Systems and methods for Wi-Fi sensing using uplink orthogonal frequency division multiple access (UL-OFDMA)

Abstract

A system and method for Wi-Fi sensing using UL-OFDMA is provided. The Wi-Fi sensing system includes a sensing device and a sensing transmitter configured to communicate via radio frequency signals. First, a first channel resource is allocated to a first expected transmission from the sensing transmitter, and a first sensing trigger message is transmitted to trigger a first series of sensing transmissions from the sensing transmitter. Further, the first series of sensing transmissions is received, and a first series of sensing measurements is generated. Then, an identification of a feature of interest is obtained, and a selection of a sensing transmitter is determined. A second channel resource is allocated to a second expected transmission from the selection of sensing transmitter. A second sensing trigger message is provided to trigger a second series of sensing transmissions from the selection of sensing transmitter. A series of sensing transmissions is received, and a second series of sensing measurements is generated based on the second series of sensing transmissions.

Description

[Technical field]

[0001] The present disclosure relates generally to systems and methods for Wi-Fi sensing, and more particularly to configuring a Wi-Fi system to perform Wi-Fi sensing using uplink orthogonal frequency division multiple access (UL-OFDMA). [Background technology]

[0002] Motion detection systems are used, for example, to detect the movement of objects in a room or an outdoor area. In some exemplary motion detection systems, infrared or optical sensors are used to detect the movement of objects in the field of view of the sensor. Motion detection systems are used in security systems, automatic control systems, and other types of systems. Wi-Fi sensing systems are one of the most recent additions to motion detection systems. A Wi-Fi sensing system can be a network of Wi-Fi enabled devices that can be part of an IEEE 802.11 network. In one example, a Wi-Fi sensing system can be configured to detect features of interest in a sensing space. A sensing space may refer to any physical space in which a Wi-Fi sensing system can operate, such as a residence, a workplace, a shopping mall, a sports hall or sports stadium, a garden, or any other physical space. Features of interest include object movement and motion tracking, presence detection, intrusion detection, gesture recognition, fall detection, respiration rate detection, and other applications. Aspects of the embodiments presented herein provide for improving Wi-Fi sensing systems. Summary of the Invention

[0003] The present disclosure relates generally to systems and methods for Wi-Fi sensing, and more particularly to configuring a Wi-Fi system to perform Wi-Fi sensing using uplink orthogonal frequency division multiple access (UL-OFDMA).

[0004] A system and method for Wi-Fi sensing is provided. In an exemplary embodiment, a method for Wi-Fi sensing is described. The method is performed by a sensing receiver comprising a transmitting antenna, a receiving antenna, and at least one processor configured to execute instructions. The method includes allocating, by at least one processor, first channel resources to first expected transmissions from a first plurality of sensing transmitters, where each of the first plurality of sensing transmitters is allocated a first respective portion of the first channel resources; generating, by the at least one processor, a series of sensing measurements based on the series of sensing transmissions; obtaining an identification of a feature of interest according to the series of sensing measurements; and allocating, by the at least one processor, second channel resources to a second plurality of sensing transmitters according to the identification of the feature of interest, where each of the second plurality of sensing transmitters is allocated a second respective portion of the second channel resources, where the second plurality of sensing transmitters is a subset of the first plurality of sensing transmitters, and where at least one second respective portion of the second channel resources is greater than a corresponding first respective portion of the first channel resources.

[0005] In some implementations, the method further includes transmitting, via a transmit antenna, a sensing sounding trigger frame configured to trigger a sequence of sensing transmissions from a first plurality of sensing transmitters, and receiving, via a receive antenna, the sequence of sensing transmissions transmitted in response to the sensing sounding trigger frame, where the sensing sounding trigger frame is a scan type trigger frame including a resource allocation subfield corresponding to a requested transmission configuration and scan mode.

[0006] In some implementations, the first channel resource is included within the first transmission opportunity, the series of sensing transmissions is a first series of sensing transmissions corresponding to a scanning mode, the first channel resource is allocated to a first plurality of sensing transmitters according to the scanning mode, and the second channel resource is included within the second transmission opportunity, the second channel resource is allocated to a second plurality of sensing transmitters according to the detection mode.

[0007] In some implementations, the first channel resource and the second channel resource are included within the same transmission opportunity, the series of sensing transmissions is a first series of sensing transmissions corresponding to a scanning mode, the first channel resource is allocated to a first plurality of sensing transmitters according to the scanning mode, and the second channel resource is allocated to a second plurality of sensing transmitters according to the detection mode.

[0008] In some implementations, allocating the first channel resources includes allocating time and bandwidth within a transmission opportunity to the first plurality of sensing transmitters.

[0009] In some implementations, obtaining an identity of the feature of interest includes identifying, by at least one processor, the feature of interest in response to the series of sensing measurements.

[0010] In some implementations, obtaining an identification of the feature of interest includes transmitting the series of sensing measurements to a sensing algorithm device and receiving, by at least one processor, the identification of the feature of interest from the sensing algorithm device.

[0011] In some implementations, allocating the second channel resources includes selecting a second plurality of sensing transmitters based on proximity to the feature of interest.

[0012] In some implementations, the series of sensing measurements is a first series of sensing measurements and the series of sensing transmissions is the first series of sensing transmissions, and the method further includes generating a second series of sensing measurements having a higher resolution than the first series of sensing measurements based on the second series of sensing transmissions.

[0013] In some implementations, the features of interest include a first feature of interest and a second feature of interest, and allocating the second channel resource based on identification information of the features of interest includes determining a first selection of sensing transmitters according to identification information of the first feature of interest and determining a second selection of sensing transmitters according to identification information of the second feature of interest, wherein the first selection of sensing transmitters and the second selection of sensing transmitters constitute a second plurality of sensing transmitters.

[0014] In some implementations, the first channel resources are included within the first transmission opportunity, and the series of sensing transmissions is a first series of sensing transmissions corresponding to a scan mode, the second channel resources are included within the second transmission opportunity, and the second sensing sounding trigger frame includes a hybrid type trigger frame, which is configured to trigger a first second series of sensing transmissions corresponding to the scan mode from a first group of sensing transmitters and to trigger a second second series of sensing transmissions corresponding to the hybrid mode from a second group of sensing transmitters, and a first portion of the second channel resources are allocated to a sensing transmission of the first second series of sensing transmissions received in response to the hybrid type trigger frame, and a second portion of the second channel resources are allocated to a sensing transmission of the second second series of sensing transmissions received in response to the hybrid type trigger frame.

[0015] In some implementations, the sensing sounding trigger frame is a first sensing sounding trigger frame, and the at least one processor is further configured to transmit a second sensing sounding trigger frame configured to trigger a first group of second sensing transmissions from a first group of sensing transmitters from the second plurality of sensing transmitters and to trigger a second group of sensing transmissions from a second group of sensing transmitters from the second plurality of sensing transmitters.

[0016] In some implementations, the method further includes transmitting, via the transmit antenna, a sensing sounding trigger frame configured to trigger a sequence of sensing transmissions from the first plurality of sensing transmitters, and receiving, via the receive antenna, the sequence of sensing transmissions transmitted in response to the sensing sounding trigger frame, where transmitting the sensing sounding trigger frame includes transmitting a sensing sounding trigger frame configured to trigger a first group of sensing transmissions from a first group of sensing transmitters from the first plurality of sensing transmitters and to trigger a second group of sensing transmissions from a second group of sensing transmitters from the first plurality of sensing transmitters.

[0017] In a further implementation, a system configured for Wi-Fi sensing is provided. The system comprises a sensing receiver including a transmitting antenna, a receiving antenna, and at least one processor, the at least one processor being configured to execute instructions for: allocating, by the at least one processor, first channel resources to first expected transmissions from a first plurality of sensing transmitters, each of the first plurality of sensing transmitters being allocated a first respective portion of the first channel resources; generating, by the at least one processor, a series of sensing measurements based on the series of sensing transmissions; obtaining an identification of a feature of interest according to the series of sensing measurements; and allocating, by the at least one processor, second channel resources to a second plurality of sensing transmitters according to the identification of the feature of interest, each of the second plurality of sensing transmitters being allocated a second respective portion of the second channel resources, the second plurality of sensing transmitters being a subset of the first plurality of sensing transmitters, and at least one second respective portion of the second channel resources being greater than a corresponding first respective portion of the first channel resources.

[0018] Other aspects and advantages of the present disclosure will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, which illustrate, by way of example, the principles of the disclosure. [Brief description of the drawings]

[0019] The above and other objects, aspects, features, and advantages of the present disclosure will become more apparent and be better understood by referring to the following description taken in conjunction with the accompanying drawings.

[0020] [Figure 1] FIG. 1 illustrates an example wireless communication system. [Figure 2A-2B] FIG. 2 illustrates exemplary wireless signals communicated between wireless communication devices. [Figure 3A-3B]2C is a plot illustrating an example of a channel response calculated from a wireless signal communicated between the wireless communication devices of FIGS. 2A and 2B. [Figure 4A-4B] 1A-1C illustrate example channel responses associated with the movement of objects in distinct regions of space. [Fig. 4C-4D] 4C is a plot illustrating the example channel responses of FIGS. 4A and 4B overlaid on an example channel response associated with no motion occurring in space. [Diagram 5] 1 depicts an implementation of some of the architectures of an implementation of a system for Wi-Fi sensing according to some embodiments. [Figure 6] 1 illustrates an uplink orthogonal frequency division multiple access (OFDMA) transmission procedure and trigger frame format according to some embodiments. [Figure 7A-7G] 1 illustrates a hierarchy of fields within a trigger frame according to some embodiments. [Figure 8] 1 depicts a representation of allowable allocations of resource units (RUs) in a 20 MHz channel, according to some embodiments. [Figure 9] 1 depicts a representation of allowable allocations of RUs in a 40 MHz channel, according to some embodiments. [Figure 10] 1 depicts a representation of allowable allocations of RUs in an 80 MHz channel, according to some embodiments. [Figure 11] 1 illustrates a state transition diagram for a sensing device, according to some embodiments. [Fig. 12A-12H] 13 illustrates a hierarchy of fields in a UL-OFDMA sensing trigger message according to some embodiments. [Figure 13] 1 depicts an example UL-OFDMA based sensing transmission transaction in accordance with some embodiments. [Figure 14] 1 illustrates an example multi-user (MU) cascaded sequence sensing transmission transaction in accordance with some embodiments. [Figure 15]13 depicts an exemplary MU cascade sequence sensing transmission transaction for scanning a large-scale network, according to some embodiments. [Figure 16] 13 depicts an example MU cascade sequence sensing transmission transaction for detecting multiple features of interest, according to some embodiments. [Figure 17] 13 illustrates an example MU cascade sequence sensing transmission transaction used to detect features of interest while maintaining a full network scan, according to some embodiments. [Figure 18] 1 depicts an example MU cascade sequence sensing transmission transaction for detecting features of interest using high bandwidth sensing transmission, according to some embodiments. [Figures 19A-19C] 1 depicts a flowchart for generating sensing measurements based on features of interest according to some embodiments. [Figures 20A-20D] 1 depicts a flowchart for generating sensing measurements based on multiple features of interest, according to some embodiments. [Figure 21] 1 depicts a flowchart for identifying features of interest according to some embodiments. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0021] A Wi-Fi sensing system (also referred to as a wireless sensing system) can measure the environment by transmitting a signal to a remote device and analyzing the response received from the remote device. A Wi-Fi sensing system can perform repeated measurements to analyze the environment and its changes. A Wi-Fi sensing system benefits from having a Medium Access Control (MAC) layer entity that can work with existing communication components and can be used to coordinate airtime resource usage among multiple devices based on a defined protocol.

[0022] One of the relevant standardization goals of Wi-Fi sensing systems is to reduce additional overhead on existing Wi-Fi networks so that overlaying Wi-Fi sensing capabilities on 802.11 networks does not impair the communication capabilities of the network. Currently, there is no known MAC protocol specifically defined for sensing in Wi-Fi sensing systems. One aspect of sensing in Wi-Fi sensing systems is the request for sensing transmissions from remote devices. Improvements to the MAC layer to enable the request for sensing transmissions from remote devices with characteristics optimized to enable the Wi-Fi sensing agent to detect presence, location, and motion can have a significant impact on existing system performance. In particular, a request or request for a remote device transmission (or sensing transmission) optimized for sensing can affect the uplink scheduler of the remote device. There are existing mechanisms for requesting or requesting a remote device to transmit a sensing transmission. However, such mechanisms were designed for different purposes. As a result, these mechanisms are not efficient, do not provide flexibility in control, and are not universally consistent between different vendors' implementations. Additionally, a channel sounding protocol may be considered to support Wi-Fi sensing, however, such functionality to support Wi-Fi sensing is not possible since the channel sounding protocol is currently not flexible.

