a Sensing Measurement Report frame may be initiated by an MLME primitive. Both immediate and delayed reporting may be performed.

[0223] At sensing session end, the STA stops performing measurements and ends the sensing session.

[0224] Threshold-Based Reporting: An optional threshold-based measurement and reporting procedure may be performed. The difference between the currently measured CI (e.g., CSI) and the previously measured CI (e.g., CSI) may be quantified. This difference may be referred to as the CI variation. A threshold may be defined (e.g., by the sensing initiator, sensing responder, sensing transmitter, sensing receiver, another STA, and / or some server) for use by the sensing receiver in the threshold-based procedure. By comparing the CI variation to a threshold, the sensing receiver may report measurements (e.g., original or transformed, uncompressed or compressed measurements) if the CI variation is likely to be large (e.g., greater than a certain threshold or falling into the "large" category).

[0225] CI Variability Options: CI variability may consist of multiple quantities / measurements / options (e.g., two CI variability measures may be selected from seven options). As an example, CI variability options may include any of the following: difference (current CI minus previous CI), moving average difference (moving average of current CI minus moving average of previous CI), magnitude difference (or L1-norm, i.e., magnitude of current CI minus magnitude of previous CI), power difference (power of current CI minus power of previous CI), difference between current value and moving average (current CI minus moving average of CI), high-pass or band-pass filter output, dot product (dot product of current CI and previous CI, both vectors), dot product of moving averages, dot product of magnitude, dot product of power, autocorrelation function (of CI), autocorrelation function of CI magnitude, autocorrelation of power of CI, autocorrelation of a function of CI, autocovariance, etc.

[0226] Selection: The same, similar or different threshold-based measurement and reporting procedures may be applied to local and non-local reporting, and (a) the amount of CI variation measures used for local and non-local reporting may be the same or different, (b) the selection of CI variation measures used for local and non-local reporting may be the same or different, and / or (c) the thresholds used for local and non-local reporting may be the same and / or different.

[0227] For non-local reporting, the enablement / disablement of threshold-based reporting, the amount and choice of CI change, and the corresponding threshold can be determined by the sensing initiator, or by at least one of the sensing responder, sensing transmitter, Type 1 device, another STA, and / or server, or locally by the sensing receiver or Type 2 device. Some precision reduction measures (quantization, approximation, etc.) may be applied to the measurement results before they are reported non-locally.

[0228] For local reporting, the enablement / disablement of threshold-based reporting, the amount and selection of CI variation, and the corresponding thresholds may be determined locally by the sensing receiver or Type 2 device. They may also be determined non-locally by at least one of the sensing initiator, sensing responder, sensing transmitter, Type 1 device, another STA, and / or some server. For local reporting, precision reduction measures applied to measurement results prior to non-local reporting may or may not be applied (i.e., may or may not be skipped). For local reporting, measurement results may be reported with the highest precision supported by the sensing receiver's hardware.

[0229] Buffering timeout: During a sensing session, the measurement results associated with a measurement instance and the corresponding measurement setup ID may be buffered and remain available for local / non-local reporting by the sensing receiver (or Type 2 device) for a period comparable to (e.g., a percentage of) the sounding period associated with the measurement setup ID. The sounding period associated with the measurement setup ID is the target time between two consecutive measurement instances negotiated in the sensing measurement setup.

[0230] The measurement result CSI:CI (e.g., CSI, CIR, CFR, RSSI, or the channel measured during the training symbol of the received PPDU) may be a type of sensing measurement result (e.g., in the case of sub-7 GHz WiFi / WLAN). To enable sensing, a parameter (e.g., RXVECTOR parameter CI_ESTIMATE) may be defined that includes the channel measured during the training symbol of the received wireless signal (e.g., PPDU of WiFi / WLAN). The format of the parameter (e.g., CI_ESTIMATE) may be the same as that used in the measurement report field in the Sensing Measurement Report frame.

[0231] Centralized Computing: Some sensing networks comprised of STAs form a centralized sensing system in which most of the high-level sensing computation tasks based on sensing measurement results (or "consumption" of sensing results, e.g., motion detection, respiration detection / monitoring, fall detection, etc.) are performed centrally by a centralized device (which may be STAs and sensing initiators, or devices requesting STAs to act as sensing initiators). On the other hand, the majority of STAs (e.g., sensing responders, sensing transmitters, sensing receivers, Type 1 devices, Type 2 devices) do not participate in high-level sensing tasks. When sensing measurement results are generated at the centralized device, local-only reporting may be used at the centralized device, and centralized computation of high-level sensing computation tasks may be performed; the sensing measurement results do not need to be transmitted from most STAs to the centralized device (which requires significant network resources, airtime, bandwidth, hardware / software resources, and involves significant time delays). Non-local-only reporting is used when sensing measurements are generated by a majority of STAs and the majority of STAs transmit all measurement results to a centralized device, which performs centralized computing of high-level sensing computation tasks. However, such non-local-only reporting can use a significant amount of network resources, airtime, bandwidth, hardware / software resources, and introduce significant time delays.

[0232] Distributed Computing: Some sensing networks form a distributed sensing system, in which the majority of high-level sensing computational tasks based on sensing measurement results are distributed or shared among most STAs, and each high-level task result is sent to a centralized device (e.g., an STA and a sensing initiator, or a device requesting an STA to act as a sensing initiator) for fusion and / or further processing. If the sensing measurement results are generated at most of the STAs, local-only reporting may be performed and distributed computing of the high-level sensing tasks may be performed. If the sensing measurement results are generated at a centralized device, the centralized device may need to send each result to each STA for distributed computing.

[0233] Example: As an example, there may be a base device (e.g., a WiFi access point / AP, or a 3G / 4G / 5G / 6G / 7G / 8G base station or hub) that acts as a sensing initiator, and there may be a number of client devices (e.g., WiFi IoT devices, mobile phones, or 3G / 4G / 5G / 6G / 7G / 8G client devices).

[0234] Case 1: The base device uses trigger-based (TB) sensing measurement by sending a trigger frame (TF) to request NDP from the client device, and the measurement results are generated on the base device. In this method, only local reporting is performed on the base device, and central computing of high-level tasks is performed on the base device.

[0235] Case 2: The base device can use non-TB sensing measurements by sending NDPA and NDP to the client device so that the measurement results are generated on the client device. In this way, local-only reporting is performed on the client device, and distributed computing of higher-level tasks is performed on the client device. The client can send the results of the higher-level tasks to the base device for fusion and further processing.

[0236] Example (Proxy): In another example, an initiating device (e.g., an STA as a real sensing initiator) can request a base device to act as a sensing initiator (proxy sensing initiator) to establish a sensing network with an IoT device. In Case 1, the base device sends all measurement results to the initiating device, and the initiating device can perform centralized computation of high-level tasks. In Case 2, the client device sends the results of high-level tasks to the base device, and the base device sends them to the initiating device for fusion and further processing (at the initiating device).

[0237] Sharing of Measurement Instances: In one embodiment, a measurement instance may be associated with one measurement setup. In another embodiment, sharing of measurement instances within a session may be disclosed. A measurement instance may be shared by multiple measurement setups within a sensing session (by being associated with multiple measurement setup IDs, the same initiator-responder pair), and measurements are performed using a "shared" or "combined" measurement setup, which may be a superset encompassing the multiple measurement setups (e.g., if one setup is 300 Hz with two antennas and another is 200 Hz with three antennas, the combined setup may be 300 Hz with three antennas). The combined sounding frequency may be greater than or equal to the sounding frequencies of the multiple measurement setups, but may be less than or equal to their least common multiple (LCM) (e.g., the LCM of 200 and 300 is 600). For example, the composite sounding frequency may be the maximum value of the sounding frequencies (e.g., the maximum of 200 and 300 is 300). Alternatively, it may be the LCM. Such sharing of measurement instances may be useful when a large number of sampling times of the multiple measurement setups coincide or are very close to each other. The amount of antenna coupling may be the maximum number of antennas of the multiple measurement setups.

[0238] As an example, sharing measurement instances is useful for two measurement setups that differ only in sounding frequency, where one sounding frequency is a factor of the other (e.g., 100 Hz vs. 200 Hz, all other settings are the same). By sharing measurement instances, all slower (lower sounding frequency) measurement instances are absorbed into the faster measurement instances. By sharing measurement instances, 100 measurement instances can be saved (now 200 instances per second, compared to 300 instances per second previously). This reduces a large amount of network resources (airtime, bandwidth, hardware / software usage).

[0239] As another example, sharing measurement instances is useful when two measurement setups differ only in sounding frequency, and the two sounding frequencies have a sufficiently large GCF (greatest common factor), e.g., 200 Hz vs. 300 Hz, with GCF = 100, while all other settings are identical. Sharing measurement instances can save 10 measurement instances (previously a total of 500 measurement instances per second, now 400 per second). In general, when GCF = N, N measurement instances can be saved per second. Two measurement instances can be merged or shared if their GCF is greater than a threshold.

[0240] In another embodiment, sharing of measurement instances across multiple sessions may be disclosed. There may be multiple sessions, each associated with a unique session ID. A measurement instance may be shared by multiple measurement setups of multiple sensing sessions (multiple sessions correspond to multiple initiator-responder pairs by being associated with multiple measurement setup IDs and multiple session IDs), and measurements are performed using a "shared" or "combined" measurement setup, which may be a superset that encompasses the multiple measurement setups. Such sharing of measurement instances is useful to eliminate or avoid "redundant" measurement instances when different initiator-responder pairs select similar or the same measurement setup parameter sets.

[0241] As an example, a smart TV can establish a first sensing session with an AP, with the AP as the sensing initiator. A smart thermostat can establish a second sensing session with the AP, with the AP as the sensing initiator. Both sensing sessions may have identical or very similar measurement setup parameter sets (e.g., "same" means both are 100 Hz, while "similar" means 100 Hz vs. 200 Hz, with all other settings being identical). For example, a smart professor may have published a paper that shares a very good measurement setup parameter set (e.g., 100 Hz). In the "same" case, both the TV and the thermostat may be designed based on the published results, resulting in identical settings (e.g., both are 100 Hz). In the "similar" case, one device may have adjusted its sounding frequency from 100 Hz to 200 Hz to achieve the desired performance, resulting in "similar" settings (100 Hz vs. 200 Hz). As explained earlier, by allowing the sharing of measurement instances across multiple sessions, savings of 100 instances per second can be achieved.

[0242] In general, two measurement instances (within the same session or across multiple sessions) associated with two different measurement setups may be "merged" or "shared" if the difference between their sampling times may be less than a threshold.

[0243] In some embodiments, applications can benefit from “local” reporting / consumption of sensing measurements (e.g., CSI) at the sensing receiver instead of “non-local” reporting (sent to the sensing initiator using a sensing measurement report frame) / consumption (by the sensing initiator). For example, the sensing initiator and sensing receiver may be designed / operated by the same company to jointly perform sensing tasks. The sensing initiator is designed to set up a WLAN sensing network, and the sensing receiver is designed to locally perform most of the sensing calculations (e.g., motion / breath detection) based on the locally reported sensing measurements. The locally calculated sensing results (which are much simpler than the raw sensing measurements) may be sent to the sensing initiator for fusion / further processing.

[0244] This significantly reduces the heavy network resources (signaling, bandwidth, airtime, delay) required for non-local reporting due to the large scale of sensing measurements (e.g., CSI). Local consumption distributes the sensing computation across many sensing receivers, resulting in relatively low computation / memory requirements for each. In contrast, non-local consumption centralizes all sensing computation at the sensing initiator, resulting in high computation / memory requirements. Thus, according to some embodiments of the present teachings, sensing measurements are reported locally at the sensing receivers via MLME primitives.