[0023] Protocols for Wi-Fi systems are designed with decisions made based on data transfer mechanisms versus sensing requirements. As a result, Wi-Fi sensing aspects are often not developed within typical Wi-Fi systems. With regard to antenna beamforming in Wi-Fi systems, digital signal processing directs high antenna gain beams toward transmitters or receivers for optimal data transfer purposes, but the resulting antenna patterns may not support or enhance sensing requirements.

[0024] In some aspects of what is described herein, the wireless sensing system may be used for various wireless sensing applications by processing wireless signals (e.g., radio frequency signals) transmitted through space between wireless communication devices. Exemplary wireless sensing applications include motion detection, which may include detection of object movement in space, motion tracking, respiration detection, respiration monitoring, presence detection, gesture detection, gesture recognition, human detection (moving human detection and stationary human detection), human tracking, fall detection, speed estimation, intrusion detection, walking detection, step counting, respiration rate detection, apnea estimation, posture change detection, activity recognition, gait rate classification, gesture decoding, sign language recognition, hand tracking, heart rate estimation, respiration rate estimation, room occupancy detection, human dynamics monitoring, and other types of motion detection applications. Other examples of wireless sensing applications include object recognition, speech recognition, keystroke detection and recognition, tamper detection, touch detection, attack detection, user authentication, driver fatigue detection, traffic monitoring, smoking detection, school violence detection, human counting, human recognition, bicycle localization, human cue estimation, Wi-Fi imaging, and other types of wireless sensing applications. For example, the wireless sensing system may operate as a motion detection system to detect the presence and location of motion based on Wi-Fi signals or other types of wireless signals. As described in more detail below, the wireless sensing system may be configured to control measurement rates, wireless connections, and device participation, for example, to improve system operation or achieve other technical advantages. The system improvements and technical advantages achieved when the wireless sensing system is used for motion detection are also achieved in examples where the wireless sensing system is used for another type of wireless sensing application.

[0025] In some exemplary wireless sensing systems, the wireless signal includes components (e.g., a synchronization preamble in a Wi-Fi PHY frame, or another type of component) that the wireless device can use to estimate the channel response or other channel information, and the wireless sensing system can detect motion (or another characteristic depending on the wireless sensing application) by analyzing changes in the collected channel information over time. In some examples, the wireless sensing system can operate like a bistatic radar system, where a Wi-Fi access point (AP) plays the role of a receiver and each Wi-Fi device (station or node or peer) connected to the AP plays the role of a transmitter. The wireless sensing system can trigger the connected devices to generate transmissions and generate channel response measurements at the receiver devices. This triggering process can be repeated periodically to obtain a series of time-varying measurements. The wireless sensing algorithm can then receive as input the time series of generated channel response measurements (e.g., calculated by the Wi-Fi receiver) and can then make a decision through a correlation or filtering process (e.g., determine whether there is motion or no motion in the environment represented by the channel response, e.g., based on changes or patterns in the channel estimates). In examples where a wireless sensing system detects motion, it may also be possible to identify the location of the motion within the environment based on motion detection results among multiple wireless devices.

[0026] Thus, wireless signals received at each of the wireless communication devices in a wireless communication network may be analyzed to determine channel information for various communication links (between respective pairs of wireless communication devices) in the network. The channel information may represent a physical medium that applies a transfer function to the wireless signals traversing the space. In some cases, the channel information includes a channel response. The channel response may characterize a physical communication path, e.g., representing the combined effects of scattering, fading, and power attenuation in the space between a transmitter and a receiver. In some cases, the channel information includes beamforming state information (e.g., feedback matrix, steering matrix, channel state information (CSI), etc.) provided by a beamforming system. Beamforming is a signal processing technique often used in multi-antenna (multiple-input / multiple-output (MIMO)) wireless systems for directional signal transmission or reception. Beamforming may be achieved by operating elements in an antenna array such that signals at certain angles experience constructive interference and other signals experience destructive interference.

[0027] The channel information for each of the communication links may be analyzed (e.g., by a hub device or other device in the wireless communication network, or a remote device communicatively coupled to the network) to, for example, detect whether motion has occurred within the space, determine the relative location of the detected motion, or both. In some aspects, the channel information for each of the communication links may be analyzed to detect, for example, if no motion is detected within the space, whether an object is present or absent.

[0028] In some cases, the wireless sensing system may control the node measurement rate. For example, a Wi-Fi motion system may configure a variable measurement rate (e.g., channel estimation / environment measurement / sampling rate) based on criteria provided by the current wireless sensing application (e.g., motion detection). In some implementations, for example, if no motion is present or detected for a period of time, the wireless sensing system may reduce the rate at which the environment is measured so that connected devices are triggered less frequently. In some implementations, for example, when motion is present, the wireless sensing system may increase the trigger rate to generate a time series of measurements with finer time resolution. Controlling the variable measurement rate may enable energy savings (through device triggering), reduce processing (less data to correlate or filter), and improve resolution during a specified time.

[0029] In some cases, the wireless sensing system may implement band steering or client steering of nodes across a wireless network, for example, in a Wi-Fi multi-AP or extended service set (ESS) topology, multiple cooperating wireless access points (APs) each occupy a different frequency band and provide a basic service set (BSS) that may enable devices to transparently move from one participating AP to another (e.g., mesh). For example, in a home mesh network, a Wi-Fi device may connect to any of the APs, but typically selects the one with good signal strength. The coverage footprints of mesh APs are generally overlapping, often placing each device within range or more than one AP. If an AP supports multi-band (e.g., 2.4 GHz and 5 GHz), the wireless sensing system may instruct the device to remain connected to the same physical AP, but to use different frequency bands to obtain more diverse information to help improve the accuracy or results of wireless sensing algorithms (e.g., motion detection algorithms). In some implementations, the wireless sensing system may change the device from being connected to one mesh AP to being connected to another mesh AP. Such device steering can be performed, for example, during wireless sensing (e.g., motion detection) based on criteria detected in a particular area to improve detection coverage or to better localize motion within the area.

[0030] In some cases, beamforming may be performed between wireless communication devices based on some knowledge of the communication channel (e.g., through feedback properties generated by the receiver), which may be used to generate one or more steering properties (e.g., steering matrices) that are applied by the transmitter device to shape the transmission beam / signal in one or more specific directions. Thus, changes in the steering or feedback properties used in the beamforming process are indicative of changes that may be caused by a moving object in the space accessed by the wireless communication system. For example, movement may be detected by a substantial change in the communication channel, as indicated by, for example, the channel response, or steering or feedback properties, or any combination thereof, over a period of time.

[0031] In some implementations, for example, a steering matrix may be generated in a transmitter device (beamformer) based on a feedback matrix provided by a receiver device (beamformee) based on channel sounding. Because the steering matrix and feedback matrix are related to the propagation characteristics of the channel, these matrices change as an object moves in the channel. Thus, changes in channel characteristics are reflected in these matrices, and by analyzing the matrices, motion can be detected and different characteristics of the detected motion can be determined. In some implementations, a spatial map may be generated based on one or more beamforming matrices. The spatial map may indicate a general direction of an object in space relative to the wireless communication device. In some cases, many beamforming matrices (e.g., feedback matrices or steering matrices) may be generated to represent multiple directions in which an object may be located relative to the wireless communication device. These many beamforming matrices may be used to generate a spatial map. The spatial map may be used to detect the presence of motion in space or to detect the location of the detected motion.

[0032] In some cases, the motion detection system may control a variable device measurement rate in the motion detection process. For example, a feedback control system for a multi-node wireless motion detection system may adaptively change the sample rate based on environmental conditions. In some cases, such control may improve the operation of the motion detection system or provide other technical advantages. For example, the measurement rate may be controlled in a manner that optimizes or otherwise improves airtime usage versus detection capability suitable for a wide range of different environments and different motion detection applications. The measurement rate may be controlled in a manner that reduces redundant measurement data processed, thereby reducing processor load / power requirements. In some cases, the measurement rate is controlled in a manner that is adaptive, e.g., adaptive samples may be controlled individually for each participating device. The adaptive sample rate may be used in conjunction with tuning control loops for different use cases or device characteristics.

[0033] In some cases, the wireless sensing system may allow devices to dynamically indicate and communicate their wireless sensing capabilities or willingness to the wireless sensing system. For example, a device may not want to be periodically interrupted or triggered to transmit wireless signals that enable an AP to generate channel measurements. For example, if a device is asleep, waking the device frequently to transmit or receive wireless sensing signals may consume resources (e.g., drain a cell phone battery faster). These and other events may cause a device to be willing or unwilling to participate in the operation of the wireless sensing system. In some cases, a cell phone running on its battery may not want to participate, but may be willing to participate when the cell phone is plugged into a charger. Thus, if the cell phone is unplugged, it may indicate to the wireless sensing system to exclude the cell phone from participating, whereas if the cell phone is plugged in, it may indicate to the wireless sensing system to include the cell phone in the operation of the wireless sensing system. In some cases, if a device is under load (e.g., a device streaming audio or video) or is in the middle of performing a primary function, the device may not want to participate; if the load on that same device is reduced and participating would not interfere with the primary function, the device can indicate to the wireless sensing system that it is willing to participate.

[0034] An exemplary wireless sensing system is described below in the context of motion detection (detection of object movement in space, motion tracking, respiration detection, respiration monitoring, presence detection, gesture detection, gesture recognition, human detection (moving human detection and stationary human detection), human tracking, fall detection, speed estimation, intrusion detection, walking detection, step counting, respiration rate detection, apnea estimation, posture change detection, activity recognition, gait rate classification, gesture decoding, sign language recognition, hand tracking, heart rate estimation, respiration rate estimation, room occupancy detection, human dynamics monitoring, and other types of motion detection applications). However, the operation, system improvements, and technical advantages achieved when the wireless sensing system is operating as a motion detection system are also applicable in examples where the wireless sensing system is used for another type of wireless sensing application.

[0035] As disclosed in the embodiments herein, a wireless local area network (WLAN) sensing procedure allows a station (STA) to perform WLAN sensing. The WLAN sensing may include a WLAN sensing session. For example, a WLAN sensing procedure, a WLAN sensing, and a WLAN sensing session may be referred to as a wireless sensing procedure, a wireless sensing, and a wireless sensing session, a Wi-Fi sensing procedure, a Wi-Fi sensing, and a Wi-Fi sensing session, or a sensing procedure, a sensing, and a sensing session.

[0036] WLAN sensing is a service that allows a STA to obtain sensing measurements of a channel between two or more STAs and / or a channel between a receiving antenna and a transmitting antenna of a STA or an access point (AP). A WLAN 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.

[0037] In the examples disclosed herein, the sensing session setup and the sensing measurement setup may be referred to as sensing configuration and may be accomplished by a sensing configuration message and may be confirmed by a sensing configuration response message. A sensing measurement instance may be an individual sensing measurement and may be derived from a sensing transmission. For example, the sensing configuration message may be referred to as a sensing measurement setup request and the sensing configuration response message may be referred to as a sensing measurement setup response.

[0038] A WLAN sensing procedure may include multiple sensing measurement instances, eg, which may be referred to as a measurement campaign.

[0039] A sensing initiator may refer to a STA or AP that initiates a WLAN sensing procedure. A sensing responder may refer to a STA or AP that participates in a WLAN sensing procedure initiated by a sensing initiator. A sensing transmitter may refer to a STA or AP that transmits a physical layer protocol data unit (PPDU) used for sensing measurements in a WLAN sensing procedure. A sensing receiver may refer to a STA or AP that receives a PPDU transmitted by a sensing transmitter and performs sensing measurements in a WLAN sensing procedure.

[0040] For example, a PPDU used for sensing measurements may be referred to as a sensing transmission.

[0041] A STA acting as a sensing initiator can participate in a sensing measurement instance as a sensing transmitter, a sensing receiver, both a sensing transmitter and a sensing receiver, or neither a sensing transmitter nor a sensing receiver. A STA acting as a sensing responder can participate in a sensing measurement instance as a sensing transmitter, a sensing receiver, and both a sensing transmitter and a sensing receiver.

[0042] In one example, the sensing initiator can be considered to control the WLAN sensing procedure or measurement campaign. The role of the sensing initiator may be taken over by the sensing device, a remote device, or a separate device that contains the sensing algorithm (e.g., a sensing algorithm manager).

[0043] For example, a sensing transmitter may be referred to as a remote device and a sensing receiver may be referred to as a sensing device. In other examples, a sensing initiator may be a function of a sensing device or a remote device, and a sensing responder may be a function of a sensing device or a remote device.

[0044] IEEE P802.11-REVmd / D5.0 considers an STA to be a physical (PHY) and medium access controller (MAC) entity capable of supporting the features defined by the standard. A device that includes an STA may be referred to as a Wi-Fi device. A Wi-Fi device that manages a basic service set (BSS) (as defined by IEEE P802.11-REVmd / D5.0) may be referred to as an AP STA. A Wi-Fi device that is a client node in a BSS may be referred to as a non-AP STA. In some examples, an AP STA may be referred to as an AP and a non-AP STA may be referred to as an STA.