[0245] In some embodiments, the threshold-based procedure is extended from non-local reporting to local reporting of sensing measurements. For local reporting, an option "threshold-based local reporting" may be defined. In some embodiments, the option "threshold-based local reporting" (and associated threshold) may be selected / deselected by an MLME primitive. If the sensing measurement can be reported locally at the sensing receiver, "threshold-based local reporting" may be applied to the local reporting at the sensing receiver. Threshold-based local reporting means that the sensing measurement is reported locally if the "variance of the sensing measurement" is greater than a threshold.

[0246] In various embodiments, "threshold-based local reporting" can be applied in a voluntary or mandatory manner at the sensing receiver. In some embodiments, the threshold used in "threshold-based local reporting" can be set via the MLME in the sensing receiver. In some embodiments, at least one "sensing measurement variance" (SMV) is available for "threshold-based local reporting." In some embodiments, one of the at least one SMV is selected via the MLME in the sensing receiver.

[0247] In some embodiments, the wireless device may reduce the accuracy of the sensing measurements by performing some quantization on the sensing measurements (e.g., CSI) before transmitting them in the sensing measurement report frame. This helps reduce computational complexity, hardware costs, and achieve increased / sustained throughput. However, for local consumption by the sensing receiver (or local reporting of the sensing measurements), the sensing measurements can / should be reported with as high accuracy as possible.

[0248] In some embodiments, for purposes of non-local reporting at the sensing receiver, precision reduction measures applied to the sensing measurements can be skipped. In some embodiments, the sensing measurements may be reported locally at the sensing receiver via the MLME with the highest precision supported by the sensing receiver's hardware.

[0249] In some embodiments, sensing measurements may require a significant amount of memory to store / buffer in the sensing receiver. Due to limited memory allocated in the sensing receiver hardware, it may be expensive, if not impossible, to buffer new sensing measurements if old sensing measurements have not been "cleared" - either to be sent for non-local reporting or to be read for local reporting.

[0250] In some embodiments, older sensing measurements may be overwritten by newer ones. Therefore, sensing measurements associated with a measurement instance with a measurement setup ID should be buffered and available for local / non-local reporting for a period comparable to the sounding period associated with the measurement setup ID (e.g., a percentage of the sounding period, such as 50%). This allows higher-level applications to know when they must obtain sensing measurements using MLME primitives.

[0251] The sounding period associated with a measurement setup ID is the target duration between two consecutive measurement instances negotiated in the corresponding sensing measurement setup. In some embodiments, a statement is added to the SPF that sounding measurements associated with a measurement instance with a measurement setup ID should be buffered and available for local / non-local reporting for a time duration comparable to the sounding period associated with the measurement setup ID.

[0252] In various embodiments, there are different ways of reporting sensing measurements. First, sensing measurements can be reported only non-locally, without local reporting, which is suitable for centralized sensing systems. Second, sensing measurements can be reported only locally, without non-local reporting, which is suitable for fully distributed sensing systems. Third, sensing measurements can be reported both locally and non-locally, which is suitable for hybrid sensing systems. Fourth, sensing measurements can be either not reported or reporting can be paused / stopped. For example, a sensing measurement / session can be paused for privacy purposes. Pausing can be achieved by terminating the measurement setup and resuming it later by starting a new measurement setup.

[0253] According to the first method, only non-local reporting of sensing measurement results using sensing measurement report frames is performed, and no local reporting is performed. In this method, all sensing measurements are transmitted elsewhere for non-local consumption. This is useful in a centralized sensing system where the sensing responder does not participate in the consumption of sensing measurements. That is, the sensing responder does not perform high-level WLAN sensing computations (such as motion detection / monitoring, breathing, and falls). This increases network traffic, airtime, and resources spent on transmitting raw sensing measurements (e.g., CSI) and causes significant time delays (for the sensing initiator to collect all sensing measurements). Furthermore, this requires centralized computation, resulting in high computational and storage requirements for the sensing initiator. This method is suitable for "cooperative" sensing receivers that cooperate only in generating and transmitting sensing measurements.

[0254] According to the second method, only local reporting of sensing measurement results is performed, and no non-local reporting is performed. In this method, all sensing measurement results are consumed locally at the upper layer of the sensing responder and are not sent to the sensing initiator. This is useful in distributed cases where each sensing receiver performs high-level WLAN sensing computations related to the (local) sensing measurements (such as motion detection / monitoring, respiration, and falls). The sensing initiator is responsible for setting up the sensing responders to form the WLAN sensing network. The sensing initiator can function as either a sensing transmitter or a sensing receiver. In some embodiments, the sensing receiver can share the computed sensing results (which require little network bandwidth, airtime, or resources) with the sensing initiator for fusion / further processing. This only induces local computing and has lower computing / storage requirements than the first method. No network resources are used to transmit the demanding raw sensing measurements, making it suitable for a "partner" sensing receiver to help perform some of the high-level computing.

[0255] According to the third method, both local and non-local reporting is performed, and sensing measurement results are consumed both locally and non-locally. This is useful in hybrid cases where both the sensing responder and the sensing initiator participate in consuming sensing measurements. That is, the sensing responder shares some high-level WLAN sensing computations with the sensing initiator. Like the first method, the third method incurs significant network traffic, airtime, or resources spent transmitting raw sensing measurements (e.g., CSI). Because the third method performs both centralized and distributed computing, the sensing initiator has similar computational / memory requirements as the first method, and the sensing receiver has similar requirements as the second method.

[0256] The hybrid case means centralized and distributed computing. As an example, consider an AP as the sensing initiator and many IoT devices as sensing responders (or the AP is required to be a proxy).

[0257] An exemplary "recipe" for centralized computing is as follows: AP uses TF to make TB sensing measurements, requests NDP from IoT devices, and has measurement results generated at the AP. Local-only reporting is sufficient for centralized computing; measurements are never transmitted over the air.

[0258] An example "recipe" for distributed computing is as follows: APs can use non-TB sensing measurements by sending NDPA+NDP to IoT devices so that the measurements are generated at the IoT device. Distributed computing at the IoT device requires only local reporting; measurements are never sent over the air.

[0259] In some embodiments, the selection between local and non-local reporting remains the same for measurement instances with the same measurement setup ID. Local or non-local reporting can be selected at different levels or granularity, including at the session setup level (e.g., local / non-local reporting selection applied to all measurement setups in a session), at the measurement setup level (e.g., local / non-local reporting selection applied to one measurement setup), or both (e.g., one bit at the session level indicating the session level or the measurement setup level, then selection at the corresponding level).

[0260] In some embodiments, one measurement instance is associated with one measurement setup. However, it may be useful to associate one measurement instance with multiple measurement setups within a sensing session for measurements performed using a "shared" measurement setup. In a first example, the multiple shared measurement setups may be two measurement setups in which a large number of measurement instances match each other. In a second example, the two or more shared measurement setups may be two measurement setups that differ only in sounding frequency, where F1 is a factor of F2 (e.g., 10 Hz vs. 20 Hz, all other settings are identical, and 30 instances / second becomes 20 instances / second). In a third example, the multiple shared measurement setups are two measurement setups that differ only in sounding frequency and have a large greatest common factor (GCF) (e.g., 20 Hz vs. 30 Hz, all other settings are identical, GCF = 10, 20 + 30 = 50 instances / second becomes 40 instances / second. If GCF = N, the instance savings is N). In a fourth example, the multiple shared measurement setups may be two measurement setups with different sounding frequencies and antenna counts (e.g., 10 Hz / 3 antennas vs. 20 Hz / 2 antennas, where "shared" measurement setup = 3 antennas). Sharing sensing measurements can reduce the total amount of measurement instances, meaning less airtime / bandwidth / network resources for sensing, less buffering memory, lower power, longer battery life, etc.

[0261] In some embodiments, it may be useful to share measurement instances of different sensing sessions (e.g., different initiator-responder pairs) where measurements are performed using a "shared" measurement setup. When the initiator is an AP and the responder is an IoT device, some "common" and "good" configurations are likely to be used by many IoTs, causing their measurement setup parameters to be very similar. In one example, a shared measurement setup in TB-based sensing is two measurement setups that differ only in sounding frequency, one being a factor of the other (e.g., a smart TV wants 10 Hz, but a smart speaker wants 20 Hz, and all other settings are identical). In another example, a shared measurement setup in TB-based sensing is two measurement setups that differ in sounding frequency and number of antennas (e.g., a smart TV wants 10 Hz with three antennas, but a smart speaker wants 20 Hz with two antennas, and the "shared" measurement setup is three antennas). Sharing sensing measurements reduces the total amount of measurement instances, which means reduced airtime / bandwidth / network resources for sensing, reduced buffering memory, lower power consumption, and longer battery life.

[0262] In some embodiments, the sounding transmitter may associate a measurement instance with up to N measurement setup IDs, where N is an integer. Among the N measurement setup IDs, local / non-local reporting is performed in a predefined (e.g., increasing) order of the measurement setup IDs.

[0263] In some embodiments, "measurement instance sharing" is permitted in a sensing session. In some embodiments, "measurement instance sharing" allows for associating an instantaneous (individual) measurement instance with N sensing measurement setup IDs and performing the associated sensing measurements using an instantaneous "common" setup that allows the sensing measurements to meet all requirements / specifications of the N sensing measurement setup IDs, where N is an integer greater than or equal to 1.

[0264] In some embodiments, "measurement instance sharing" is an option in a sensing session, and "measurement instance sharing" allows for associating an instantaneous (individual) measurement instance with N sensing measurement setup IDs and performing the associated sensing measurements using an instantaneous "common" setup that allows the sensing measurements to meet all requirements / specifications of the N sensing measurement setup IDs, where N is an integer greater than or equal to 1.

[0265] In some embodiments, access to CSI is controlled for privacy protection. In WLAN sensing, there are different functional roles: A sensing initiator initiates the sensing procedure and has access to the CSI. A sensing responder participates in the session procedure and, if it is a receiver, has access to the CSI. A sensing transmitter transmits sensing PPDUs. A sensing receiver performs sensing measurements, reports the sensing measurements, and has access to the CSI. There may also be an SBP requester STA that requests an SBP procedure and has access to the CSI.

[0266] In some embodiments, the sensing system can maintain classifications of STAs to manage CSI access. In one example, the system can allow the most trusted class of STAs to perform all roles (with full CSI access), including 1, 2, 3, 4, and 5 (e.g., user's IoT devices from trusted sources). In another example, the system can allow a class of STAs to perform several roles (with limited CSI access), such as {1, 2, 3, 4}, {2, 3, 4}, or {4} (e.g., user's IoT devices from less trusted sources, neighboring devices). In another example, the system can allow a class of STAs to perform several roles (without CSI access), such as responder (not receiver), or {3} (e.g., for unknown devices). In another example, the system can allow a class of STAs to perform no roles (without CSI access) (e.g., hostile device, compromised device).

[0267] In some embodiments, optional proxy-based sensing (SBP) procedures may be defined as follows: First, an "SBP request" involves a non-AP STA sending an SBP Request frame to an SBP-capable AP STA. The STA sending the SBP Request frame to invoke SBP (and consequently WLAN sensing) is referred to as the "SBP requesting STA." The format and content of the SBP Request frame are determined. Second, an AP STA that receives the SBP Request can accept or reject the request by sending an SBP Response frame to the SBP requesting STA. The format and content of the SBP Response frame are determined. Next, an AP STA that accepts the SBP request can initiate WLAN sensing procedures with one or more non-AP STAs using operating parameters derived from the operating parameters indicated in the SBP Request. Measurement results obtained in the WLAN sensing procedures resulting from the SBP request may be reported to the SBP requesting STA.