[0045] In various embodiments of the present disclosure, non-limiting definitions of one or more terms used herein are provided below.

[0046] The term "measurement campaign" may refer to a series of bidirectional sensing transmissions between a sensing device (generally known as a wireless access point, Wi-Fi access point, access point, sensing initiator, or sensing receiver) and one or more remote devices (generally known as Wi-Fi devices, sensing responders, or sensing transmitters) that allows a series of sensing measurements to be computed.

[0047] The term "Channel State Information (CSI)" may refer to characteristics of a communication channel that are known or measured by channel estimation techniques.

[0048] The term "training field" may refer to a sequence of bits transmitted by a sensing device that is known by a remote device and used upon reception to measure the channel for purposes other than demodulating the data portion of a containing PHY layer protocol data unit (PPDU). In one example, the training field is included within the preamble of the transmitted PPDU. In some examples, future training fields may be defined within the preamble structure (cascading training fields with legacy support) or may replace existing training fields (non-legacy support).

[0049] The term "uplink orthogonal frequency division multiple access (UL-OFDMA) sensing trigger message" may refer to a message from a sensing device to one or more remote devices to generate a sensing transmission in a single transmission opportunity (TXOP) using UL-OFDMA. The UL-OFDMA sensing trigger message includes data that instructs one or more remote devices how to form a sensing transmission in response to the UL-OFDMA sensing trigger message.

[0050] A "multi-user (MU) cascade sequence" may refer to a sequence of frames exchanged between a sensing device and one or more remote devices in which the sensing device triggers multiple transmissions from one or more remote devices within a single TXOP.

[0051] The term "Transmission Opportunity (TXOP)" may refer to a negotiated time interval during which a sensing device or one or more remote devices may have the right to initiate a frame exchange on the wireless medium. A TXOP is a feature of IEEE 802.11 networks that allows contention-free access to the channel for the duration of the TXOP. In some cases, a device that is allocated a TXOP may transmit as many frames as can be accommodated during the TXOP according to the constraints for which the TXOP was allocated. TXOPs are negotiated and allocated by a defined process that determines that the channel is available and can accommodate the TXOP. A further feature of IEEE 802.11 allows a TXOP to be shared among multiple devices in the uplink direction (e.g., from one or more remote devices to the sensing device) using UL-OFDMA.

[0052] The term "Quality of Service (QoS) Access Category" may refer to an identifier of a frame that classifies the transmission priority that the frame requires. In one example, four QoS access categories are defined: AC_VI: Video, AC_VO: Voice, AC_BE: Best Effort, and AC_BK: Background. Furthermore, each QoS access category may have different transmission opportunity parameters defined for it.

[0053] The term "resource unit (RU)" can refer to an allocation of orthogonal frequency division multiplexing (OFDM) channels that can be used to carry modulated signals. A RU can contain a variable number of carriers depending on the mode of the modem.

[0054] The term "transmit parameters" may refer to a set of IEEE 802.11 PHY transmitter configuration parameters that are defined as part of a transmit vector (TXVECTOR) corresponding to a particular PHY and are configurable for each PPDU transmission.

[0055] The term "requested transmission configuration" may refer to the requested transmission parameters of the remote device to be used when sending a sensing transmission. In one example, the requested transmission configuration may include one or more components, such as IEEE 802.11 Elements (IEEE 802.11md / D5.0, §9.4.2).

[0056] The term "sensing configuration message" may refer to a configuration message that may be used to pre-configure sensing transmissions from a remote device to a sensing device, for example, for a measurement campaign.

[0057] The term "sensing configuration response message" may refer to a response message to a sensing configuration message that indicates which configuration options are supported by the remote device, e.g., the transmission capabilities of the remote device. In one example, the sensing configuration response message may be transmitted from a remote device to a sensing device in response to a sensing configuration message.

[0058] The term "distributed transmission configuration" may refer to transmission parameters applied by a remote device to a sensing transmission. In one example, the distributed transmission configuration may include transmission parameters supported by the remote device.

[0059] A "feature of interest" may refer to an item or a condition of an item that is actively detected and / or identified by a sensing algorithm.

[0060] The term "measurement time jitter" may refer to the inaccuracy introduced when the measurement time of a sensing measurement is either inaccurate or unavailable.

[0061] The term "sensing trigger message" may refer to a message sent from a sensing device to a remote device to trigger one or more sensing transmissions that may be used to perform a sensing measurement. In an example, the term sensing trigger message may be referred to as a sensing sounding trigger message or a sensing sounding trigger frame.

[0062] The term "sensing transmission" may refer to any transmission made from a remote device to a sensing device that may be used to make a sensing measurement. In one example, a sensing transmission may be referred to as a wireless sensing signal or a wireless signal. In one example, a sensing transmission may be either a sensing response message or a sensing response NDP that includes one or more training fields used to make a sensing measurement.

[0063] The term "sensing response message" may refer to a message included in a sensing transmission from a remote device to a sensing device. In one example, a sensing transmission including a sensing response message may be used to perform a sensing measurement.

[0064] The term "sensing measurement" may refer to a measurement of a channel condition, e.g., a CSI measurement between a remote device and a sensing device derived from a sensing transmission. In one example, the sensing measurement may also be referred to as a channel response measurement.

[0065] The term "sensing algorithm" may refer to a computational algorithm that achieves a sensing goal. A sensing algorithm may be executed by a Wi-Fi sensing agent and may be executed on a sensing device or any other device in a Wi-Fi sensing system. In one example, a sensing algorithm may be required to perform a calculation (or a series of calculations) on sensing measurements to meet a sensing goal at a particular time.

[0066] The term "sensing goal" may refer to the goal of a sensing activity at a point in time. Sensing goals are not static and may change at any time. Sensing goals are determined by the Wi-Fi sensing agent. In one example, a sensing goal may require that sensing measurements of a particular type, a particular format, or a particular precision, resolution, or accuracy be available to a sensing algorithm.

[0067] The term "sensing space" may refer to any physical space in which a Wi-Fi sensing system may operate.

[0068] The term "steering matrix configuration" may refer to a matrix of complex values ​​that represent the real and complex phases required to precondition the antennas of a radio frequency (RF) transmit signal chain for each transmit signal. Application of steering matrix configurations (e.g., by a spatial mapper) enables beamforming and beamsteering.

[0069] The term "wireless local area network (WLAN) sensing session" may refer to a period of time during which objects in a physical space may be probed, detected, and / or characterized. In one example, during a WLAN sensing session, multiple devices participate, thereby contributing to the generation of sensing measurements.

[0070] In reading the following description of the various embodiments, the following description of the sections of this specification and their respective contents may be useful.

[0071] Section A describes wireless communication systems, wireless transmissions, and sensing measurements that may be useful in implementing the embodiments described herein.

[0072] Section B describes embodiments of systems and methods for Wi-Fi sensing. In particular, Section B describes a Wi-Fi system for implementing Wi-Fi sensing using uplink orthogonal frequency division multiple access (UL-OFDMA).

[0073] A. Wireless communication systems, wireless transmission, and sensing measurements 1 shows a wireless communication system 100. The wireless communication system 100 includes three wireless communication devices: a first wireless communication device 102A, a second wireless communication device 102B, and a third wireless communication device 102C. The wireless communication system 100 may include additional wireless communication devices and other components (e.g., additional wireless communication devices, one or more network servers, network routers, network switches, cables, or other communication links, etc.).

[0074] The wireless communication devices 102A, 102B, 102C can operate in a wireless network, for example, according to a wireless network communication protocol or another type of wireless standard. For example, the wireless network can be configured to operate as a wireless local area network (WLAN), a personal area network (PAN), a metropolitan area network (MAN), or another type of wireless network. Examples of WLANs include networks configured to operate according to one or more of the 802.11 family of standards developed by the IEEE (e.g., Wi-Fi networks), etc. Examples of PANs include networks that operate according to short-range communication standards (e.g., Bluetooth, Near Field Communication (NFC), ZigBee), millimeter wave communications, and others.

[0075] In some implementations, the wireless communication devices 102A, 102B, 102C may be configured to communicate over a cellular network, for example, according to a cellular network standard. Examples of cellular networks include networks configured according to 2G standards such as Global System for Mobile (GSM) and Enhanced Data rate for GSM Evolution (EDGE) or EGPRS, 3G standards such as Code Division Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Universal Mobile Telecommunications System (UMTS), Time Division Synchronous Code Division Multiple Access (TD-SCDMA), 4G standards such as Long-Term Evolution (LTE) and LTE-Advanced (LTE-A), 5G standards, and others.

[0076] In the example shown in FIG. 1, the wireless communication devices 102A, 102B, 102C may be or may include standard wireless network components. For example, the wireless communication devices 102A, 102B, 102C may be commercially available Wi-Fi access points or another type of wireless access point (WAP) that performs one or more operations described herein embedded as instructions (e.g., software or firmware) on the WAP's modem. In some cases, the wireless communication devices 102A, 102B, 102C may be nodes of a wireless mesh network, such as, for example, a commercially available mesh network system (e.g., Plume Wi-Fi, Google Wi-Fi, Qualcomm Wi-Fi SoN, etc.). In some cases, another type of standard or conventional Wi-Fi transmitter device may be used. In some cases, one or more of the wireless communication devices 102A, 102B, 102C may be implemented as a WAP in the mesh network, while other wireless communication devices 102A, 102B, 102C are implemented as leaf devices (e.g., mobile devices, smart devices, etc.) that access the mesh network through one of the WAPs. In some cases, one or more of the wireless communication devices 102A, 102B, 102C is a mobile device (e.g., a smartphone, a smart watch, a tablet, a laptop computer, etc.), a wireless-enabled device (e.g., a smart thermostat, a Wi-Fi enabled camera, a smart TV), or another type of device that communicates in a wireless network.

[0077] The wireless communication devices 102A, 102B, 102C may be implemented without a Wi-Fi component, e.g., other types of standard or non-standard wireless communications may be used for motion detection. In some cases, the wireless communication devices 102A, 102B, 102C may be or may be part of a dedicated motion detection system. For example, a dedicated motion detection system may include a hub device and one or more beacon devices (as remote sensor devices), and the wireless communication devices 102A, 102B, 102C may be either a hub device or a beacon device in the motion detection system.

[0078] 1, the wireless communication device 102C includes a modem 112, a processor 114, a memory 116, and a power unit 118, and any of the wireless communication devices 102A, 102B, 102C in the wireless communication system 100 may include the same, additional, or different components, and the components may be configured to operate as shown in FIG. 1 or in another manner. In some implementations, the modem 112, processor 114, memory 116, and power unit 118 of a wireless communication device are housed together in a common housing or other assembly. In some implementations, one or more of the components of a wireless communication device may be housed separately, for example, in a separate housing or other assembly.

[0079] The modem 112 can communicate (receive, transmit, or both) wireless signals. For example, the modem 112 can be configured to communicate radio frequency (RF) signals formatted according to a wireless communication standard (e.g., Wi-Fi or Bluetooth). The modem 112 can be implemented as the exemplary wireless network modem 112 shown in FIG. 1 or can be implemented otherwise, e.g., with other types of components or subsystems. In some implementations, the modem 112 includes a radio subsystem and a baseband subsystem. In some cases, the baseband subsystem and the radio subsystem can be implemented on a common chip or chipset, or they can be implemented in a card or another type of assembled device. The baseband subsystem can be coupled to the radio subsystem, e.g., by leads, pins, wires, or other types of connections.

[0080] In some cases, the radio subsystem in the modem 112 may include one or more antennas and radio frequency circuitry. The radio frequency circuitry may include, for example, circuitry for filtering, amplifying, or otherwise conditioning analog signals, circuitry for upconverting baseband signals to RF signals, circuitry for downconverting RF signals to baseband signals, etc. Such circuitry may include, for example, filters, amplifiers, mixers, local oscillators, etc. The radio subsystem may be configured to communicate radio frequency radio signals over a wireless communication channel. As an example, the radio subsystem may include a radio chip, an RF front end, and one or more antennas. The radio subsystem may include additional or different components. In some implementations, the radio subsystem may be or include radio electronics (e.g., RF front end, radio chip, or similar components) from a traditional modem, for example, a Wi-Fi modem, a pico base station modem, etc. In some implementations, the antenna includes multiple antennas.

[0081] In some cases, the baseband subsystem in the modem 112 may include digital electronics configured to process, for example, digital baseband data. As an example, the baseband subsystem may include a baseband chip. The baseband subsystem may include additional or different components. In some cases, the baseband subsystem may include a digital signal processor (DSP) device or another type of processor device. In some cases, the baseband system includes digital processing logic for operating the radio subsystem, communicating wireless network traffic via the radio subsystem, detecting motion based on motion detection signals received via the radio subsystem, or performing other types of processes. For example, the baseband subsystem may include one or more chips, chip sets, or other types of devices configured to encode signals, deliver the encoded signals to the radio subsystem for transmission, or identify and analyze encoded data in signals from the radio subsystem (e.g., by decoding the signals according to a wireless communication standard, by processing the signals according to a motion detection process, or otherwise).