[0268] In some embodiments, the proxy-based sensing with local reporting (SBP-LR) procedure may be defined as follows: An "SBP-LR request" involves a non-AP STA sending an SBP-LR Request frame to an SBP-LR-capable AP STA. The STA sending the SBP-LR Request frame to invoke SBP-LR (and consequently WLAN sensing) is referred to as the "SBP-LR-requesting STA." The format and content of the SBP Request frame are determined. An AP STA that receives an SBP-LR Request can accept or reject the request by sending an SBP-LR Response frame to the SBP-LR-requesting STA. If accepted, the AP can promise to perform SBP-LR for a certain period of time. When the period expires, the ABP-LR may stop. However, the STA (or another STA) requesting SBP-LR can send another "continuation request" with the SBP-LR setup ID. The format and content of the SBP-LR Response frame are determined. An AP STA that accepts the SBP-LR request may initiate a WLAN sensing procedure with one or more non-AP STAs using operating parameters derived from those indicated in the SBP-LR Request frame. Measurement results may be reported locally only (i.e., locally to the sensing receiver), remotely only (to the AP STA that forwards them to the SBP-LR / SBP requesting STA), or both locally and remotely.

[0269] In some embodiments, an SBP-LR setup ID may be associated with an SBP-LR setup and / or operational parameters. Each measurement instance may be associated with one or more SBP-LR setup IDs. AP STAs may store / buffer / process / forward / redirect / reroute / distribute / utilize / execute / deliver sensing measurement results received from sensing receivers.

[0270] In some embodiments, an AP STA may perform non-TB sensing measurements with non-AP STAs using an NDP transmitted to the non-AP STAs, such that the sensing measurements are performed at each of the non-AP STAs and the measurement results are reported locally at the non-AP STAs. An AP STA may perform non-TB sensing measurements with non-AP STAs using an NDP transmitted from the non-AP STAs, such that the sensing measurements are performed at the AP STAs and the measurement results are reported locally at the AP STAs. An AP STA may perform non-TB sensing measurements with non-AP STAs by transmitting some NDPs to the non-AP STAs and some NDPs from the non-AP STAs. In this manner, the sensing measurement results may not be transmitted wirelessly from the sensing receiver to the AP STAs. In some embodiments, an AP STA may perform TB sensing measurements with non-AP STAs by transmitting the sensing measurements at the AP STAs and the measurement results are reported locally at the AP STAs.

[0271] In the local reporting of the sensing receiver, unsolicited / unconsumed measurement results may be retained until a timeout period. Beyond the timeout period, the measurement results may persist (e.g., persist until overwritten, persist until the timeout period), discard, overwritten, or retained. One or more high-level application processes in the non-AP STA can use an MLME primitive to request the non-AP STA to participate in SBP-LR on the corresponding sounding frequency. The sensing measurement results may be retrieved via the MLME primitive within the timeout period. An AP STA may perform wireless (e.g., WLAN, 4G / 5G / 6G / 7G / 8G, Bluetooth, WiMax, Wi-Fi, etc.) sensing procedures for multiple SBP-LR requests / SBP requests and / or multiple SBP-LR requesting STAs / SBP requesting STAs. An AP STA can perform a WLAN sensing procedure as a service for multiple SBP-LR requesting STAs / SBP requesting STAs. As long as there is one SBP-LR / SBP request, an AT STA may start performing a WLAN sensing procedure. Once all SBP-LR / SBP requests have been fulfilled and completed, and there are no further requests, the service may be suspended.

[0272] When there are two or more SBP-LR / SBP requests with different sensing parameters (e.g., one with 20 Hz sounding and one with 10 Hz, or one with 20 Hz and one with 30 Hz), the AP STA may perform a wireless sensing procedure with a "superset" of sensing parameters so that all SBP-LR / SBP requests are satisfied simultaneously. Alternatively, the AP STA may perform multiple wireless sensing procedures so that each SBP-LR / SBP request is satisfied by multiple wireless sensing procedures. For example, the AP STA may perform multiple wireless sensing procedures, e.g., A, B, and C, each with its own sensing parameters. The first SBP-LR / SBP request may be satisfied by A (or part of A). The second request may be satisfied by combining A and B. The third request may be satisfied by A and C. The fourth request may be satisfied by A, B, and C, etc.

[0273] In some embodiments, the SBP-LR / SBP-requesting STAs may be selected or authorized STAs to send SBP-LR / SBP requests, and the AP STA may reject / reject SBP-PR / SBP requests from non-selected / non-authorized STAs.

[0274] In some embodiments, an AP STA can provide privacy protection / access control for a wireless sensing system formed by AP STAs and non-AP STAs. The AP STA may belong to a user and be installed in the user's home / office / facility. The user can designate / designate / select some user devices (e.g., the user's device, some authorized user's devices, the user's trusted devices, the user's recognized devices, the user's authorized devices) as "authorized" or "selected" STAs that send SBP-LR / SBP requests to enable sensing, using some authentication protocol, some pairing procedure, some identification procedure, some password, etc. The user can also designate / designate / select some WiFi devices "visible" to the AP STA (e.g., neighboring WiFi devices, public devices, commercial devices, unknown devices, devices not trusted by the user, or devices owned by unauthorized users such as tenants, residents, or visitors in the user's home / office / facility) as "unauthorized," "unselected," or "denied" devices.

[0275] In some embodiments, in a mesh network where multiple AP STAs cooperate to form a mesh network, some or all of the AP STAs may perform SBP or SBP-LR. Each AP STA may perform wireless sensing independently with its own set of "client" STAs. A client STA may perform wireless sensing with one or more AP STAs. Alternatively, some or all of the AP STAs may perform wireless sensing jointly or cooperatively. The sounding of two AP STAs may be synchronous, nearly synchronous, simultaneous, out-of-phase with a fixed phase difference, or not. Assume there are three APs: AP1, AP2, and AP3. Each of the three APs may perform one or more wireless sensing procedures (e.g., AP1 performs A, B, and C, and AP2 performs D, E, and F) with respective sensing parameters. D and A may be related. D and A may have the same sensing parameters. Similarly, E and B may be related, similar, or identical. F and C may be related, similar, or identical. AP1 and AP2 may perform A and D simultaneously, simultaneously, synchronously (with or without a phase delay), or asynchronously. AP1 and AP2 may perform A and B alternately (e.g., AP1 performs A while AP2 performs B, and AP1 performs B while AP2 performs A; A=D, B=E), or in stages (e.g., AP1 performs A, AP1 performs B while AP2 performs D, AP1 performs C while AP2 performs E, and AP1 performs A while AP2 performs F; AP2 may be one step behind AP1). AP3 can perform wireless sensing relative to AP1 only, AP2 only, or both AP1 and AP2.

[0276] In some embodiments, a distributed computing "recipe" is implemented: the AP can use non-TB sensing measurements by sending NDPA+NDP to the IoT device so that the measurement results are generated at the IoT device. Distributed computing at the IoT device requires only local reporting; there is no over-the-air transmission of the measurement results.

[0277] In some embodiments, the sensing by proxy (SBP-LR) procedure with local reporting for multiple SBP-LR-requesting STAs (e.g., one request for 10 Hz / 20 MHz / 1 antenna, one request for 30 Hz / 40 MHz / 4 antennas, and one request for 15 Hz / 40 MHz / 3 antennas) can be defined as follows: When multiple SBP-LR-requesting STAs send SBP-LR requests to an SBP-LR-capable AP STA, the AP can assign an SBP-LR setup ID to each set of requested parameters. For those with identical requested parameters, the SBP-LR setup ID can be the same, which means sharing an SBP-PR setup ID. When the AP establishes a session with a non-AP STA, the AP obtains the maximum parameter set supported by the non-AP STA. Therefore, the AP can know which non-AP STAs can participate in each SBP-LR setup. The AP performs measurement setup with each non-AP STA using the measurement setup based on the SBP-LR setup. Some measurement setup IDs may be reserved for the SBP-LR setup.

[0278] In some embodiments, selective SBP may be applied. A proxy initiator (e.g., SBP initiator) may send a request to a wireless access point (AP) that is a proxy responder (e.g., SBP responder) to perform non-selective wireless sensing (e.g., SBP) between the AP (acting as a sensing initiator on behalf of the proxy initiator) and any available sensing responders (e.g., non-AP STAs / devices, another AP, mesh AP) in the AP's wireless network. Each available sensing responder may be assigned / associated with an identity (ID, e.g., MAC address). The proxy initiator (e.g., SBP initiator) may send another request to the AP to perform selective wireless sensing (e.g., selective SBP) with a group of selected sensing responders in the AP's wireless network. Each selected sensing responder may be identified by its respective ID. The same or different sensing configurations may be used for different sensing responders. For a sensing responder, the same or different sensing configurations may be used for different target tasks (in the case of multiple target tasks) or different proxy initiators (in the case of multiple proxy initiators).

[0279] The proxy initiator can request the AP to provide a list of sensing-enabled devices in the AP's network that support / capable of wireless sensing (e.g., 802.11bf compatible) along with associated device information (e.g., device name, hostname, vendor class ID, device product name). The proxy initiator can select a selected sensing responder based on the list and associated device information.

[0280] The proxy initiator can use a two-stage approach to perform selective wireless sensing for the target task. In Stage 1, the proxy initiator can request / perform / use non-selective wireless sensing (i.e., sensing by all available sensing responders) to perform a trial / test / training task with all sensing responders and select selected sensing responders based on the sensing results and some criteria. The trial / test / training task can be a motion detection task. In the trial / test / training task, the location (or mapping to the target physical device) of each sensing responder within the venue can be estimated and the sensing responders can be selected based on their estimated location (or mapping). The proxy selector can also select some devices from the list of sensing-capable devices that did not participate in Stage 1.

[0281] Next, in stage 2, the proxy-initiator can request / perform selective wireless sensing for the target task using the selected sensing responders. The trial / test / training task may be related to the target task in some way. The trial / test / training task may have low sensing requirements so that all sensing-capable wireless responders can meet the requirements and participate in non-selective wireless sensing. The trial / test / training task may have sensing results that are useful for selecting the selected sensing responders.

[0282] The proxy initiator may use a two-stage approach to perform selective wireless sensing for two target tasks. For each target task, a respective Stage 1 may be performed followed by a respective Stage 2. Alternatively, a common Stage 1 may be performed in which a first group of selected sensing responders is selected for the first target task and a second group is selected for the second target task. The first group may or may not overlap with the second group. Separate Stages 2 may then be performed (e.g., sequentially, simultaneously, or contemporaneously) for the two target tasks based on the respective groups of selected sensing responders. If the first and second groups overlap with at least one common sensing responder appearing in both groups, sensing results associated with the common sensing responder may be shared by both target tasks.

[0283] Two different proxy initiators may use a two-stage approach to perform selective wireless sensing for their respective target tasks. For each target task of each proxy initiator, a respective stage 1 may be performed followed by a respective stage 2. Alternatively, a first common stage 1 may be performed for a first proxy initiator (to select a group of sensing responders selected for each of its target tasks), followed by a separate stage 2 (to perform selective wireless sensing for each of its target tasks). Similarly, a second common stage 1 may be performed for a second proxy initiator, followed by a separate stage 2 for each of its target tasks. Alternatively, a third common stage 1 may be performed for both proxy initiators, followed by a separate stage 2 for each target task. If a common sensing responder is selected for multiple target tasks, sensing results associated with the common sensing responder may be shared by the multiple target tasks.