[0082] In some cases, the radio subsystem in modem 112 receives baseband signals from the baseband subsystem, upconverts the baseband signals in frequency (radio frequency (RF) signals, and transmits the radio frequency signals wirelessly (e.g., through an antenna). In some cases, the radio subsystem in modem 112 receives radio frequency signals wirelessly (e.g., through an antenna), downconverts the radio frequency signals to baseband signals, and transmits the baseband signals to the baseband subsystem. Signals exchanged between the radio subsystem and the baseband subsystem may be digital signals or analog signals. In some examples, the baseband subsystem includes conversion circuitry (e.g., digital-to-analog converters, analog-to-digital converters) and exchanges analog signals with the radio subsystem. In some examples, the radio subsystem includes conversion circuitry (e.g., digital-to-analog converters, analog-to-digital converters) and exchanges digital signals with the baseband subsystem.

[0083] In some cases, the baseband subsystem of the modem 112 can communicate wireless network traffic (e.g., data packets) in a wireless communication network through the radio subsystem over one or more network traffic channels. The baseband subsystem of the modem 112 can also transmit or receive (or both) signals (e.g., motion search signals or motion detection signals) through the radio subsystem over a dedicated wireless communication channel. In some cases, the baseband subsystem generates a motion search signal for transmission, for example, to search a space for motion. In some cases, the baseband subsystem processes a received motion detection signal (a signal based on the motion search signal transmitted through the space), for example, to detect the motion of an object in the space.

[0084] The processor 114 may execute instructions, for example, to generate output data based on data input. The instructions may include programs, codes, scripts, or other types of data stored in memory. Additionally or alternatively, the instructions may be encoded as preprogrammed or reprogrammable logic circuits, logic gates, or other types of hardware or firmware components. The processor 114 may be or include a general-purpose microprocessor, as a dedicated coprocessor or another type of data processing device. In some cases, the processor 114 performs high-level operations of the wireless communication device 102C. For example, the processor 114 may be configured to execute or interpret software, scripts, programs, functions, executable files, or other instructions stored in the memory 116. In some implementations, the processor 114 may be included in the modem 112.

[0085] The memory 116 may include a computer-readable storage medium, such as a volatile memory device, a non-volatile memory device, or both. The memory 116 may include one or more read-only memory devices, random access memory devices, buffer memory devices, or a combination of these and other types of memory devices. In some cases, one or more components of the memory may be integrated with or otherwise associated with another component of the wireless communication device 102C. The memory 116 may store instructions executable by the processor 114. For example, the instructions may include instructions for time-aligning a signal using an interference buffer and a motion detection buffer, such as through one or more of the operations of the example processes described in any of Figures 11, 19A, 19B, 19C, 20A, 20B, 20C, 20D, and 21.

[0086] The power supply unit 118 provides power to other components of the wireless communication device 102C. For example, the other components may operate based on power provided by the power unit 118 through a voltage bus or other connection. In some implementations, the power unit 118 includes a battery or battery system, e.g., a rechargeable battery. In some implementations, the power unit 118 includes an adapter (e.g., an AC adapter) that receives an external power signal (from an external source) and converts the external power signal into an internal power signal conditioned for the components of the wireless communication device 102C. The power supply unit 118 may include other components or operate in another manner.

[0087] In the example shown in Figure 1, the wireless communication devices 102A, 102B transmit wireless signals (e.g., in accordance with a wireless network standard, a motion detection protocol, or other method). For example, the wireless communication devices 102A, 102B may broadcast wireless motion detection signals (e.g., reference signals, beacon signals, status signals, etc.) or may transmit wireless signals addressed to other devices (e.g., user equipment, client devices, servers, etc.), and the other devices (not shown) as well as the wireless communication device 102C may receive the wireless signals transmitted by the wireless communication devices 102A, 102B. In some cases, the wireless signals transmitted by the wireless communication devices 102A, 102B are repeated periodically, e.g., in accordance with a wireless communication standard or otherwise.

[0088] In the illustrated example, the wireless communication device 102C processes the wireless signals from the wireless communication devices 102A, 102B to detect motion of objects in a space accessed by the wireless signals, determine a location of the detected motion, or both. For example, the wireless communication device 102C may perform one or more operations of the example processes described below with respect to any of Figures 11, 19A, 19B, 19C, 20A, 20B, 20C, 20D, and 21, or another type of process for detecting motion or determining a location of the detected motion. The space accessed by the wireless signals may be, for example, an indoor or outdoor space that may include one or more fully or partially enclosed areas, unenclosed open areas, etc. The space may be within or may include a room, multiple rooms, a building, etc. In some cases, the wireless communication system 100 may be modified, for example, so that the wireless communication device 102C may transmit wireless signals and the wireless communication devices 102A, 102B may process the wireless signals from the wireless communication device 102C to detect motion or determine the location of detected motion.

[0089] The wireless signals used for motion detection may include, for example, beacon signals (e.g., Bluetooth beacons, Wi-Fi beacons, other wireless beacon signals), other standard signals generated for other purposes according to a wireless network standard, or non-standard signals (e.g., random signals, reference signals, etc.) generated for motion detection or other purposes. For example, motion detection may be performed by analyzing one or more training fields carried by the wireless signals, or by analyzing other data carried by the signals. In some examples, data is added or used for the explicit purpose of motion detection, or data that is nominally for another purpose is reused or used for another purpose for motion detection. In some examples, the wireless signals propagate through objects (e.g., walls) before or after interacting with a moving object, thereby allowing the movement of the moving object to be detected even without an optical line of sight between the moving object and the transmitting or receiving hardware. Based on the received signals, the wireless communication device 102C may generate motion detection data. In some cases, the wireless communication device 102C may communicate the motion detection data to another device or system, such as a security system, which may include a control center for monitoring movement within a space, such as a room, a building, an outdoor area, etc.

[0090] In some implementations, the wireless communication devices 102A, 102B may be modified to transmit a motion probing signal (which may include, for example, a reference signal, a beacon signal, or another signal used to probe the space for motion) on a wireless communication channel (e.g., a frequency channel or a coded channel) separate from the wireless network traffic signals. For example, the modulation applied to the payload of the motion probing signal and the type of data or data structure in the payload may be known by the wireless communication device 102C, which may reduce the amount of processing the wireless communication device 102C performs for motion sensing. The header may include additional information, such as, for example, an indication of whether motion has been detected by another device in the communication system 100, an indication of the modulation type, an identification of the device transmitting the signal, etc.

[0091] 1, the wireless communication system 100 is a wireless mesh network having wireless communication links between each of the wireless communication devices 102. In the illustrated example, the wireless communication link between the wireless communication device 102C and the wireless communication device 102A may be used to probe the motion detection field 110A, the wireless communication link between the wireless communication device 102C and the wireless communication device 102B may be used to probe the motion detection field 110B, and the wireless communication link between the wireless communication device 102A and the wireless communication device 102B may be used to probe the motion detection field 110C. In some cases, each wireless communication device 102 detects motion in the motion detection field 110 accessed by that device by processing a received signal based on a wireless signal transmitted by the wireless communication device 102 through the motion detection field 110. 1 moves in motion detection field 110A and motion detection field 110C, the wireless communication devices 102 can detect the motion based on signals they receive that are based on wireless signals transmitted through the respective motion detection fields 110. For example, wireless communication device 102A can detect the motion of person 106 in motion detection fields 110A, 110C, wireless communication device 102B can detect the motion of person 106 in motion detection field 110C, and wireless communication device 102C can detect the motion of person 106 in motion detection field 110A.

[0092] In some cases, the motion detection field 110 may include, for example, air, solid material, liquid, or another medium through which wireless electromagnetic signals may propagate. In the example shown in FIG. 1, the motion detection field 110A provides a wireless communication channel between the wireless communication device 102A and the wireless communication device 102C, the motion detection field 110B provides a wireless communication channel between the wireless communication device 102B and the wireless communication device 102C, and the motion detection field 110C provides a wireless communication channel between the wireless communication device 102A and the wireless communication device 102B. In some aspects of operation, wireless signals transmitted on a wireless communication channel (separate from or shared with a wireless communication channel for network traffic) are used to detect the movement of an object in space. The object may be any type of stationary or movable object, animate or inanimate. For example, the object may be a human (e.g., person 106 shown in FIG. 1), an animal, an inanimate object, or another device, apparatus, or assembly), an object that defines all or a portion of a boundary of a space (e.g., a wall, a door, a window, etc.), or another type of object. In some implementations, the motion information from the wireless communication devices may be analyzed to determine a location of the detected motion. For example, as described further below, one of the wireless communication devices 102 (or another device communicatively coupled to the wireless communication device 102) may determine that the detected motion is in the vicinity of a particular wireless communication device.

[0093] 2A and 2B are diagrams illustrating exemplary wireless signals communicated between wireless communication devices 204A, 204B, and 204C. The wireless communication devices 204A, 204B, and 204C may be, for example, wireless communication devices 102A, 102B, and 102C shown in FIG. 1, or other types of wireless communication devices. The wireless communication devices 204A, 204B, and 204C transmit wireless signals through a space 200. The space 200 may be fully or partially enclosed with one or more boundaries, or may be open. In one example, the space 200 may be a sensing space. The space 200 may be within or may include a room, multiple rooms, a building, an indoor area, an outdoor area, and the like. A first wall 202A, a second wall 202B, and a third wall 202C at least partially surround the space 200 in the illustrated example.

[0094] 2A and 2B, the wireless communication device 204A is operable to transmit a wireless signal repeatedly (e.g., periodically, intermittently, at scheduled, unscheduled, or random intervals, etc.). The wireless communication devices 204B, 204C are operable to receive a signal based on the signal transmitted by the wireless communication device 204A. The wireless communication devices 204B, 204C each have a modem (e.g., modem 112 shown in FIG. 1) configured to process the received signal to detect movement of an object in the space 200.

[0095] As shown, the object is at a first position 214A in Figure 2A, and the object has moved to a second position 214B in Figure 2B. Although the moving object in the space 200 is depicted as a human in Figures 2A and 2B, the moving object may be another type of object. For example, the moving object may be an animal, an inanimate object (e.g., a system, device, apparatus, or assembly), an object that defines all or part of the boundary of the space 200 (e.g., a wall, a door, a window, etc.), or another type of object.

[0096] 2A and 2B, multiple exemplary paths of a wireless signal transmitted from the wireless communication device 204A are indicated by dashed lines. Along a first signal path 216, the wireless signal is transmitted from the wireless communication device 204A and reflected from the first wall 202A towards the wireless communication device 204B. Along a second signal path 218, the wireless signal is transmitted from the wireless communication device 204A and reflected from the second wall 202B and the first wall 202A towards the wireless communication device 204C. Along a third signal path 220, the wireless signal is transmitted from the wireless communication device 204A and reflected from the second wall 202B towards the wireless communication device 204C. Along a fourth signal path 222, the wireless signal is transmitted from the wireless communication device 204A and reflected from the third wall 202C towards the wireless communication device 204B.

[0097] In FIG. 2A, along the fifth signal path 224A, the wireless signal is transmitted from the wireless communication device 204A and is reflected from an object at the first position 214A toward the wireless communication device 204C. Between FIG. 2A and FIG. 2B, the surface of the object moves from the first position 214A to the second position 214B in the space 200 (e.g., a distance away from the first position 214A). In FIG. 2B, along the sixth signal path 224B, the wireless signal is transmitted from the wireless communication device 204A and is reflected from an object at the second position 214B toward the wireless communication device 204C. The sixth signal path 224B depicted in FIG. 2B is longer than the fifth signal path 224A depicted in FIG. 2A due to the movement of the object from the first position 214A to the second position 214B. In some examples, the signal paths can be added, removed, or otherwise modified due to the movement of the object in the space.

[0098] 2A and 2B may be attenuated, frequency shifted, phase shifted, or otherwise affected along their respective paths, and may have portions that propagate in different directions through the first wall 202A, the second wall 202B, and the third wall 202C, for example. In some examples, the wireless signal is a radio frequency (RF) signal. The wireless signal may include other types of signals.

[0099] In the example shown in Figures 2A and 2B, the wireless communication device 204A may repeatedly transmit a wireless signal. In particular, Figure 2A shows a wireless signal being transmitted from the wireless communication device 204A at a first time, and Figure 2B shows the same wireless signal being transmitted from the wireless communication device 204A at a second, later time. The transmission signal may be transmitted continuously, periodically, at random or intermittent times, etc., or combinations thereof. The transmission signal may have multiple frequency components within a frequency bandwidth. The transmission signal may be transmitted from the wireless communication device 204A omnidirectionally, directional, or otherwise. In the illustrated example, the wireless signal traverses multiple respective paths in the space 200, and the signal along each path may be attenuated due to path loss, scattering, reflection, etc., and may have a phase or frequency offset.