[0284] A proxy initiator may be an "authorized" or "trusted" device that the AP permits / authorizes / authenticates to initiate either a non-selective SBP or a selective SBP, or both. A first test / configuration / procedure may be performed for the SBP-initiator to be authorized by the AP to initiate a non-selective SBP (first authorization). A second test / configuration / procedure may be performed for the SBP-initiator to be authorized by the AP to initiate a selective SBP (second authorization). An SBP-initiator may have either or both of the first authorization and the second authorization. Either the first authentication or the second authentication may imply the other.

[0285] The proxy initiator may be connected to the AP via a wireless connection (e.g., the AP's wireless network, WiFi, WiMax, 4G / 5G / 6G / 7G / 8G, Bluetooth, UWB, mmWave, etc.) or via a wired connection (e.g., Ethernet, USB, fiber optic, etc.).

[0286] A sensing responder may or may not support non-selective proxy sensing (e.g., SBP), selective proxy sensing, or both. When sending sensing results to an AP for onward transmission to a proxy initiator, the sensing responder may encrypt / process the sensing results so that they may not be decrypted / interpreted / consumed / sensed by the AP (which does not have the decryption key), but may be decrypted / interpreted / consumed / sensed by the proxy initiator (which does have the decryption key).

[0287] In some embodiments, an SBP initiator may request an SBP responder (e.g., during SBP setup, or during an SBP setup request frame, or during an SBP setup protocol / exchange / signaling) to restrict the sensing procedure in an SBP to a list of non-AP STAs selected as sensing responders, and an SBP responder may restrict the sensing procedure in an SBP to a list of non-AP STAs selected as sensing responders. Each selected non-AP STA may be specified by its MAC address. If requested, an SBP responder may not include non-AP STAs that are not selected as sensing responders in the sensing procedure in an SBP. An SBP initiator may include itself as one of the sensing responders.

[0288] In some embodiments, a bit pattern in the SBP setup request frame may be used to indicate the presence or absence of such a request. If the bit pattern indicates the presence of a request, a field indicating the number / count / quantity of selected non-AP STAs may be present in the SBP setup request frame. The MAC addresses of the list of selected non-AP STAs may be transmitted in or after the SBP setup request frame.

[0289] In some embodiments, there are different use cases for wireless sensing. The first use case for wireless sensing is shown in FIG. 4. In this case, an AP is both a sensing initiator and a sensing transmitter for wireless sensing. An 802.11bf-compatible STA may be a sensing responder and a sensing receiver for wireless sensing. In this case, sensing measurement results (e.g., CSI) may be fed back to the sensing initiator. Some sensing-based results (e.g., tasks and applications such as respiration detection and fall detection) may be calculated by the sensing initiator based on the sensing measurement results.

[0290] A second use case for wireless sensing is shown in Figure 5. In this case, the AP is both the sensing initiator and the sensing transmitter for wireless sensing. An 802.11bf-compatible STA may be the sensing responder and the sensing receiver for wireless sensing. In this case, there is no feedback of sensing measurement results (e.g., CSI) to the sensing initiator. Some sensing-based results may be calculated by the sensing responder based on the sensing measurement results. The sensing-based results may be used by the sensing responder or transmitted elsewhere.

[0291] A third use case of wireless sensing is shown in Figure 6. In this case, the AP is both the sensing responder and the sensing receiver for wireless sensing. An 802.11bf-compatible STA may be the sensing initiator and the sensing transmitter for wireless sensing. In this case, the sensing measurement results (e.g., CSI) may be fed back to the sensing initiator. Some sensing-based results (e.g., tasks and applications such as respiration detection, fall detection, etc.) may be calculated by the sensing initiator based on the sensing measurement results.

[0292] A fourth use case for wireless sensing is shown in Figure 7. In this case, the AP is both the sensing responder and the sensing receiver for wireless sensing. An 802.11bf-compatible STA may be the sensing initiator and the sensing transmitter for wireless sensing. In this case, there is no feedback of sensing measurement results (e.g., CSI) to the sensing initiator. Some sensing-based results may be calculated by the sensing responder (AP) based on the sensing measurement results. The sensing-based results may be used by the sensing responder or transmitted elsewhere.

[0293] A fifth use case of wireless sensing is shown in Figure 8. In this case, the AP is both the sensing initiator and the sensing receiver for wireless sensing. An 802.11bf-compatible STA may be the sensing responder and the sensing transmitter for wireless sensing. In this case, sensing measurement results (e.g., CSI) may be acquired by the sensing initiator. Some sensing-based results (e.g., tasks and applications such as respiration detection and fall detection) may be calculated by the sensing initiator based on the sensing measurement results.

[0294] A sixth use case of wireless sensing is shown in Figure 9. In this case, the AP is both the sensing responder and the sensing transmitter for wireless sensing. An 802.11bf-compatible STA may be the sensing initiator and the sensing receiver for wireless sensing. In this case, the sensing measurement results (e.g., CSI) may be acquired by the sensing initiator. Some sensing-based results (e.g., tasks and applications such as respiration detection and fall detection) may be calculated by the sensing initiator based on the sensing measurement results.

[0295] The seventh use case of wireless sensing is the proxy-based sensing (SBP) case shown in Figure 10. In this case, the AP is both the sensing initiator and the sensing transmitter for wireless sensing. An 802.11bf-compatible STA may be the sensing responder and the sensing receiver for wireless sensing. In this case, the sensing measurement results (e.g., CSI) may be fed back to the SBP-requesting STA. Some sensing-based results (e.g., tasks and applications such as respiration detection, fall detection, etc.) may be calculated by the SBP-requesting STA based on the sensing measurement results.

[0296] The eighth use case of wireless sensing is the proxy-based sensing (SBP) case shown in FIG. 11. In this case, the AP is both the sensing initiator and the sensing receiver for wireless sensing. An 802.11bf-compatible STA may be the sensing responder and the sensing transmitter for wireless sensing. In this case, the sensing measurement results (e.g., CSI) may be fed back to the SBP-requesting STA. Based on the sensing measurement results, the SBP-requesting STA may calculate sensing-based results (e.g., tasks and applications such as respiration detection, fall detection, etc.).

[0297] The ninth use case of wireless sensing is the sensing by proxy (SBP) case shown in Figure 12. In this case, the AP is both the sensing initiator and the sensing transmitter for wireless sensing. An 802.11bf-compatible STA may be the sensing responder and the sensing receiver for wireless sensing. In this case, there is no feedback of sensing measurement results (e.g., CSI) to the SBP-requesting STA. Some sensing-based results (e.g., tasks and applications such as respiration detection, fall detection, etc.) may be calculated by the sensing responder based on the sensing measurement results.

[0298] The tenth use case of wireless sensing is the proxy-based sensing (SBP) case shown in Figure 13. In this case, the AP is both the sensing initiator and the sensing transmitter for wireless sensing. An 802.11bf-compatible STA may be the sensing responder and the sensing receiver for wireless sensing. In this case, PPDUs are broadcast from the AP to one or more sensing responders with the same sensing measurement setup, and there is no feedback of the sensing measurement results (e.g., CSI) to the SBP-requesting STA. Some sensing-based results (e.g., tasks and applications such as respiration detection and fall detection) may be calculated by the sensing responder based on the sensing measurement results.

[0299] In some embodiments, the present teachings disclose systems and methods for wireless sensing. In some embodiments, when a sensing result (e.g., CSI) is reported locally at a sensing receiver, a timestamp may be included in the report. The timestamp includes the time at which a wireless signal (i.e., a sensing physical layer protocol data unit (PPDU) transmitted from the sensing transmitter to the sensing receiver) from a Type 1 device (which may be a sensing transmitter) was received by a Type 2 device (sensing receiver). In some embodiments, the timestamp may be used for time base correction (e.g., in respiration detection / monitoring).

[0300] In some embodiments, each measurement instance is associated with only one measurement setup, although it may be associated with multiple sessions.

[0301] However, it is useful to associate one measurement instance with multiple measurement setups. This means reduced airtime / bandwidth / network resources for sensing, reduced buffering memory, lower power consumption, longer battery life, etc. In some embodiments, there is sharing of measurement instances within a session. Figure 14 shows an example of associating a measurement instance with multiple measurement setup IDs.

[0302] In some embodiments, measurement instances can be shared between sessions. The standard allows one measurement instance to be associated with multiple sessions, so a measurement instance associated with multiple measurement setups can be associated with multiple {measurement setup ID, session ID} sets. Figure 15 shows an example of a measurement instance with multiple {measurement setup ID, session ID}s.

[0303] Thus, according to some embodiments, in 802.11bf, a measurement instance may or may not be allowed to be associated with one or more measurement setup IDs. According to some embodiments, in 802.11bf, a measurement instance may or may not be allowed to be associated with one or more {measurement setup ID, session ID}.

[0304] 16 is an exemplary block diagram of a first wireless device, e.g., a bot 1600, of a system for wireless sensing in accordance with some embodiments of the present disclosure. The bot 1600 is an example of a device that can be configured to implement various methods described herein. As shown in FIG. 16, the bot 1600 includes a processor 1602, a memory 1604, a transceiver 1610 consisting of a transmitter 1612 and a receiver 1614, a synchronization controller 1606, a power module 1608, an optional carrier configurator 1620, and a housing 1640 including a wireless signal generator 1622.

[0305] In this embodiment, processor 1602 controls the general operation of bot 1600 and may include one or more processing circuits or modules, such as a central processing unit (CPU), and / or any combination of general-purpose microprocessors, microcontrollers, digital signal processors (DSPs), field programmable gate arrays (FPGAs), programmable logic devices (PLDs), controllers, state machines, gate logic, discrete hardware components, dedicated hardware finite state machines, or any other suitable circuits, devices, and / or structures capable of performing calculations or other manipulations on data.

[0306] The memory 1604 may include both read-only memory (ROM) and random access memory (RAM) and may provide instructions and data to the processor 1602. A portion of the memory 1604 may also include non-volatile random access memory (NVRAM). The processor 1602 typically performs logical and arithmetic operations based on program instructions stored in the memory 1604. The instructions (also known as software) stored in the memory 1604 may be executed by the processor 1602 to perform the methods described herein. The processor 1602 and the memory 1604 together form a processing system that stores and executes software. As used herein, "software" refers to any type of instructions, whether referred to as software, firmware, middleware, microcode, or the like, that can configure a machine or device to perform one or more desired functions or processes. The instructions may include code (e.g., code in source code format, binary code format, executable code format, or any other suitable format). The instructions, when executed by one or more processors, cause the processing system to perform various functions described herein.

[0307] The transceiver 1610, including a transmitter 1612 and a receiver 1614, enables the bot 1600 to transmit and receive data to and from a remote device (e.g., the Origin or another bot). The antenna 1650 is typically mounted to the housing 1640 and is electrically coupled to the transceiver 1610. In various embodiments, the bot 1600 includes multiple transmitters, multiple receivers, and multiple transceivers (not shown). In one embodiment, the antenna 1650 is replaced with a multi-antenna array 1650 capable of forming multiple beams, each pointing in a separate direction. The transmitter 1612 can be configured to wirelessly transmit signals having different types or functions, and such signals are generated by the processor 1602. Similarly, the receiver 1614 is configured to receive wireless signals having different types or functions, and the processor 1602 is configured to process multiple different types of signals.

[0308] The bot 1600 in this example can function as a bot or Type 1 device or sensing transmitter for wireless sensing. The synchronization controller 1606 in this example is configured to control the operation of the bot 1600 to synchronize or asynchronously with another device, such as an Origin or another bot. In one embodiment, the synchronization controller 1606 can control the bot 1600 to synchronize with an Origin that receives a wireless signal transmitted by the bot 1600. In another embodiment, the synchronization controller 1606 may control the bot 1600 to transmit a wireless signal asynchronously with the other bots. In another embodiment, the bot 1600 and each of the other bots can transmit a wireless signal individually and asynchronously.