[0100] As shown in FIG. 2A and FIG. 2B, signals from the first through sixth paths 216, 218, 220, 222, 224A, and 224B are combined at the wireless communication device 204C and the wireless communication device 204B to form a received signal. Due to the effect of multiple paths in the space 200 on the transmitted signal, the space 200 may be represented as a transfer function (e.g., a filter) where the transmitted signal is input and the received signal is output. When an object moves in the space 200, the attenuation or phase offset affecting the signal in the signal path may change, and thus the transfer function of the space 200 may change. Assuming the same wireless signal is transmitted from the wireless communication device 204A, if the transfer function of the space 200 changes, the output of that transfer function (the received signal) will also change. The change in the received signal can be used to detect the movement of the object.

[0101] Mathematically, a transmit signal f(t) transmitted from the first wireless communication device 204A may be described according to equation (1).

number

[0102] In the formula, ω n represents the frequency of the nth frequency component of the transmission signal, and c n represents the complex coefficient of the n-th frequency component, and t represents time. Using a transmission signal f(t) transmitted from the first wireless communication device 204A, an output signal r from a path k is k (t) can be written according to equation (2).

number

[0103] In the formula, α n,k represents the attenuation factor for the nth frequency component along path k (or, for example, the channel response due to scattering, reflection, and path loss), and φ n,krepresents the phase of the signal for the nth frequency component along path k. The received signal R at the wireless communication device is then calculated as the sum of all the output signals r from all the paths to the wireless communication device, as shown in equation (3). k (t) can be written as the sum of

number

[0104] By substituting equation (2) into equation (3), we obtain the following equation (4).

number

[0105] The received signal R at the wireless communication device may then be analyzed. The received signal R at the wireless communication device may be transformed into the frequency domain, for example, using a Fast Fourier Transform (FFT) or another type of algorithm. The transformed signal may be divided into n frequencies ω n The received signal R can be represented as a sequence of n complex values, one for each of the respective frequency components (at frequencies ω n For frequency components in the complex value H n can be expressed in equation (5) as follows:

number

[0106] For a given frequency component ω n Complex value H for n is the frequency component ω n , and the relative magnitude and phase offset of the received signal at n,k By changing the complex value H nchanges. Thus, a detected change in the channel response can indicate the movement of an object in the communication channel. In some cases, noise, interference, or other phenomena can affect the channel response detected by the receiver, and the motion detection system can reduce or isolate such effects to improve the accuracy and quality of the motion detection capability. In some implementations, the overall channel response can be expressed in equation (6) as follows:

number

[0107] In some cases, the spatial channel response h ch can be determined based on, for example, a mathematical estimation theory. For example, the reference signal R ef is the candidate channel response (h ch ) and then the received signal (R cvd A maximum likelihood approach can be used to select the candidate channel that provides the best match for the estimated received signal

number

number

number

[0108] The optimization criterion is

number

[0109] The minimization or optimization process may utilize adaptive filtering techniques such as least mean squares (LMS), recursive least squares (RLS), batch least squares (BLS), etc. The channel response may be a finite impulse response (FIR) filter, an infinite impulse response (IIR) filter, etc. As shown in the above equation, the received signal may be considered as a convolution of a reference signal and a channel response. The convolution operation means that the channel coefficients have some correlation with each of the delayed replicas of the reference signal. Thus, the convolution operation shown in the above equation indicates that the received signal appears at different delay points, and each delayed replica is weighted by a channel coefficient.

[0110] 3A and 3B are plots illustrating example channel responses 360 and 370 calculated from wireless signals communicated between wireless communication devices 204A, 204B, 204C in FIGS. 2A and 2B. FIGS. 3A and 3B also show a frequency domain representation 350 of an initial wireless signal transmitted by wireless communication device 204A. In the illustrated example, channel response 360 ​​in FIG. 3A represents a signal received by wireless communication device 204B when there is no motion in space 200, and channel response 370 in FIG. 3B represents a signal received by wireless communication device 204B in FIG. 2B after an object has moved in space 200.

[0111] In the example shown in FIG. 3A and FIG. 3B, for illustrative purposes, the wireless communication device 204A transmits a signal having a flat frequency profile (the magnitude of each frequency component f1, f2, and f3 is the same), as shown in the frequency domain representation 350. Due to the interaction of the signal with the space 200 (and objects therein), the signal received at the wireless communication device 204B based on the signal transmitted from the wireless communication device 204A is different from the transmitted signal. In this example where the transmitted signal has a flat frequency profile, the received signal represents the channel response of the space 200. As shown in FIG. 3A and FIG. 3B, the channel response 360 ​​channel response 370 is different from the frequency domain representation 350 of the transmitted signal. When motion occurs in the space 200, a variation in the channel response also occurs. For example, as shown in FIG. 3B, the channel response 370 associated with the motion of an object in the space 200 is different from the channel response 360 ​​associated with no motion in the space 200.

[0112] Furthermore, as an object moves within the space 200, the channel response may vary from the channel response 370. In some cases, the space 200 may be divided into distinct regions, and the channel responses associated with each region may share one or more characteristics (e.g., shape), as described below. Thus, the movement of objects within different distinct regions may be distinguished, and the location of the detected movement may be determined based on an analysis of the channel responses.

[0113] 4A and 4B are diagrams illustrating example channel responses 401 and 403 associated with the movement of an object 406 in distinct regions of a space 400, a first region 408, and a third region 412. In the illustrated example, the space 400 is a building, and the space 400 is divided into multiple distinct regions, namely, a first region 408, a second region 410, a third region 412, a fourth region 414, and a fifth region 416. The space 400 may include additional or fewer regions in some cases. As shown in FIGS. 4A and 4B, the regions in the space 400 may be defined by walls between rooms. In addition, the regions may be defined by ceilings between floors of the building. For example, the space 400 may include additional floors with additional rooms. In addition, in some cases, the multiple regions of the space may be or include multiple floors in a high-rise building, multiple rooms in a building, or multiple rooms on a particular floor of a building. In the example shown in FIG. 4A, the object located in the first region 408 is represented as a person 406, although the moving object may be another type of object, such as an animal or an inanimate object.

[0114] In the illustrated example, the wireless communication device 402A is located in a fourth region 414 of the space 400, the wireless communication device 402B is located in a second region 410 of the space 400, and the wireless communication device 402C is located in a fifth region 416 of the space 400. The wireless communication device 402 may operate in the same or similar manner as the wireless communication device 102 of FIG. 1. For example, the wireless communication device 402 may be configured to transmit and receive wireless signals and detect whether motion has occurred in the space 400 based on the received signals. As an example, the wireless communication device 402 may periodically or repeatedly transmit a motion probing signal through the space 400 and receive a signal based on the motion probing signal. The wireless communication device 402 may analyze the received signals to detect whether an object has moved within the space 400, such as by analyzing a channel response associated with the space 400 based on the received signals. Additionally, in some implementations, the wireless communication device 402 may analyze the received signals to identify a location of the detected motion within the space 400. For example, the wireless communication device 402 may analyze the characteristics of the channel response to determine whether the channel response shares the same or similar characteristics as channel responses known to be associated with the first through fifth regions 408, 410, 412, 414, 416 of the space 400.

[0115] In the illustrated example, one (or more) of the wireless communication devices 402 repeatedly transmits a motion search signal (e.g., a reference signal) through the space 400. The motion search signal may have a flat frequency profile in some cases, with the magnitudes of f1, f2, and f3 being the same or nearly the same. For example, the motion search signal may have a frequency response similar to the frequency domain representation 350 shown in FIGS. 3A-3B. The motion search signal may have a different frequency profile in some cases. Due to the interaction of the reference signal with the space 400 (and objects therein), a signal received at another wireless communication device 402 based on a motion search signal transmitted from another wireless communication device 402 differs from the transmitted reference signal.

[0116] Based on the received signals, the wireless communication device 402 can determine a channel response for the space 400. When motion occurs in distinct regions in the space, distinct characteristics may be seen in the channel response. For example, the channel response may be slightly different for motion in the same region of the space 400, but the channel responses associated with motion in distinct regions may generally share the same shape or other characteristics. For example, the channel response 401 in FIG. 4A represents an exemplary channel response associated with motion of an object 406 in a first region 408 of the space 400, and the channel response 403 in FIG. 4B represents an exemplary channel response associated with motion of an object 406 in a third region 412 of the space 400. The channel response 401 and the channel response 403 are associated with signals received by the same wireless communication device 402 in the space 400.

[0117] 4C and 4D are plots showing the channel response 401 and the channel response 403 of FIG. 4A and FIG. 4B superimposed on a channel response 460 associated with no motion occurring in the space 400. In the illustrated example, the wireless communication device 402 transmits a motion probing signal having a flat frequency profile as shown in the frequency domain representation 450. When motion occurs in the space 400, a variation in the channel response occurs with respect to the channel response 460 associated with no motion, and thus, by analyzing the variation in the channel response, motion of an object in the space 400 can be detected. In addition, the relative location of the detected motion in the space 400 can be identified. For example, the shape of the channel response associated with the motion can be compared to reference information (e.g., using a trained AI model) to classify the motion as occurring in a distinct region of the space 400.

[0118] When there is no motion in the space 400 (e.g., no object 406 is present), the wireless communication device 402 may calculate a channel response 460 associated with no motion. Although multiple factors may cause slight variations in the channel response, multiple channel responses 460 associated with different time periods may share one or more characteristics. In the illustrated example, the channel response 460 associated with no motion has a decreasing frequency profile (the magnitude of each frequency component f1, f2, and f3 is smaller than the previous frequency component). The profile of the channel response 460 may differ in some cases (e.g., based on different room layouts or placements of the wireless communication device 402).

[0119] When motion occurs in the space 400, variations in the channel response occur. For example, in the example shown in Figures 4C and 4D, the channel response 401 associated with the movement of the object 406 in the first region 408 is different from the channel response 460 associated with no motion, and the channel response 403 associated with the movement of the object 406 in the third region 412 is different from the channel response 460 associated with no motion. The channel response 401 has a concave parabolic frequency profile (the magnitude of the middle frequency component f2 is smaller than the outer frequency components f1 and f3), and the channel response 403 has a convex asymptotic frequency profile (the magnitude of the middle frequency component f2 is larger than the outer frequency components f1 and f3). The profiles of the channel responses 401, 403 may be different in some cases (e.g., based on different room layouts or placements of the wireless communication devices 402).

[0120] Analyzing a channel response can be considered similar to analyzing a digital filter. The channel response can be formed through reflections of objects in space as well as reflections caused by moving or stationary humans. When a reflector (e.g., a human) moves, the channel response changes. This can be translated into changes in the equivalent taps of a digital filter that can be considered to have poles and zeros (poles amplify frequency components of the channel response and appear as peaks or high points in the response, while zeros attenuate frequency components of the channel response and appear as troughs, low points or nulls in the response). The changing digital filter can be characterized by the location of its peaks and troughs, and the channel response can be characterized by its peaks and troughs as well. For example, in some implementations, nulls and peaks in the frequency components of the channel response can be analyzed (e.g., by marking their location on the frequency axis and their magnitude) to detect motion.

[0121] In some implementations, time series aggregation can be used to detect motion. Time series aggregation can be performed by observing the characteristics of the channel response over a moving window and aggregating the windowed results by using statistical measures (e.g., mean, variance, principal components, etc.). During an instance of motion, the characteristic digital filter features are displaced in terms of location and flip-flop between some values ​​due to the continuous changes of the scattering scene. That is, the equivalent digital filter shows a range of values ​​for its peaks and nulls (due to motion). By looking at this range of values, a unique profile (e.g., the profile may be referred to as a signature) can be identified for a distinct region in the space.

[0122] In some implementations, artificial intelligence (AI) models can be used to process the data. AI models can be of various types, such as linear regression models, logistic regression models, linear discriminant analysis models, decision tree models, naive Bayes models, K-nearest neighbor models, learning vector quantization models, support vector machines, bagging and random forest models, and deep neural networks. Generally, all AI models aim to learn a function that provides the most accurate correlation between input and output values, and are trained using a historical set of inputs and outputs that are known to be correlated. For example, artificial intelligence is sometimes referred to as machine learning.

[0123] In some implementations, a profile of channel response associated with movement in distinct regions of the space 400 may be learned. For example, machine learning may be used to categorize channel response characteristics with movement of objects in distinct regions of the space. In some cases, a user associated with the wireless communication device 402 (e.g., an owner or other occupant of the space 400) may assist in the learning process. For example, with reference to the example shown in FIG. 4A and FIG. 4B, the user may move within each of the first through fifth regions 408, 410, 412, 414, 416 during the learning phase and may indicate (e.g., through a user interface on a mobile computing device) that the user is moving within one of the particular regions in the space 400. For example, while the user is moving through the first region 408 (e.g., as shown in FIG. 4A), the user may indicate on the mobile computing device that he or she is within the first region 408 (and may name the region as a "bedroom," "living room," "kitchen," or another type of room in the building, if desired). Channel responses may be obtained as the user moves through the region, and the channel responses may be "tagged" with the user's indicated location (region). The user may repeat the same process for other regions of the space 400. As used herein, the term "tagged" may refer to marking and identifying the channel response with the user's indicated location or any other information.