[0309] The carrier configurator 1620 is an optional component of the Bot 1600 for configuring transmission resources, e.g., time and carrier, for transmitting the wireless signal generated by the wireless signal generator 1622. In one embodiment, each CI in the time series of CIs has one or more components, each corresponding to a carrier or subcarrier for the transmission of the wireless signal. Wireless sounding sensing may be based on any one or any combination of the components.

[0310] The power module 1608 may include a power source, such as one or more batteries, and a power regulator to provide regulated power to each of the above-mentioned modules of Figure 16. In some embodiments, if the Bot 1600 is coupled to a dedicated external power source (e.g., a wall outlet), the power module 1608 may include a transformer and a power regulator.

[0311] The various modules described above are coupled together by a bus system 1630. The bus system 1630 may include, for example, a power bus, a control signal bus, and / or a status signal bus in addition to a data bus. It will be appreciated that the modules of the bot 1600 may be operably coupled to each other using any suitable technology and medium.

[0312] 16 illustrates a number of separate modules or components, those skilled in the art will appreciate that one or more of the modules may be combined or commonly implemented. For example, processor 1602 may implement the functionality described above with respect to processor 1602 as well as the functionality described above with respect to wireless signal generator 1622. Conversely, each of the modules illustrated in FIG. 16 may be implemented using multiple separate components or elements.

[0313] 17 is an exemplary block diagram of a second wireless device, e.g., Origin 1700, of a system for wireless sensing in accordance with an embodiment of the present teachings. Origin 1700 is an example of a device that can be configured to implement various methods described herein. In this example, Origin 1700 can function as an Origin or Type 2 device for wireless sensing or a sensing receiver. As shown in FIG. 17 , Origin 1700 includes a housing 1740 that includes a processor 1702, a memory 1704, a transceiver 1710 consisting of a transmitter 1712 and a receiver 1714, a power module 1708, a synchronization controller 1706, a channel information extractor 1720, and an optional motion detector 1722.

[0314] In this embodiment, the processor 1702, memory 1704, transceiver 1710, and power module 1708 operate similarly to the processor 1602, memory 1604, transceiver 1610, and power module 1608 of the Bot 1600. An antenna 1750 or multi-antenna array 1750 is typically mounted in the housing 1740 and electrically coupled to the transceiver 1710.

[0315] The Origin 1700 may be a second wireless device having a different type from the first wireless device (e.g., the Bot 1600). In particular, the channel information extractor 1720 in the Origin 1700 is configured to receive a wireless signal through a wireless channel and obtain time-series channel information (CI) of the wireless channel based on the wireless signal. The channel information extractor 1720 can transmit the extracted CI to an optional motion detector 1722 or a motion detector external to the Origin 1700 to perform wireless sounding sensing within the venue.

[0316] The motion detector 1722 is an optional component of the Origin 1700. In one embodiment, it is located within the Origin 1700, as shown in FIG. 17. In another embodiment, it is located outside the Origin 1700, in another device such as a bot, another Origin, a cloud server, a fog server, a local server, or an edge server. The optional motion detector 1722 may be configured to detect sound information from a vibrating object or source within the venue based on the motion information. The motion information may be calculated based on a time series of CIs by the motion detector 1722 or another motion detector outside the Origin 1700.

[0317] The synchronization controller 1706 in this example is configured to control the operation of the Origin 1700 to be synchronized or asynchronous with other devices, such as bots, other Origins, or independent motion detectors. In one embodiment, the synchronization controller 1706 controls the Origin 1700 to synchronize with a bot transmitting a wireless signal. In another embodiment, the synchronization controller 1706 controls the Origin 1700 to receive wireless signals asynchronously with other Origins. In another embodiment, the Origin 1700 and each of the other Origins may receive wireless signals individually and asynchronously. In one embodiment, the optional motion detector 1722 or a motion detector external to the Origin 1700 is configured to asynchronously calculate respective heterogeneous motion information based on respective time series of the CIs.

[0318] The various modules described above are coupled together by a bus system 1730. The bus system 1730 may include, for example, a power bus, a control signal bus, and / or a status signal bus in addition to a data bus. It will be appreciated that the modules of the Origin 1700 may be operably coupled to each other using any suitable technology and medium.

[0319] 17 illustrates a number of separate modules or components, those skilled in the art will appreciate that one or more of the modules may be combined or co-implemented. For example, processor 1702 may implement the functionality described above with respect to processor 1702 as well as the functionality described above with respect to channel information extractor 1720. Conversely, each module illustrated in FIG. 17 may be implemented using multiple separate components or elements.

[0320] FIG. 18 shows a flowchart of an example method 1800 for wireless sensing in accordance with some embodiments of the present disclosure. In various embodiments, method 1800 may be performed by the systems disclosed above. At operation 1802, a time series of wireless sounding signals (WSS) is transmitted by a transmitter in a wireless data communication network based on a wireless protocol associated with the communication network. The wireless data communication network may be composed of multiple layers: a physical (PHY) layer, a medium access control (MAC) layer, and at least one upper layer. At operation 1804, the time series of WSS (TSWSS) is received by a receiver in the wireless data communication network based on the wireless protocol via a wireless channel of a venue. At operation 1806, multiple wireless sensing measurements are performed by the receiver based on the received TSWSS to obtain sensing measurement results. At operation 1808, the sensing measurement results are reported by the PHY layer (or MAC layer) of the receiver to at least one upper layer of the receiver. In operation 1810, a sensing-based task is performed by at least one upper layer of the receiver based on the sensing measurement results. The order of the operations in FIG. 18 can be changed according to various embodiments of the present teachings.

[0321] In some embodiments, the present teachings disclose a method for bidirectional P2P sensing. In one example of bidirectional P2P sensing, an AP may be a sensing initiator, and both the first and second non-AP STAs may be sensing responders. In another example, a non-AP STA may be a proxy-based sensing (SBP) initiator that requests an AP (SBP responder) to perform bidirectional P2P sensing, and in bidirectional P2P sensing, the AP may be the sensing initiator, and both the first and second non-AP STAs may be sensing responders.

[0322] In both embodiments, the AP can individually configure / negotiate / arrange with two non-AP STAs so that they can identify each other (each having at least one corresponding ID, e.g., an identifiable network address, an identifiable wireless network address / ID, an AP-assigned ID, an initiator-assigned ID, a user-defined ID, or a MAC address), and the two non-AP STAs transmit NDP to each other as a sounding signal so that sensing measurements are acquired / generated at both non-AP STAs. The AP can transmit a second P2P sensing trigger frame to the pair of non-AP STAs. The second P2P sensing trigger frame may be an NDPA frame, a trigger frame, a special NDPA-trigger frame (described above), a first P2P sensing trigger frame, or another frame. A separate first P2P sensing trigger frame may be transmitted to each pair of non-AP STAs, or a common / shared first P2P sensing trigger frame may be transmitted to multiple (e.g., some or all) available STAs. Next, the first non-AP STA sends an NDP to the second non-AP STA to generate sensing measurement results at the second non-AP STA, and the second non-AP STA sends an NDP to the first non-AP STA to generate sensing measurement results at the first non-AP STA. The sensing measurement results may be used / required at the second non-AP STA, or the sensing results may optionally be transmitted from the second non-AP STA (sensing responder) to the AP (sensing initiator). In the SBP example, the AP (SBP responder) may further report the sensing results to the SBP initiator.

[0323] In another example, a first and a second non-AP STA can perform unidirectional P2P sensing or bidirectional P2P sensing without signaling from the AP. The two non-AP STAs can identify each other and configure / negotiate / coordinate with each other. In unidirectional P2P sensing, an NDP can be unilaterally transmitted from a first non-AP STA to a second non-AP STA to generate a sensing result at the second non-AP STA. The second non-AP STA may optionally transmit its sensing result to the first non-AP STA. In bidirectional P2P sensing, an NDP can be transmitted bidirectionally between two non-AP STAs without signaling from the AP.

[0324] An AP-initiated sensing procedure may optionally allow responder-to-responder sounding for responder-to-responder bidirectional sensing. For example, an AP-initiated sensing procedure may optionally allow bidirectional sounding between two responders, with an NDP from Responder 1 (R1) to Responder 2 (R2) and another NDP from Responder 2 (R2) to Responder 1 (R1). This is useful when there are N responders forming a daisy chain, scan order, or configuration.

[0325] In the example where N=3, the three responders R1, R2, and R3 can form a closed daisy chain or closed loop. R2 can obtain the CSI between R1 and R2 and the CSI between R2 and R3. R2 can perform useful WLAN sensing calculations based on the two CSIs. Optionally, the CSI is reported to the AP.

[0326] 19 shows an example of bidirectional responder-to-responder sensing. In this example, four sensing responders R1, R2, R3, and R4 are configured to form a network (e.g., a daisy chain). Some "links" can perform bidirectional sensing (e.g., R1-R2 or R2-R3), with each linked pair transmitting NDPs to each other in tandem (e.g., NDP from R1 to R2 and NDP from R2 to R1).

[0327] Some links have one-way sensing (e.g., R3-R4, R4-R1), where NDP is sent in only one direction. R2 has two CSIs: the CSI between R1 and R2 and the CSI between R2 and R3 (and potentially more if R2 is linked to additional responders, such as R4). In some embodiments, reporting of sensing measurements is optional.

[0328] According to some embodiments, in optional responder-to-responder sensing, a first sensing responder should be allowed to perform one-way or two-way sensing with a second sensing responder. In one-way sensing, an NDP is sent from the first responder to the second responder. In two-way sensing, an NDP is sent from the first responder to the second responder, followed by another NDP from the second responder to the first responder.

[0329] In some embodiments, the present teachings also disclose terminating or pausing session setup / measurement setup associated with a sensing responder. The AP may determine that sensing measurements (e.g., CSI, CIR, CFR, RSSI) associated with a particular sensing responder are unusable, useless, and / or not most useful for the task (e.g., too noisy, too unstable, too chaotic, too much interference, unreliable, faulty, or a user "pauses" or "stops" sensing associated with a particular responder, or a user "pauses" or "stops" sensing associated with all sensing responders, etc.), or in the case of sensing by proxy (SBP), may receive the determination from the SBP initiator. The determination may be based on (i) tests on the sensing measurements (e.g., based on tests / measurements for noise, stability, variability, randomness / chaos, interference, reliability, failures, errors, and / or mistakes), and / or (ii) system states / conditions / tests (e.g., whether transmitting / storing / associated processing / sensing computations of the sensing measurements consumes too much bandwidth / memory / processing power / time or generates too much power, or another task of higher priority may require the resources currently allocated to the sensing measurements). There may be a determination that sensing measurements associated with another sensing responder may be useful, less wasteful, and / or more useful to the task.

[0330] As a result, the AP may terminate the setup of a sensing session associated with a particular sensing responder, or may receive a request for such from the SBP initiator in the case of an SBP. The AP may wait a certain period of time (e.g., until any interference / noise / unstable / unreliable / adverse conditions end, or until the user "unpauses" or "unstops" sensing), and then initiate another sensing session (by performing a sensing session setup) with the particular sensing responder using the same, similar, or modified sensing session setup configuration as the terminated sensing session setup, or may receive a request for such from the SBP initiator in the case of an SBP. The determination of the period of time may be based on several criteria.