[0124] The tagged channel response can then be processed (e.g., by machine learning software) to identify unique characteristics of the channel response associated with motion in distinct regions. Once identified, the identified unique characteristics can be used to determine the location of the detected motion for the newly calculated channel response. For example, an AI model can be trained using the tagged channel response, and once trained, the newly calculated channel response can be input into the AI ​​model, which can output the location of the detected motion. For example, in some cases, the mean, range, and absolute values ​​are input into the AI ​​model. In some cases, the magnitude and phase of the complex channel response itself can also be input. These values ​​allow the AI ​​model to design any front-end filters to pick up the features that are most relevant to making accurate predictions regarding motion in different regions of space. In some implementations, the AI ​​model is trained by performing stochastic gradient descent. For example, channel response variations that are most active during certain zones may be monitored during training, and certain channel variations may be weighted heavily (by training and adapting weights in the first layer to correlate with their shape, trend, etc.). The weighted channel variation can be used to create a metric that activates when a user is within a particular region.

[0125] For extracted features such as channel response nulls and peaks, a time series (of nulls / peaks) can be created using aggregation in a moving window, taking snapshots of some features in the past and present, and using the aggregated values ​​as input to the network. Thus, the network tries to aggregate values ​​in a particular region in order to cluster them while adapting its weights, which can be done by creating a logistic classifier-based decision surface. The decision surface separates the different clusters, and subsequent layers can form categories based on a single cluster or a combination of clusters.

[0126] In some implementations, the AI ​​model includes two or more layers of inference. The first layer acts as a logistic classifier that can split values ​​of different cardinality into separate clusters, and the second layer combines some of these clusters together to create a category of separate regions. Additional subsequent layers can help extend the separate regions across more than two categories of clusters. For example, a fully connected input layer model may include an AI that corresponds to the number of tracked features, an intermediate layer that corresponds to the number of valid clusters (through iterations between selections), and a final layer that corresponds to the different regions. If full channel response information is input to the AI ​​model, the first layer may act as a shape filter that can correlate specific shapes. Thus, the first layer may lock onto specific shapes, the second layer may generate a measure of the variations that occur in those shapes, and the third and subsequent layers may create combinations of those variations and map them to different regions in space. The outputs of the different layers may then be combined through a fusion layer.

[0127] Systems and methods for Wi-Fi sensing using uplink orthogonal frequency division multiple access (UL-OFDMA) The present disclosure relates generally to systems and methods for Wi-Fi sensing, and more particularly to configuring a Wi-Fi system to perform Wi-Fi sensing using uplink orthogonal frequency division multiple access (UL-OFDMA).

[0128] The systems and methods of the present disclosure utilize a sensing device that may be configured to control a measurement campaign. In one implementation, the systems and methods also utilize one or more remote devices. The one or more remote devices may be configured to perform sensing transmissions, and the sensing devices may be configured to calculate sensing measurements based on the sensing transmissions. In one implementation, the sensing measurements may be further processed to achieve the purpose of the measurement campaign. According to one implementation, the sensing device may provide a sensing agent that may use channel resources in different manners to explore the sensing space in which the system is deployed. The different manners may be considered as different operation modes of the sensing agent, and the selection of the operation mode is made based on the requirements of the sensing agent at a particular time. Each mode of operation delivers appropriate sensing measurements with efficient use of the available channel resources.

[0129] According to one implementation, a sensing device can initiate a WLAN sensing session, and one or more remote devices can join the WLAN session initiated by the sensing device. In some implementations, the one or more remote devices can transmit PPDUs used for sensing measurements in the WLAN sensing session. In one implementation, the sensing device can receive PPDUs in the WLAN sensing session and process the PPDUs into sensing measurements.

[0130] FIG. 5 illustrates a portion of the architecture of an implementation of a system 500 for Wi-Fi sensing, according to some embodiments.

[0131] The system 500 (alternatively referred to as Wi-Fi sensing system 500) may include a sensing device 502, a number of remote devices 504-(1-N), a sensing algorithm device 506, and a network 560 that enables communication between the system components for information exchange. The system 500 may be an example or instance of the wireless communication system 100, and the network 560 may be an example or instance of a wireless network or cellular network connection, details of which are provided with reference to FIG. 1 and the accompanying description.

[0132] According to some embodiments, the sensing device 502 may be configured to receive sensing transmissions and perform one or more measurements (e.g., CSI) useful for Wi-Fi sensing. These measurements may be known as sensing measurements. The sensing measurements may be processed to achieve the sensing goal of the system 500. In one embodiment, the sensing device 502 may be an access point (AP). In some embodiments, the sensing device 502 may be, for example, a station (STA) in a mesh network scenario. According to one implementation, the sensing device 502 may be implemented by a device such as the wireless communication device 102 shown in FIG. 1. In some implementations, the sensing device 502 may be implemented by a device such as the wireless communication device 204 shown in FIG. 2A and FIG. 2B. Furthermore, the sensing device 502 may be implemented by a device such as the wireless communication device 402 shown in FIG. 4A and FIG. 4B. In one implementation, the sensing device 502 may coordinate and control communications between multiple remote devices 504-(1-N). According to one implementation, the sensing device 502 can control the measurement campaign to ensure that the necessary sensing transmissions occur at the necessary times and to ensure accurate determination of the sensing measurements. In some embodiments, the sensing device 502 can process the sensing measurements to achieve the sensing goals of the system 500. In some embodiments, the sensing device 502 can be configured to transmit the sensing measurements to the sensing algorithm device 506, which can be configured to process the sensing measurements and achieve the sensing goals of the system 500.

[0133] Referring again to FIG. 5, in some embodiments, the remote device 504-1 may be configured to transmit a sensing transmission to the sensing device 502, based on which one or more sensing measurements (e.g., CSI) may be performed for Wi-Fi sensing. In one embodiment, the remote device 504-1 may be a STA. In some embodiments, the remote device 504-1 may be an AP for Wi-Fi sensing, for example, in a scenario in which the sensing device 502 operates as a STA. According to one implementation, the remote device 504-1 may be implemented by a device such as the wireless communication device 102 shown in FIG. 1. In some implementations, the remote device 504-1 may be implemented by a device such as the wireless communication device 204 shown in FIG. 2A and FIG. 2B. Furthermore, the remote device 504-1 may be implemented by a device such as the wireless communication device 402 shown in FIG. 4A and FIG. 4B. In some implementations, communications between the sensing device 502 and the remote device 504-1 may be controlled via a Station Management Entity (SME) and MAC Layer Management Entity (MLME) protocol. According to one embodiment, each of the multiple remote devices 504-(1-N) may be configured to send a sensing transmission to the sensing device 502.

[0134] In some embodiments, the sensing algorithm device 506 may be configured to receive sensing measurements from the sensing device 502 and process the sensing measurements. In one example, the sensing algorithm device 506 may process and analyze the sensing measurements to identify one or more features of interest. According to some implementations, the sensing algorithm device 506 may include / execute a sensing algorithm. In one embodiment, the sensing algorithm device 506 may be a STA. In some embodiments, the sensing algorithm device 506 may be an AP. According to one implementation, the sensing algorithm device 506 may be implemented by a device such as the wireless communication device 102 shown in FIG. 1. In some implementations, the sensing algorithm device 506 may be implemented by a device such as the wireless communication device 204 shown in FIG. 2A and FIG. 2B. Furthermore, the sensing algorithm device 506 may be implemented by a device such as the wireless communication device 402 shown in FIG. 4A and FIG. 4B. In some embodiments, the sensing algorithm device 506 can be any computing device, such as a desktop computer, a laptop, a tablet computer, a mobile device, a personal digital assistant (PDA), or any other computing device. In an embodiment, the sensing algorithm device 506 can act as a sensing initiator, where the sensing algorithm determines the measurement campaign and the sensing measurements required to satisfy the measurement campaign. The sensing algorithm device 506 can communicate the sensing measurements required to satisfy the measurement campaign to the sensing device 502 to coordinate and control communications between the multiple remote devices 504-(1-N).

[0135] 5 in more detail, the sensing device 502 may include a processor 508 and a memory 510. For example, the processor 508 and memory 510 of the sensing device 502 may be the processor 114 and memory 116, respectively, as shown in FIG. 1. In one embodiment, the sensing device 502 may further include a transmit antenna 512, a receive antenna 514, and a sensing agent 516. In some embodiments, the antennas may be used to both transmit and receive signals in a half-duplex format. When an antenna is transmitting, it may be referred to as a transmit antenna 512, and when an antenna is receiving, it may be referred to as a receive antenna 514, and it will be understood by those skilled in the art that the same antenna may be a transmit antenna 512 in some cases and a receive antenna 514 in other cases. In the case of an antenna array, one or more antenna elements may be used to transmit or receive signals, for example, in a beamforming environment. In some examples, a group of antenna elements used to transmit the composite signal may be referred to as a transmit antenna 512, and a group of antenna elements used to receive the composite signal may be referred to as a receive antenna 514. In some examples, each antenna may have its own transmit and receive paths that may be alternately switched to connect to the antenna depending on whether the antenna is operating as a transmit antenna 512 or a receive antenna 514.

[0136] In one implementation, the sensing agent 516 may be responsible for receiving the sensing transmission and associated transmission parameters, calculating the sensing measurements, and processing the sensing measurements to meet the sensing objectives. In some implementations, receiving the sensing transmission and associated transmission parameters and calculating the sensing measurements may be performed by algorithms operating in a medium access control (MAC) layer of the sensing device 502, and processing the sensing measurements to meet the sensing objectives may be performed by algorithms operating in an application layer of the sensing device 502. For example, algorithms running in the application layer of the sensing device 502 are known as Wi-Fi sensing agents, sensing applications, or sensing algorithms. In some implementations, algorithms running in the MAC layer of the sensing device 502 and algorithms running in the application layer of the sensing device 502 may run separately on the processor 508. In one implementation, the sensing agent 516 can pass physical layer parameters (e.g., CSI, etc.) from the MAC layer of the sensing device 502 to the application layer of the sensing device 502, and can use the physical layer parameters to detect one or more features of interest. In one example, the application layer can operate on the physical layer parameters to form services or features that can be presented to an end user. According to one implementation, communication between the MAC layer and other layers or components of the sensing device 502 can be based on a communication interface, such as an MLME interface and a data interface. According to some implementations, the sensing agent 516 can include / execute sensing algorithms. In one implementation, the sensing agent 516 can process and analyze sensing measurements using the sensing algorithms to identify one or more features of interest. Furthermore, the sensing agent 516 can be configured to determine the number and timing of sensing transmissions and sensing measurements for the purpose of Wi-Fi sensing.In some implementations, the sensing agent 516 may be configured to transmit the sensing measurements to the sensing algorithm device 506 for further processing.

[0137] In one implementation, the sensing agent 516 may be configured to cause at least one of the transmitting antennas 512 to transmit a message to the remote device 504-1. Additionally, the sensing agent 516 may be configured to receive a message from the remote device 504-1 via at least one of the receiving antennas 514. In one example, the sensing agent 516 may be configured to perform a sensing measurement based on the sensing transmission received from the remote device 504-1. According to one implementation, the sensing agent 516 may be configured to process and analyze the sensing measurements to identify one or more features of interest. In some embodiments, the sensing agent 516 may have multiple operating modes or states to execute when monitoring the sensing space to detect associated features of interest.

[0138] In some embodiments, the sensing device 502 may include a sensing trigger message storage 518, a resource unit storage 520, and a sensing measurement storage 522. In one implementation, the sensing trigger message storage 518 may store a sensing trigger message transmitted by the sensing device 502 to the multiple remote devices 504-(1-N). According to one implementation, the resource unit storage 520 may store resource units (RUs) allocated to the multiple remote devices 504-(1-N). In one implementation, the sensing measurement storage 522 may store sensing measurements calculated by the sensing device 502 based on the sensing transmissions. Information about the sensing trigger message stored in the sensing trigger message storage 518, information about the RUs allocated to the multiple remote devices 504-(1-N) stored in the resource unit storage 520, and information about the sensing measurement values ​​stored in the sensing measurement storage 522 may be updated periodically or dynamically as needed. In one implementation, the sensing trigger message storage 518 , the resource unit storage 520 , and the sensing measurement value storage 522 may include any type or form of storage, such as a database or file system, or coupled to the memory 510 .