[0331] Alternatively, instead of terminating the sensing session setup, the AP may terminate a specific sensing measurement setup associated with a specific sensing responder and may receive a request from the SBP initiator in the case of an SBP. The AP may wait for a certain period of time and then initiate another sensing measurement setup with the specific sensing responder with the same or similar settings as the terminated specific sensing measurement setup, or may receive a request from the SBP initiator in the case of an SBP.

[0332] Alternatively, the AP may be requested to suspend a sensing session (i.e., setting up a sensing session) with a particular sensing responder for a certain period of time and resume the sensing session after a certain period of time, or in the case of an SBP, may receive a request from the SBP initiator.

[0333] Alternatively, the AP may suspend a specific sensing measurement session with a specific sensing responder for a certain period of time and resume the specific sensing measurement session after a certain period of time, or in the case of an SBP, may receive a request from the SBP initiator.

[0334] In some embodiments, a sounding signal may be multicast or broadcast from an AP to multiple sensing responders within an SBP. The AP may be both a sensing initiator and a sensing transmitter (e.g., in a sensing session or in an SBP). The AP may transmit a sounding signal (e.g., NDP) individually to each of multiple sensing responders (i.e., point-to-point sounding). Alternatively, the sounding signal (e.g., NDP) may be transmitted to multiple sensing responders using multicast or broadcast, and sensing measurements may be generated simultaneously or concurrently at the multiple sensing responders. The sensing measurements may be optional (i.e., may / may not be reported to the AP). In the case of an SBP, the AP may optionally (i.e., may / may not) report the sensing measurements to the SBP initiator.

[0335] In some embodiments, the present teachings disclose systems and methods for ad hoc network sensing, peer-to-peer mode sensing, and non-infrastructure mode (NIM) sensing, such as wireless sensing in wireless ad hoc networks or distributed wireless networks (e.g., WiFi in non-infrastructure mode or peer-to-peer mode, Bluetooth, or other devices in non-infrastructure mode or peer-to-peer mode, WiFi Direct, mobile ad hoc networks (MANETs), vehicular ad hoc networks (VANETs), SPAN, wireless mesh networks). In some embodiments, ad hoc networks do not rely on existing infrastructure (e.g., ad hoc networks do not have access points / APs), making them suitable for applications that cannot rely on a centralized node. Ad hoc networks tend to require minimal configuration and can be deployed quickly, making them suitable for emergencies, natural disasters, temporary / special events, or robotics.

[0336] Wireless sensing procedures can be used in infrastructure mode (non-ad hoc networks) where an access point (AP) establishes / organizes / manages the wireless network. A STA (AP STA or non-AP STA) can act as a sensing initiator that initiates a sensing procedure (infrastructure mode). One or more other STAs can act as sensing responders by participating in the sensing procedure. A STA can initiate multiple wireless sensing procedures with respective sets of sensing responders and respective configurations of sensing parameters / configurations. There may be multiple STAs, each initiating a respective sensing procedure.

[0337] The AP is the sensing initiator or the sensing responder. Sounding signals may be transmitted from a STA (sensing transmitter) to another STA (sensing responder). These signals may be transmitted from the AP to non-AP STAs, from non-AP STAs to the AP, or both, or neither. When the AP is the initiator of sensing, trigger-based (TB) sensing may be used. Triggering the transmission of a sounding signal (e.g., non-data packet (NDP), a variant of NDP) may be achieved by the AP transmitting an NDP announcement frame (NDPA) or a trigger frame variant (TF). A short time after a trigger (e.g., interframe space (IFS), short IFS (SIFS), reduced IFS (RIFS), PCF IFS (PIFS), DCF IFS (DIFS), arbitrary IFS (AIFS), extended IFS (EIFS), etc.), an NDP can be sent from the AP (sensing initiator) to a non-AP STA (sensing responder), or from non-AP STA(s) to the AP, or both, or from a non-AP STA to another non-AP STA to generate a sensing result. When a non-AP STA is the sensing initiator, non-TB sensing can be used, in which the non-AP STA sends an NDPA to the AP, followed by an initiator-to-responder (I2R) NDP and a responder-to-initiator (R2I) NDP pair. Either NDP can be used to generate a sensing result at the sensing receiver. Reporting the sensing result to the sensing initiator is optional.

[0338] In some embodiments, the present teachings disclose non-infrastructure mode (NIM) wireless sensing based on a protocol (e.g., 802.11, 802.11bf) for a wireless ad-hoc network consisting of multiple peer-to-peer wireless devices or wireless stations (STAs) in a non-infrastructure mode. Non-infrastructure mode wireless sensing (including frames, exchanges, timing, specifications, etc.) can follow / be based on a protocol or standard (e.g., 802.11, 802.11bf). Similar to infrastructure mode, a non-infrastructure mode STA can act as a sensing initiator by initiating a non-infrastructure mode sensing procedure or sensing session (e.g., by sending a request to a neighboring station in the ad-hoc network). The non-infrastructure mode sensing procedure can be similar to the infrastructure mode sensing procedure, except that the AP is replaced by a non-infrastructure mode STA. Similar to infrastructure mode, other STA(s) in non-infrastructure mode can act as sensing responders by participating in non-infrastructure mode sensing procedures (e.g., by replying to a request from the sensing initiator indicating their willingness to participate). A non-infrastructure mode STA can initiate multiple non-infrastructure mode sensing procedures or sensing sessions, with each procedure / session conducted with a respective set of sensing responders (also non-infrastructure mode STAs). Multiple STAs in non-infrastructure mode in an ad hoc network can act as sensing initiators, each with its own non-infrastructure mode sensing procedure or sensing session.

[0339] In a non-infrastructure mode sensing procedure, the sensing initiator may be a sensing transmitter, a sensing receiver, both, or nothing. The sensing responder may be a transmitter, a receiver, or both. A sounding signal may be transmitted from the sensing transmitter to the sensing receiver. If bidirectional sensing is supported, the sounding signal may also be transmitted in the reverse direction. The sounding signal may be transmitted from the sensing initiator to the sensing responder, or from the sensing responder to the sensing initiator, or both, or from the first sensing responder to the second responder.

[0340] Trigger-based (TB) sensing in non-infrastructure mode may be performed similarly to TB sensing in infrastructure mode, except that the infrastructure mode AP is replaced with a non-infrastructure mode sensing initiator. Triggering of sounding signal (e.g., NDP, NDP variant) transmission may be achieved by the sensing initiator transmitting an NDPA or an NDPA-like frame, or a TF or a TF-like frame. A short time after the trigger (e.g., IFS, SIFS, RIFS, PIFS, DIFS, AIFS, EIFS, etc.), an NDP may be transmitted from the sensing initiator to the sensing responder, or from the sensing responder to the sensing initiator, or both, or from the first sensing responder to the second sensing responder, and a sensing result may be generated (at the sensing receiver).

[0341] Similar to infrastructure mode non-TB sensing, non-infrastructure mode non-TB sensing may be performed, in which the sensing initiator sends an NDPA to the sensing responder, followed by a pair of initiator-to-responder (I2R) NDP and responder-to-initiator (R2I) NDP. In non-infrastructure mode non-TB sensing, the sensing responder may send an NDPA to the sensing initiator, followed by a pair of initiator-to-responder (I2R) NDP and responder-to-initiator (R2I) NDP.

[0342] Any NDP may be used to generate the sensing results at the sensing receiver, and reporting the sensing results to the sensing initiator is optional.

[0343] In some embodiments, for non-infrastructure mode (e.g., polling phase in TB sensing), a frame (public or protected) similar to the trigger frame variant (TF) may be defined in a protocol or standard (e.g., 802.11, 802.11bf) that allows a STA in non-infrastructure mode (e.g., sensing initiator) to request an NDP transmission from another STA in non-infrastructure mode to obtain sensing measurements. If a STA in non-infrastructure mode is available, the STA can respond with a CTS-to-self.

[0344] In some embodiments, the TF of the protocol or standard may be defined / improved / modified / changed to allow a STA in non-infrastructure mode to request NDP transmissions from other STAs in non-infrastructure mode to obtain sensing measurements. When the TF is transmitted by an AP (infrastructure mode), the AP can request NDP transmissions from the STA to obtain sensing measurements. When the TF is transmitted by a STA in non-infrastructure mode, the STA can request NDP transmissions from other STAs in non-infrastructure mode to obtain sensing measurements.

[0345] The non-infrastructure mode NDPA sounding phase may consist of the transmission of an NDPA or NDPA-like frame by a non-infrastructure mode STA (e.g., a sensing initiator or sensing responder) and the transmission of an NDP by the non-infrastructure mode STA (e.g., the sensing initiator, or sensing responder, or sensing transmitter) a short time (e.g., IFS, SIFS, RIFS, PIFS, DIFS, AIFS) after the NDPA transmission. For example, NDPA sounding may be used by 802.11 High Efficiency (HE), Very High Throughput (EHT), or pre-HE STAs.

[0346] The non-infrastructure mode TF sounding phase may consist of a non-infrastructure mode STA (e.g., a sensing initiator or sensing responder) transmitting a TF or a TF-like frame to request an NDP transmission from another STA, and a short time (e.g., IFS, SIFS, RIFS, PIFS, DIFS, AIFS, EIFS, etc.) after receiving the TF or TF-like frame, transmitting an NDP by the other STA (e.g., from another STA to that STA, from that STA to another STA, or from another STA to yet another STA).

[0347] A non-infrastructure mode non-TB sensing measurement instance may be performed as follows: When a non-infrastructure mode STA (e.g., sensing transmitter, sensing initiator, sensing responder) obtains a transmit opportunity (TXOP), it initiates a non-infrastructure mode non-TB sensing measurement instance by sending an NDPA to the sensing receiver, followed by an I2R NDP (from the sensing initiator to the sensing responder) and an R2I NDP (from the sensing responder to the sensing initiator) pair. If the sensing initiator is a sensing transmitter only, the NDPA frame configures the R2I NDP to be transmitted with a minimum length of one LTF symbol. If the sensing responder is a sensing transmitter only, the NDPA frame configures the I2R NDP to be transmitted with a minimum length of one LTF symbol.

[0348] The proxy-based sensing (SBP) procedure is primarily used in infrastructure mode. In infrastructure mode SBP, a non-AP STA (acting as an SBP initiator) sends an SBP request (using an SBP Request frame or "Infrastructure mode SBP Request frame") to an AP (acting as an SBP responder), and the AP accepts the SBP request by sending an SBP response (using an SBP Response frame). The AP then performs the sensing procedure with multiple sensing responders (with the SP acting as the sensing initiator) and optionally reports the sensing measurement results (e.g., CSI).

[0349] In some embodiments, for infrastructure mode SBP, an infrastructure mode SBP responder (and also a sensing initiator) may be performing an existing sensing procedure before receiving an SBP request from the SBP initiator. A sensing procedure may or may not be associated with another SBP procedure initiated by another SBP initiator. An existing sensing procedure may consist of many existing sensing responders and may be associated with a set of sensing measurement configurations / parameters.

[0350] In one case, the sensing measurement configuration / parameters of an existing sensing procedure may be acceptable to the SBP initiator (for the requested SBP), and the SBP responder can simply associate the existing sensing procedure with the requested SBP and send / share the sensing measurements from the existing sensing procedure to the SBP initiator.

[0351] In another case, the sensing measurement settings / parameters of an existing sensing procedure may not be acceptable to the SBP initiator (for the requested SBP). The SBP responder / sensing initiator, in cooperation with the sensing responder, can adjust / modify one or more sensing measurement settings / parameters of the existing sensing procedure so that the adjusted / modified sensing procedure with the adjusted / modified sensing measurement settings / parameters is acceptable to the SBP initiator. The SBP responder can then associate the existing sensing procedure with the requested SBP and send / share the sensing measurements from the existing sensing procedure to the SBP initiator.