[0139] Referring again to FIG. 5, the remote device 504-1 may include a processor 528-1 and a memory 530-1. For example, the processor 528-1 and the memory 530-1 of the remote device 504-1 may be the processor 114 and the memory 116, respectively, as shown in FIG. 1. In one embodiment, the remote device 504-1 may further include a transmit antenna 532-1, a receive antenna 534-1, and a sensing agent 536-1. In one implementation, the sensing agent 536-1 may be a block that passes physical layer parameters to and from the MAC of the remote device 504-1 to an application layer program. The sensing agent 536-1 may be configured to cause at least one transmit antenna of the transmit antennas 532-1 and at least one receive antenna of the receive antennas 534-1 to exchange messages with the sensing device 502. In some embodiments, the antennas may be used to both transmit and receive in a half-duplex format. When an antenna is transmitting, it may be referred to as a transmitting antenna 532-1, and when an antenna is receiving, it may be referred to as a receiving antenna 534-1. It will be understood by those skilled in the art that the same antenna may be a transmitting antenna 532-1 in some cases and a receiving antenna 534-1 in other cases. In the case of an antenna array, one or more antenna elements may be used to transmit or receive signals, for example, in a beamforming environment. In some examples, a group of antenna elements used to transmit a composite signal may be referred to as a transmitting antenna 532-1, and a group of antenna elements used to receive a composite signal may be referred to as a receiving antenna 534-1. In some examples, each antenna has its own transmitting and receiving paths, which may be alternately switched to connect to the antenna depending on whether the antenna is operating as a transmitting antenna 532-1 or a receiving antenna 534-1.

[0140] In some embodiments, the remote device 504-1 may include a transmission configuration storage 540-1 and a steering matrix configuration storage 542-1. The transmission configuration storage 540-1 may store a requested transmission configuration to be delivered by the sensing device 502 to the remote device 504-1 or a delivered transmission configuration to be delivered by the remote device 504-1 to the sensing device 502. In addition, the steering matrix configuration storage 542-1 may store one or more predefined steering matrix configurations. Information about the transmission configurations stored in the transmission configuration storage 540-1 and the one or more predefined steering matrix configurations stored in the steering matrix configuration storage 542-1 may be updated periodically or dynamically as needed. In one implementation, the transmission configuration storage 540-1 and the steering matrix configuration storage 542-1 may include any type or form of storage, such as a database or a file system, or be coupled to the memory 530-1.

[0141] According to one or more implementations, communications in network 560 may be governed by one or more of the 802.11 family of standards developed by the IEEE. Some example IEEE standards may include IEEE P802.11-REVmd / D5.0, IEEE P802.11ax / D7.0, and IEEE P802.11be / D0.1. In some implementations, communications may be governed by other standards (other or additional IEEE standards or other types of standards). In some embodiments, portions of network 560 that do not require system 500 to be governed by one or more of the 802.11 family of standards may be implemented by instances of any type of network, including wireless or cellular networks.

[0142] Furthermore, IEEE 802.11ax employs OFDMA, which allows the sensing device 502 to simultaneously transmit data to all participating devices, such as multiple remote devices 504-(1-N), using a single TXOP, and vice versa. The efficiency of OFDMA depends on how the sensing device 502 schedules channel resources (interchangeably referred to as resource units (RUs)) among the multiple remote devices 504-(1-N) and configures transmission parameters. The uplink OFDMA transmission procedure and trigger frame format of IEEE 802.11ax are illustrated in FIG. 6. According to IEEE 802.11ax, all uplink multi-user transmissions are followed by a trigger frame 610, the format of which is illustrated in FIG. 6. As seen in FIG. 6, the sensing transmission (i.e., the sensing response message) is followed by one SIFS followed by the trigger frame. In one example, the duration of the SIFS is 10 μs. The main purpose of the trigger frame is to solicit an immediate response of the multi-user PPDU from the multiple remote devices 504-(1-N). According to one example, the trigger frame can specify common synchronization parameters for the TXOP to multiple remote devices 504-(1-N) along with a map to the RU for each remote device. This map allows OFDMA to function without interference. Messages controlled by the trigger frame generally follow a time-frequency message pattern as shown in FIG. 6. The trigger frame includes a common information field, a user information list field, and various other fields.

[0143] According to one implementation, the hierarchy of fields within a trigger frame 710 is shown in Figures 7A-7G.

[0144] As illustrated in Figures 7A and 7D, the top level of the hierarchy includes a MAC header that includes a control field and a frame addressing field. Figure 7A also shows a common information field that contains information common to the triggered request (e.g., information about the remote devices participating in the triggered request), and Figure 7D shows a user information list that contains information specific to each individual remote device in a contiguous list of remote devices participating in the triggered request.

[0145] As illustrated in Figure 7B, the first four bits (B0-B3) of the common information field define the trigger type, and as illustrated in Figure 7C, bits B18 and B19 define the uplink (UL) bandwidth (BW) of the resulting combined response, with the encoding described by Table 1 provided below. The bandwidth of the combined response refers to the bandwidth of the TXOP that contains the remote device's transmission. [Table 1]

[0146] As will be explained, the User Information List of the trigger frame 710 contains data specific to the remote devices participating in the triggered response. As will be explained in Figure 7E, the first 12 bits (B0-B11) of the User Information List define the remote device (AID12) that the User Information is targeted to, and as will be explained in Figures 7F and 7G, bits B12-B19 constitute the Resource Allocation subfield and define the allocation of RUs according to Table 2 (provided below) and Figures 8, 9, 10A, and 10B. [Table 2-1] [Table 2-2]

[0147] In one example, if the UL BW subfield indicates 80+80 MHz or 160 MHz, the description indicates the RU index for the primary 80 MHz channel or the secondary 80 MHz channel as indicated by B0 in the RU allocation subfield. In one implementation, with the evolution of the IEEE 802.11 standard, the bandwidth of the channel available for each sensing device-remote device connection has increased, up to a current maximum of 160 MHz. The IEEE 802.11ax HE PHY amendment allows channels to be allocated with greater flexibility and detail to multiple remote devices 504-(1-N) using OFDMA in uplink transmissions from the multiple remote devices 504-(1-N) to the sensing device 502. FIG. 8 illustrates a representation 810 of an allowable allocation for an RU in a 20 MHz channel, FIG. 9 illustrates a representation 910 of an allowable allocation for an RU in a 40 MHz channel, and FIGS. 10A and 10B illustrate a representation 1010 of an allowable allocation for an RU in an 80 MHz channel.

[0148] Future extensions to IEEE 802.11 may extend the maximum bandwidth of the channel as well as the number and format of RUs. The descriptions given in Tables 1 and 2 and Figures 7F and 7G and Figures 12F and 12G are examples based on the current level of the standard and should not limit any extensions to the described fields made to support IEEE 802.11.

[0149] According to one or more implementations, the sensing agent 516 can use channel resources in different manners to explore the sensing space in which the system 500 is deployed. The different manners can be considered as different operating modes of the sensing agent 516. Examples of different operating modes of the sensing agent 516 include a scan mode, a detection mode, and a hybrid mode. In one example, the selection of the operating mode can be based on the requirements of the sensing agent 516 at a particular time. Each operating mode can deliver appropriate sensing measurements with efficient use of the available channel resources.

[0150] In an example implementation, the scan mode may allow sensing measurements to be taken at a lower resolution. The resolution of the sensing measurements may be a function of the transmission bandwidth of the sensing transmission and may be adjusted by the sensing agent 516 requesting a lower bandwidth sensing transmission by allocating certain RUs to the sensing transmission. In one example, the sensing goal may be that the scan may be performed quickly and efficiently and may be required to survey the largest area in the sensing space in the shortest amount of time. Remote devices supporting the scan mode may be allocated a small amount of transmission bandwidth during a TXOP. In one example, the sensing agent 516 may allocate a fixed transmission bandwidth to each remote device that participates in the scan mode, and in this example may be able to support as many remote devices as a fraction of the sensing goal that may be allocated the transmission bandwidth. In the scan mode, the sensing agent 516 may track the allocated transmission bandwidth per remote device as part of the sensing algorithm for the purpose of calculating the sensing measurements per remote device. In one implementation, the sensing agent 516 may operate in the scan mode while scanning features of interest in the sensing space.

[0151] According to an example implementation, the detection mode may enable sensing measurements with high resolution to detect or analyze one or more features of interest in the sensing space. The detection mode may consume a larger transmission bandwidth per remote device. In one example, a remote device supporting the detection mode may be allocated a large amount of transmission bandwidth in a TXOP. In one example, the sensing agent 516 may allocate a fixed transmission bandwidth to each remote device participating in the detection mode, and in this example, may be able to support as many remote devices as a fraction of the sensing targets that may be allocated transmission bandwidth.

[0152] In an example, there may be multiple features of interest that may be analyzed in parallel. If there are multiple features of interest that the sensing agent 516 identifies, the sensing agent 516 may determine that a reduced level of resolution may be used, and the available transmission bandwidth may be shared between the features of interest. According to one implementation, when one or more features of interest have been identified (or potentially identified), high-resolution sensing measurements may be required, derived from a subset of available remote devices around the one or more features of interest. High-resolution sensing may be achieved by allocating a larger number of RUs such that a larger percentage of the available bandwidth is allocated to the subset of remote devices.

[0153] In an exemplary implementation, a hybrid mode may be employed that reduces the resources available for both scanning and detection operations as detection is performed for features of interest and scanning continues for the remainder of the network. In the hybrid mode, the transmission bandwidth for sensing transmissions may be allocated to the remote devices in any manner. An example of the use of the hybrid mode may be to focus in detail on a portion of the network of remote devices (e.g., all remote devices that may sense in a single room in a house) while scanning the rest of the remote devices in the network. In one example, in the hybrid mode, the sensing agent 516 may maintain a record of the allocated transmission bandwidth for each remote device to ensure that correct sensing measurements are calculated and that the sensing algorithms perform the scanning and detection operations correctly. In a further example, the sensing agent 516 may allocate a fixed transmission bandwidth to each remote device involved in the scanning operation as part of the hybrid mode and allocate a fixed transmission bandwidth to each remote device involved in the detection operation as part of the hybrid mode.

[0154] According to one implementation, the sensing agent 516 can operate in a hybrid mode in scenarios where the sensing target in the detection mode (as determined by the sensing agent 516) does not require the use of all available bandwidth. In such scenarios, the sensing agent 516 may allow the spare bandwidth to be allocated to successive low-resolution scans. In one example, the resolution for successive scans is not reduced, but the channels are multiplexed in time such that the frequency of successive scan sensing measurements is reduced to accommodate all remote devices in the network.

[0155] In one or more embodiments, the sensing agent 516 can transition between operational modes during its operation. An example of a state transition diagram 1110 of the sensing agent 516 is depicted in FIG. 11. In one implementation, each of the multiple remote devices 504-(1-N) can support the operational mode of the sensing agent 516 by providing sensing transmissions in a format defined by the sensing agent 516. The sensing agent 516 can maintain a record of the format of the sensing transmission to enable computing sensing measurements from the sensing transmission. As shown in FIG. 11, the sensing agent 516 can operate in a scan mode until one or more features of interest are identified (start state). Once one or more features of interest are identified from the scan mode, the sensing agent 516 can transition to a detection mode in which high-resolution sensing measurements may be performed. In some scenarios, the sensing agent 516 can operate in a hybrid mode such that the sensing agent 516 can also perform actions to continue in a low-resolution scan mode of operation while performing actions associated with the detection mode of operation.

[0156] According to one implementation, in the detection mode, the sensing agent 516 can determine a reduced set of remote devices and allocate a fixed percentage of the bandwidth to each remote device in the reduced set. In one example, the sensing agent 516 can allocate as much of the available channel bandwidth to the remote devices that the signaling can support. Furthermore, in the hybrid mode, the sensing agent 516 can determine the sensing goal and then determine the amount of bandwidth that can be allocated to the scanning and detection operations and therefore whether the sensing goal can be met by these operations. If the sensing agent 516 determines that the hybrid mode is inappropriate (e.g., it is not possible to maintain the hybrid mode operation and still provide sufficient transmission bandwidth to the remote devices sensing transmissions for which the sensing device 502 would make sensing measurements in the detection mode), the sensing agent 516 can transition to the detection mode.

[0157] In one implementation, if the sensing agent 516 determines that all sensing measurements required for the detection sensing target (i.e., performed in detection mode) have been made, the sensing agent 516 can return to the scan mode. In one example, the sensing agent 516 can transition from the detection mode to the scan mode via the hybrid mode to allow the scanning to resume for a portion of the sensing space, but ensure that eventual changes to the detection of the feature of interest do not occur and are not missed. The sleep state allows the sensing agent 516 to support a state of zero or low system resource utilization. In some examples, a timer periodically wakes the sensing agent 516, and the sensing agent 516 can transition to the scan mode. Depending on the results of the subsequent scan, the sensing agent 516 can proceed to the detection mode or the hybrid mode, or can return to the sleep state.