[0352] For example, one of the following settings / parameters of an existing sensing procedure can be adjusted / changed: sounding frequency / timing (e.g., 0.1 / 1 / 10 / 100 / 1000 / 10000 Hz), carrier frequency (e.g., channel number, 2.4 GHz, 5 GHz, 6 GHz, etc.), bandwidth (e.g., 20 / 40 / 80 / 160 / 320 / 640 MHz, or part of bandwidth / sharing), unicast / multicast / broadcast, sensing transmitter / receiver settings, trigger (TB sensing, NDPA / TF use, non-TB sensing, etc.), antenna amount, optional reporting of sensing measurements, type of sensing measurements reported, set of sensing responders.

[0353] In another case, the sensing measurement settings / parameters of an existing sensing procedure may be partially acceptable (for the requested SBP) to the SBP initiator. It may become acceptable if augmented by another sensing procedure. For example, the SBP initiator may request a 100 Hz sounding frequency, but the existing sensing procedure has a 50 Hz sounding frequency. The SBP responder can initiate a complementary / auxiliary sensing procedure with a 50 Hz sounding frequency and time the soundings of the complementary / auxiliary sensing procedure so that the two sensing procedures together produce the 100 Hz sounding frequency requested by the SBP initiator.

[0354] In another example, an SBP initiator may request a 100 Hz sounding frequency, but the existing sensing procedure has a 25 Hz sounding frequency (uniform timing / sampling). The SBP responder can initiate a complementary / auxiliary sounding procedure with a sounding frequency of 75 Hz (non-uniform timing / sampling) and time the soundings of the complementary / auxiliary sounding procedure so that the two sounding procedures together produce the 100 Hz (uniform sounding / sampling) sounding frequency requested by the SBP initiator. For example, the SBP responder could obtain one sensing measurement from the existing sensing procedure, then obtain three sensing measurements from the auxiliary sensing procedure, then obtain another sensing measurement from the existing sensing procedure, then obtain three more sensing measurements from the auxiliary sensing procedure, and so on.

[0355] In another example, an SBP initiator may request an 80 MHz bandwidth, but the existing sensing procedure has a 40 MHz bandwidth. The SBP responder can initiate a complementary / auxiliary sensing procedure with a 40 MHz bandwidth, and the two sensing procedures together can produce the 80 MHz bandwidth requested by the SBP initiator.

[0356] The SBP request frame may have a field (e.g., a bit or a bit pattern) indicating whether multiple sensing procedures are allowed in the SBP procedure (for one / some / any / all sensing responders), or whether "mix-and-match" of sensing procedures is allowed in the SBP procedure.

[0357] In some embodiments, an SBP request frame or associated frame may include a specification / description / list of allowed sensing responders (or allowed / preferred sensing responders). An SBP initiator may restrict the SBP procedures performed / initiated by an SBP responder / sensing initiator such that the SBP responder / sensing initiator only allows allowed sensing responders to participate in the sensing procedure (or the SBP initiator may only desire / prefer to receive sensing measurements from allowed sensing responders, and the SBP responder may only provide sensing measurements from allowed sensing responders to the SBP initiator). Other sensing responders not in the list of allowed sensing responders may be "not allowed" and not allowed to participate in the sensing procedure. To identify the allowable sensing responders, the SBP initiator may provide a unique identifier (ID) (e.g., a user ID (UID), association (AID), universally unique ID (UUID), globally unique ID (GUID), MAC address, or Internet Protocol (IP) address, an internal ID within the system, etc.) for each allowable sensing responder in the SBP request frame or associated frame.

[0358] In some embodiments, an SBP initiator can send an SBP update frame to an SBP responder at any time during the sensing step of an SBP procedure to update / change / modify at least one setting / parameter of the SBP procedure. For example, an SBP initiator can request an SBP responder / sensing initiator (e.g., using an SBP update frame) to terminate / stop a particular sensing responder (e.g., because the sensing measurements / TSCIs associated with the particular sensing responder may be noisy, problematic, unstable, defective, unreliable, etc., and may be wasting valuable network resources such as TXOPs, data bandwidth, memory, computing power, and / or energy for processing / transmitting), and at least request that the SBP responder / sensing initiator stop transmitting the sensing measurements / TSCIs associated with the particular sensing responder. An SBP initiator can request an SBP responder / sensing initiator to suspend, resume, or add a particular sensing responder. An SBP may provide a unique identifier for a particular sensing responder.

[0359] In some embodiments, a non-infrastructure mode (NIM) SBP procedure is defined that is similar to infrastructure mode SBP, except that the AP in infrastructure mode SBP is replaced by a non-infrastructure mode STA. A frame (public or protected) similar to the SBP request frame is defined in the protocol or standard (802.11, 802.11bf) using which a non-infrastructure mode STA (acting as an SBP initiator, or NIM SBP initiator) can send an NIM SBP request to another non-infrastructure mode STA (acting as an SBP responder, or NIM SBP responder, similar to an infrastructure mode SBP AP) that sends an NIM SBP response (e.g., an SBP response frame or a similar frame) to accept the SBP request. The SBP Request frame can have a bit / field that indicates / specifies whether the SBP responder is a sensing transmitter, a sensing receiver, both, or neither in the NIM sensing procedure initiated by the SBP responder. Another STA (that is both an SBP responder and a sensing initiator) can then perform / initiate NIM sensing procedures with multiple sensing responders (STAs in non-infrastructure mode). Measurement results obtained in non-infrastructure mode sensing procedures may optionally be reported from the sensing responders to the sensing initiator and from the SBP responders (sensing initiators) to the SBP initiator. Another STA (i.e., an SBP responder and a sensing initiator) may assign a Measurement Setup ID in its SBP response.

[0360] In some embodiments, the infrastructure mode (IM) SBP Request frame may be defined / improved / modified / altered to allow a non-infrastructure mode STA (SBP initiator) to send a non-infrastructure mode SBP request to another non-infrastructure mode STA.

[0361] The NIM SBP response sent by another STA in non-infrastructure mode may be a frame similar to an IM SBP Response frame, or may be an IM SBP Response frame itself as defined / modified by a protocol or standard to allow another STA in non-infrastructure mode to accept or reject the NIM SBP request.

[0362] In some embodiments, an SBP initiator can specify / describe / list / provide the number of allowed sensing responders. The SBP initiator can limit the NIM SBP procedures or NIM sensing procedures performed / initiated by the SBP responder / sensing initiator so that the SBP responder / sensing initiator only allows the allowed number of sensing responders to participate in the NIM sensing procedure (or the SBP initiator can desire / prefer to receive sensing measurements only from allowed sensing responders, and the SBP responder can only provide sensing measurements from allowed sensing responders to the SBP initiator). Other sensing responders not on the list of allowed sensing responders may be "unauthorized" and not allowed to participate in the NIM sensing procedure. To specify the number of allowed sensing responders, the SBP initiator may provide a unique identifier (ID) for each allowed sensing responder (e.g., a user ID (UID), association (AID), universally unique ID (UUID), globally unique ID (GUID), MAC address, or Internet Protocol (IP) address, system internal ID, etc.).

[0363] In some embodiments, an SBP initiator can send a NIM SBP update frame to an SBP responder at any time during the NIM sensing procedure of an NIM SBP procedure to update / change / modify at least one setting / parameter of the NIM SBP procedure. For example, an SBP initiator can request an SBP responder / sensing initiator (e.g., using a NIM SBP update frame) to terminate / stop a particular sensing responder (e.g., because perhaps the sensing measurements / TSCIs associated with the particular sensing responder may be noisy, problematic, unstable, defective, unreliable, etc., and may be wasting valuable network resources such as TXOPs, data bandwidth, memory, computing power, and / or energy to process / transmit), or at least to stop transmitting the sensing measurements / TSCIs associated with the particular sensing responder. An SBP initiator can request an SBP responder / sensing initiator to pause, resume, or add a particular sensing responder. The SBP may provide a unique identifier for a particular sensing responder.

[0364] In infrastructure mode, the sensing procedure initiated by the AP STA is optionally extended to allow NDP measurements between sensing responders.

[0365] In some embodiments, a non-infrastructure mode sensing procedure initiated by a non-infrastructure mode STA may be optionally extended to allow sensing responder-to-sensing responder NDP measurements. A first sensing responder and a second sensing responder, both non-infrastructure mode STAs, may be configured to send NDP from the first responder to the second responder, or from the second responder to the first responder, or both.

[0366] In some embodiments, a non-infrastructure mode STA in an ad-hoc network acts as a sensing initiator that initiates a non-infrastructure mode sensing procedure based on a protocol (e.g., 802.11, 802.11bf). At least one other STA in the non-infrastructure mode ad-hoc network participates in the sensing procedure as a sensing responder based on the protocol. The sensing initiator and sensing responder negotiate to set up a sensing procedure / session and associated sensing measurement parameters.

[0367] In some embodiments, one device is set up as a sensing transmitter (Type 1 device). The other device is set up as a sensing receiver (Type 2 device). A wireless sounding signal (e.g., NDP, time series of NDP) is transmitted from the sensing transmitter to the sensing receiver, which generates a sensing measurement (e.g., TSCI). The NDP can be I2R or R2I depending on which device is the sensing transmitter.

[0368] The sensing measurements may be made available locally to an application (e.g., software, firmware) in the sensing receiver. The sensing measurements may optionally be transmitted wirelessly (e.g., using protocol-based sensing measurement report frames) from the sensing responder to the sensing initiator or from the sensing receiver to the sensing transmitter for availability to an application (e.g., software, firmware) in the sensing initiator.

[0369] In some embodiments, there may be multiple wireless mesh routers in a mesh network, e.g., R1, R2, R3, ..., R_k, for some k (e.g., k may be 3, 4, 6, 10, or 100). Some mesh routers may be dual-band, tri-band, or quad-band devices. Some backchannels may allow mesh routers to send / receive / transfer / channel / exchange digital data to / from the Internet / broadband service (e.g., via some broadband router / service provider). Mesh routers may be interconnected via non-infrastructure mode. Individual wireless client devices (e.g., IoT devices) may be connected to any one of multiple mesh routers (e.g., in infrastructure mode or non-infrastructure mode). Wireless client devices and / or mesh routers may form a wireless sensing network, with some being wireless transmitters (e.g., sensing transmitters) and some being wireless receivers (e.g., sensing receivers). Some (e.g., sensing initiators) may initiate wireless sensing procedures / sessions. Some may respond to participate in the wireless sensing procedure / session.

[0370] In some embodiments, each mesh router is available for client devices to connect to, but it may be better to "encourage" or "move" or "reconnect" or "reconnect" or "concentrate" most or all of the client devices to one (or very few) mesh routers, if possible. With all client devices connecting to the same mesh router, the sensing network may provide better coverage of the venue and / or the sensing network's functions / logic / algorithms may function better. For example, a system may concentrate all client devices to one or more specific mesh routers (e.g., R1). However, in a large location, multiple mesh routers may be required to provide overall coverage. In that case, two or more mesh routers may be identified as specific mesh routers.

[0371] In some embodiments, some signaling (protocol, control data / frame exchange) may be performed to propose / instruct / request / ask / instruct the client device to disconnect from its current mesh router and connect with a specific mesh router (or one of several specific mesh routers), each of which may be identified (SSID, name, MAC address, etc.).

[0372] Figure 20 shows a large number of STAs in non-infrastructure mode forming an ad-hoc network. There is no access point (AP) in this ad-hoc network. Figures 21 to 25 show various use cases of non-infrastructure mode sensing.

[0373] FIG. 21 shows use case 1, in which the sensing initiator is the sensing transmitter. First, a STA (as the sensing initiator) starts a sensing session. Some STAs join the sensing session (as sensing responders). Some STAs do not join the sensing session. The sensing initiator is the sensing transmitter (Tx). In some embodiments, TB-like sensing may be performed using NDPA (I2R) and NDP (I2R). In some embodiments, non-TB-like sensing may be performed using NDPA (I2R), NDP (I2R), and NDP (R2I). Bidirectional sensing may be supported (i.e., both Tx and Rx), and sensing measurement reporting may be optional.

[0374] Figure 22 shows use case 2 in which the sensing initiator is the sensing receiver. First, a STA (as the sensing initiator) starts a sensing session. Some STAs join the sensing session (as sensing responders). Some STAs do not join the sensing session. The sensing initiator is the sensing receiver (Rx). In some embodiments, TB-like sensing may be performed using TF (I2R) and NDP (R2I). In some embodiments, non-TB-like sensing may be performed with: NDPA (I2R) and NDP (I2R) and NDP (R2I). Bidirectional sensing may be supported (i.e., both Tx and Rx), and sensing measurement reporting may be optional.

[0375] Figure 23 shows use case 3 in which responder-to-responder (R2R) sensing is performed. First, a STA initiates a sensing session (as a sensing initiator). Some STAs participate in the sensing session (as sensing responders). Some STAs do not participate in the sensing session. A first responder (Tx) may be configured to transmit a sounding signal to a second responder (Rx). Bidirectional sensing may be supported (i.e., both Tx and Rx), and sensing measurement reporting may be optional.

[0376] Figure 24 shows use case 4, in which proxy-based sensing (SBP) is performed and the sensing initiator is the sensing transmitter. First, an STA (SBP initiator) requests another STA (SBP responder, sensing initiator) to initiate a sensing session. The sensing initiator is the sensing transmitter (Tx). In some embodiments, TB-like sensing can be performed using NDPA (I2R) and NDP (I2R). In some embodiments, non-TB-like sensing can be performed using: NDPA (I2R) and NDP (I2R) and NDP (R2I). Bidirectional sensing may be supported (i.e., both Tx and Rx), and sensing measurement reporting may be optional.

[0377] Figure 25 shows use case 5, in which proxy-based sensing (SBP) is performed and the sensing initiator is the sensing receiver. First, an STA (SBP initiator) requests another STA (SBP responder, sensing initiator) to initiate a sensing session. The sensing initiator is the sensing receiver (Rx). In some embodiments, TB-like sensing can be performed using TF (I2R) and NDP (R2I). In some embodiments, non-TB-like sensing can be performed with: NDPA (I2R) and NDP (I2R) and NDP (R2I). Bidirectional sensing may be supported (i.e., both Tx and Rx), and sensing measurement reporting may be optional.

[0378] According to some embodiments, in the non-infrastructure mode, WLAN sensing is supported. For the WLAN sensing procedure in the non-infrastructure mode, the WLAN sensing step may be similar to at least one of trigger-based (TB) sensing, non-TB sensing, or other WLAN sensing steps.

[0379] In some embodiments, a first mode, flag, setting, bit combination, and / or field may be present in the sensing session / procedure setup frame and / or SBP setup frame to indicate (e.g., from the sensing initiator / SBP responder to the sensing responder) that both a minimum bandwidth (BW) requirement and a minimum number of spatial streams (SS) requirement apply. A second mode, flag, setting, bit combination, and / or field may be present to indicate that a minimum BW and a minimum SS do not apply. Instead, a minimum "effective bandwidth" or a minimum "product of BW and SS" applies (e.g., from the sensing initiator / SBP responder to the sensing responder). For example, {BW=40 MHz, number of spatial streams=4}. In the first mode / flag / setting / bit combination / field, BW must be at least 40 MHz and SS must be at least 4. In a second mode / flag / setting / bit combination / field, the system may allow {BW=80 MHz, number of spatial streams=2} that would otherwise fail the SS requirement, or {BW=20 MHz, number of spatial streams=8} or {BW=20 MHz, number of spatial streams=9} that would otherwise fail the BW requirement. Alternatively, if {BW=40 MHz, SS=3}, the system may allow {BW=20 MHz, SS=6} or {BW=80 MHz, SS=2} that would otherwise fail the BW or SS requirement.

[0380] In some embodiments, a mode / flag / setting / bit combination / field may be present in the sensing session / procedure setup frame and / or SBP setup frame to indicate a priority for maintaining the sounding frequency over the BW. For example, a STA may normally transmit a sounding signal at a specific BW (e.g., 80 MHz) and a specific sounding frequency (e.g., 100 Hz). However, in some situations (e.g., data traffic congestion or high interference), the sounding frequency and BW cannot be maintained simultaneously. In that case, maintaining the sounding frequency is prioritized over the BW. The priority may be applied by the sensing transmitter when transmitting the sounding signal to the sensing receiver. There may be another mode / flag / setting / bit combination / field in the sensing session / procedure setup frame and / or SBP setup frame to indicate a priority for maintaining the BW over the sounding frequency. In general, there may be a mode / flag / setting / bit combination / field to indicate a priority for maintaining a specific parameter of the sensing procedure / session or SBP over other parameters and / or other parameters. There may be a mode / flag / setting / bit combination / field indicating a first priority for maintaining a first parameter and a second priority for maintaining a second parameter (i.e., multiple parameters with corresponding priorities) over another and / or other parameter of the sensing procedure / session or SBP.

[0381] In some embodiments, after an SBP procedure is established / configured, the SBP configuration may be updated one or more times during the SBP procedure using the configuration field of the configuration frame. Possible updates may include adding / configuring / stopping / pausing / resumeing a new sensing responder, adding / configuring / pausing / resumeing a new sensing transmitter, adding / configuring / stopping / pausing / resumeing a new sensing receiver, stopping / pausing / resumein...

Claims

1. 1. A standardized wireless sensing method, comprising: In accordance with a standard wireless network protocol, in response to at least one of: (1) a first sensing measurement setup request message sent from a sensing initiator device to a first sensing responder device, requesting the first sensing responder device to function as a sensing receiver device; or (2) a second sensing measurement setup request message sent from the sensing initiator device to a second sensing responder device, requesting the second sensing responder device to function as a sensing transmitter device; the sensing receiver device receives the wireless sounding signal transmitted from the sensing transmitter device over a wireless channel of the venue using a receiving antenna and associated receiving circuitry; the sensing receiver device performs wireless sensing measurements to generate sensing measurement results based on the received wireless sounding signals; The sensing receiver device provides a report including: (a) the sensing measurement results; and (b) information on modem parameters used for processing the received wireless sounding signal. Standardized wireless sensing methods.

2. and locally reporting the sensing measurement results from a physical (PHY) layer or a medium access control (MAC) layer of the sensing receiver device to an upper layer of the sensing receiver device based on the standard wireless network protocol. The standardized wireless sensing method of claim 1 .

3. and reporting information about the modem parameters from a PHY layer or a MAC layer of the sensing receiver device to an upper layer of the sensing receiver device based on the standard wireless network protocol. The standardized wireless sensing method of claim 2 .

4. (a) executing a sensing task to detect an object present in the venue in the upper layer of the sensing receiver device based on the sensing measurement results and (b) information on modem parameters used for processing the received wireless sounding signal. The standardized wireless sensing method according to claim 3 .

5. providing the report to the sensing initiator device by the sensing receiver device wirelessly transmitting the report in a report frame to the sensing initiator device based on the standard wireless network protocol; the sensing measurement result is provided by the sensing receiver device in a first field of the report frame; and wherein information of modem parameters used for processing the received wireless sounding signal is provided by the sensing receiver device in a second field of the report frame. The standardized wireless sensing method of claim 1 .

6. and (b) the sensing initiator device executing a sensing task to detect an object present in the venue based on (a) the sensing measurement result and (b) information on modem parameters used for processing the received wireless sounding signal. The standardized wireless sensing method according to claim 5 .

7. Based on the standard wireless network protocol, the proxy initiator device sends to the sensing initiator device: requesting a sensing responder device to function as the sensing transmitter device to transmit the wireless sounding signal; a sensing responder device, said sensing receiver device including: receiving the radio sounding signal; performing the wireless sensing measurements to generate the sensing measurement results based on the received wireless sounding signals; reporting the sensing measurement results to the sensing initiator device; requesting the sensing receiver device to function as the sensing receiver device; and and the sensing initiator device provides (a) the sensing measurement results and (b) information of modem parameters used for processing the received wireless sounding signals to the proxy initiator device by wirelessly transmitting the results in a second report frame from the sensing initiator device to the proxy initiator device based on the standard wireless network protocol; the sensing measurement result is provided by the sensing initiator device in a third field of the second report frame; The information of the modem parameters used for processing the wireless sounding signal is provided by the sensing initiator device in a fourth field of the second report frame. and further including The standardized wireless sensing method according to claim 5 .

8. and (b) the proxy initiator device executing a sensing task to obtain a sensing task result based on (a) the sensing measurement result and (b) information about modem parameters used for processing the received wireless sounding signal. The standardized wireless sensing method of claim 7.

9. According to the standard wireless network protocol, the proxy initiator device sends a proxy sensing request message to the sensing initiator device, requesting the sensing initiator device to perform wireless sensing on behalf of the proxy initiator device; the sensing initiator device is requested to perform the wireless sensing by initiating a sensing session with a plurality of sensing responder devices, the sensing responder devices including a sensing device selected to perform wireless sensing measurements to obtain sensing measurement results based on wireless sounding signals communicated between the plurality of sensing responder devices and the sensing initiator device; the selected sensing device is requested by the proxy initiator device in the proxy sensing request message to be either the sensing receiver device or the sensing transmitter device. The standardized wireless sensing method of claim 7.

10. Based on the standard wireless network protocol, the proxy initiator device specifies an identity (ID) of the selected sensing device in a first field of the proxy sensing request message; and wherein the ID of the selected sensing device comprises one of a MAC address, a network address, an Internet Protocol (IP) address, an ID in a network associated with a proxy responder device, a device name, a device product name, a host name, a vendor class ID, a UUID, or a GUID.

10. The standardized wireless sensing method of claim 9.

11. The information of the sensing measurement result is a non-negative real number. The standardized wireless sensing method of claim 7.

12. The modem parameters used for processing the received radio sounding signal include one or more of a gain setting, an RF filter setting, an RF front-end switch setting, a DC offset setting, an IQ compensation setting, a digital DC correction setting, a digital gain setting, and / or a digital filtering setting. The standardized wireless sensing method of claim 11.

13. The sensing measurement result includes one of channel information (CI), channel state information (CSI), channel impulse response (CIR), and channel frequency response (CFR); The standard wireless network protocol is at least one of a wireless LAN (WLAN) standard protocol, a mobile communication standard protocol, a WLAN standard, a Wi-Fi standard, an IEEE 802 standard, an IEEE 802.11 standard, or an IEEE 802.11bf standard. The standardized wireless sensing method of claim 1 .

14. 1. A standardized wireless sensing system, comprising: a sensing transmitter device configured to transmit wireless sounding signals over a wireless channel to a sensing receiver device within the venue based on a standard wireless network protocol; The sensing receiver device, receiving the wireless sounding signal from the sensing transmitter device using a receive antenna and associated receive circuitry in accordance with the standard wireless network protocol; performing wireless sensing measurements based on the received wireless sounding signals to generate sensing measurements based on the standard wireless network protocol; the sensing receiver device configured to provide a report based on the standard wireless network protocol, the report including (a) the sensing measurement results, and (b) information on modem parameters used for processing the received wireless sounding signal. Standardized wireless sensing system.

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