[0158] Referring again to FIG. 5, according to one or more implementations, the sensing device 502 can initiate a measurement campaign. In another implementation, the sensing algorithm device 506 may initiate the measurement campaign. The measurement campaign can involve an exchange of transmissions between the sensing device 502 and a number of remote devices 504-(1-N). In one example, control of these transmissions can be by a MAC (medium access control) layer of the IEEE 802.11 stack. According to one implementation, the sensing device 502 can secure a TXOP that can be allocated by the sensing device for sensing transmissions by a selected remote device. In one example, the selected remote device can include a number of remote devices 504-(1-N). In some examples, the selected remote device can include a subset of the number of remote devices 504-(1-N). For ease of illustration and understanding, the following description is provided with reference to a selected remote device that includes a number of remote devices 504-(1-N), but the description is equally applicable to the case of a subset of the number of remote devices 504-(1-N). According to one implementation, the sensing agent 516 can allocate a first channel resource to a first expected transmission from the multiple remote devices 504-(1-N), and the first channel resource can be included in a first TXOP. In one example, the sensing agent 516 can allocate the first channel resource to the multiple remote devices 504-(1-N) by allocating time and bandwidth in the first TXOP to the multiple remote devices 504-(1-N). In one implementation, the sensing device 502 can determine the bandwidth allocated to each of the multiple remote devices 504-(1-N) based on one or more of the operation mode of the sensing agent 516, the sensing goal, and the requirements for each of the multiple remote devices 504-(1-N).

[0159] In one example, the sensing goal of the scan mode may be to combine remote devices within the total available bandwidth. Thus, the allocated bandwidth per remote device may be a subset of the total available bandwidth. In one example, the allocation may be a predefined block size of bandwidth. In some examples, the bandwidth allocation may be limited by the bandwidth of each individual RU. In one implementation, equal bandwidth in the TXOP may be allocated to each remote device. According to one implementation, remote devices that need to respond in a non-equal bandwidth allocation may be determined.

[0160] According to one example, the sensing goal of the detection mode may be to increase the resolution of the sensing measurements. Thus, the allocated bandwidth per remote device may be larger compared to the sensing mode. In one example, all available bandwidth may be allocated to a single remote device. In some examples, a fixed bandwidth may be allocated to each remote device participating in the sensing goal. Furthermore, in some examples, if the sensing goal determines that a different resolution of the sensing measurements is required from the remote device, a different bandwidth may be allocated to the remote device.

[0161] In one example, the sensing goal of the hybrid mode may be to perform a detection operation with a subset of remote devices and use the spare bandwidth (i.e., the bandwidth not required by the remote devices participating in the detection operation) for the scan operation. If the bandwidth to meet the needs of the remote devices in the detection operation does not require all the bandwidth available in the TXOP, the spare bandwidth may be allocated among all remote devices that are not part of the detection operation (i.e., all remote devices participating in the scan operation). In one example, the spare bandwidth may be allocated among a subset of the remote devices participating in the scan operation, and the subset of the remote devices may be changed in a subsequent TXOP.

[0162] According to one implementation, the sensing agent 516 can allocate a first channel resource to the multiple remote devices 504-(1-N) according to a scan mode. After the first channel resource is allocated to the first expected transmission from the multiple remote devices 504-(1-N), the sensing agent 516 can generate a first sensing trigger message configured to trigger a first series of sensing transmissions from the multiple remote devices 504-(1-N). The first series of sensing transmissions may include sensing transmissions from each of the multiple remote devices 504-(1-N). In one example, the first sensing trigger message may be a UL-OFDMA sensing trigger message that may instruct the multiple remote devices 504-(1-N) to perform sensing transmissions using UL-OFDMA. Furthermore, the first sensing trigger message may be a scan type trigger message. The scan type trigger message may be a trigger message that describes different types of responses used in the scan mode and that meet the requirements of the scan mode. In one example, the first sensing trigger message may include a requested transmission configuration and a resource allocation subfield corresponding to a scanning mode.

[0163] According to an example, the first series of sensing transmissions may also correspond to a scan mode. In an example, the first sensing trigger message may inform the multiple remote devices 504-(1-N) of their allocation of RUs in the uplink bandwidth for use in the first TXOP. In some examples, the first sensing trigger message may include parameters that may instruct the multiple remote devices 504-(1-N) on further configuration items for the resulting sensing transmission using the requested transmission configuration. In one implementation, the sensing agent 516 may generate a first sensing trigger message including a specification of a steering matrix configuration. In one example, the first sensing trigger message may include the steering matrix configuration in the requested transmission configuration. In one implementation, the sensing agent 516 may transmit a first sensing trigger message configured to trigger a first series of sensing transmissions from the multiple remote devices 504-(1-N) via the transmit antenna 512.

[0164] The hierarchy of fields within the UL-OFDMA sensing trigger message 1210 is shown in FIGS. 12A-12H, and an example UL-OFDMA based sensing transmission transaction 1310 is shown in FIG.

[0165] As illustrated in Figures 12A and 12D, the top level of the hierarchy includes a MAC header that includes a control field and a frame addressing field. Figure 12A also shows a common information field that contains information common to the triggered request (e.g., information about the remote devices participating in the triggered request), and Figure 12D shows a user information list that contains information specific to each individual remote device in a contiguous list of remote devices participating in the triggered request.

[0166] As illustrated in Figure 12B, the first four bits (B0-B3) of the common information field define the trigger type. In one example, the trigger type has a subfield value of 8, which represents a UL-OFDMA sensing trigger. The UL-OFDMA sensing trigger combines a trigger frame format with multiple sensing trigger messages (e.g., one sensing trigger message for each remote device that is being triggered to perform a sensing transmission).

[0167] Referring again to FIG. 12D, in one example, in the UL-OFDMA sensing trigger message 1210, the field "Trigger Dependent User Information" contains sensing trigger message data.

[0168] As illustrated in Figure 12C, bits B18 and B19 can define the uplink (UL) bandwidth (BW) of the resulting combined response. In one example, the encoding of B18 and B19 can be explained by Table 1 already provided. The bandwidth of the combined response can refer to the bandwidth of the TXOP that includes the remote device's transmission.

[0169] As illustrated in FIG. 12E, the User Information List of the UL-OFDMA sensing trigger message 1210 may include data specific to the remote devices participating in the triggered response. As illustrated in FIG. 12E, the first 12 bits (B0-B11) of the User Information List may define the remote device (AID12) that the User Information is targeting, and as illustrated in FIG. 12F and FIG. 12G, bits B12-B19 may define the resource allocation subfield and the allocation of the RU. In an example, B12-B19 may define the allocation of the RU according to Table 2 and FIG. 8, FIG. 9, FIG. 10A, and FIG. 10B.

[0170] 13, the sensing device 502 transmits a single UL-OFDMA sensing trigger message to trigger sensing transmissions from the remote devices 504-(1-4). In response to the UL-OFDMA sensing trigger message, each of the remote devices 504-1, 504-2, 504-3, and 504-4 transmits a sensing transmission (i.e., a sensing response message).

[0171] Referring again to FIG. 5, in response to receiving the first sensing trigger message, each of the multiple remote devices 504-(1-N) can generate a sensing transmission. In one example, the sensing transmission that the first sensing trigger message triggers from each of the multiple remote devices 504-(1-N) can be a sensing response message. In one implementation, each of the multiple remote devices 504-(1-N) can generate a sensing transmission using the requested transmission configuration and the steering matrix configuration defined by the first sensing trigger message. In a scenario where the steering matrix configuration is not specified by the first sensing trigger message, each of the multiple remote devices 504-(1-N) can use a pre-configured default steering matrix configuration to perform the sensing transmission. In one implementation, the multiple remote devices 504-(1-N) can perform the first series of sensing transmissions in a single TXOP, i.e., the first TXOP. Thus, there is sufficient uplink channel bandwidth available to service the sensing target of the sensing mode. According to one implementation, multiple remote devices 504-(1-N) can transmit a first series of sensing transmissions to the sensing device 502.

[0172] In one implementation, the sensing device 502 may receive, via the receiving antenna 514, a first series of sensing transmissions transmitted in response to a first sensing trigger message. Upon receiving the first sensing trigger message, the sensing agent 516 may generate a first series of sensing measurements based on the first series of sensing transmissions. In one implementation, the sensing agent 516 may process the sensing transmissions received from each of the multiple remote devices 504-(1-N) to generate the first series of sensing measurements. According to some examples, the steering matrix configuration being applied by each of the multiple remote devices 504-(1-N) to perform the respective sensing transmissions may not support successful transfer of data to the sensing device 502. Thus, the sensing agent 516 may not be able to decode the data carried by the sensing transmissions (in the example, the data carried by the sensing transmissions is the delivered transmission configuration). However, because the sensing transmissions are made in response to the first sensing trigger message, the sensing agent 516 may assume that the sensing transmissions are made. In one example, the sensing agent 516 may assume that a requested transmission configuration is applied to the sensing transmission, and the sensing agent 516 may generate a first series of sensing measurements based on this assumption.

[0173] According to one implementation, after generating the first series of sensing measurements based on the first series of sensing transmissions, the sensing agent 516 can obtain identification information of the feature of interest according to the first series of sensing measurements. In one implementation, the sensing agent 516 can identify the feature of interest according to the first series of sensing measurements. In some implementations, the sensing agent 516 can transmit the first series of sensing measurements to the sensing algorithm device 506. Upon receiving the first series of sensing measurements, the sensing algorithm device 506 can execute a sensing algorithm to identify the feature of interest. Furthermore, the sensing algorithm device 506 can transmit the identification information of the feature of interest to the sensing device 502. In one implementation, the sensing agent 516 can receive the identification information of the feature of interest from the sensing algorithm device 506.

[0174] According to one or more embodiments, the sensing agent 516 can operate in a scan mode until a feature of interest is identified. Once a feature of interest is identified in the scan mode, the sensing agent 516 can transition to a detection mode or a hybrid mode. In one implementation, the sensing algorithm can receive notification that identification of the feature of interest is complete. The sensing algorithm can then instruct the sensing agent 516 to transition from the scan mode to a detection mode or a hybrid mode.

[0175] In one implementation, the sensing agent 516 can determine a selection of remote devices according to the feature of interest. In one example, the selection of remote devices can be a subset of the multiple remote devices 504-(1-N). According to one implementation, the sensing agent 516 can select remote devices that are in the vicinity of the feature of interest. In one implementation, the sensing agent 516 can allocate a second channel resource to a second expected transmission from the selection of remote devices. The second channel resource can be allocated to the selection of remote devices according to the detection mode and can be included in a second TXOP. In some embodiments, the sensing agent 516 can include the second channel resource in the same TXOP used for the first channel resource.

[0176] In one implementation, the sensing agent 516 may transmit, via the transmit antenna 512, a second sensing trigger message configured to trigger a second series of sensing transmissions from a selection of remote devices. In one example, the second sensing trigger message may be a UL-OFDMA sensing trigger message that may instruct the selected remote device to perform sensing transmissions using UL-OFDMA. In one example, the second sensing trigger message may be a detection type trigger message. The detection type trigger message may be a trigger message that describes a different type of response to be used in a detection mode and that meets the requirements of the detection mode. In one example, the second sensing trigger message may include a requested transmission configuration and a resource allocation subfield that corresponds to the detection mode. In one example, the second sensing trigger message may include a steering matrix configuration that corresponds to the detection mode. According to one implementation, in response to receiving the second sensing trigger message, the selected remote device may generate a second series of sensing transmissions and transmit the second series of sensing transmissions to the sensing device 502. In one implementation, the sensing agent 516 can receive, via the receiving antenna 514, a second series of sensing transmissions transmitted in response to the second sensing trigger message. In one example, the second series of sensing transmissions can correspond to a detection mode. Upon receiving the second series of sensing transmissions, the sensing agent 516 can generate a second series of sensing measurements based on the second series of sensing transmissions. In one implementation, the second series of sensing measurements can have a higher resolution than the first series of sensing measurements. According to one implementation, the sensing agent 516 can be configured to process and analyze the second series of sensing measurements to achieve a sensing goal, such as detecting movement and / or motion. Thus, the sensing agent 516 can benefit from the ability to request sensing transmissions of variable resolution that fit the requirements of a sensing algorithm and obtain them in the most efficient manner.TXOP and UL-OFDMA may also enable the sensing device 502 to ensure that many remote devices (up to all of the multiple remote devices 504-(1-N) in the BSS) have the opportunity to simultaneously transmit sensing transmissions with minimal measurement time jitter and minimal overhead, using parameters that can be controlled to efficiently achieve sensing goals.

[0177] According to some embodiments, the second sensing trigger message may include a hybrid type trigger message. The hybrid type trigger message may be a trigger message used in the hybrid mode and describing a different type of response that meets the requirements of the hybrid mode. In one example, the hybrid type trigger message may include a requested transmission configuration and a resource allocation subfield corresponding to the hybrid mode. In one example, the second sensing trigger message may include a steering matrix configuration corresponding to the hybrid mode. In one example, the hybrid type trigger message may be configured to trigger a first second series of sensing transmissions corresponding to a scan mode from a first group of remote devices and to trigger a second second series of sensing transmissions corresponding to a detection mode from a second group of remote devices. In one implementation, the sensing agent 516 may allocate a first portion of the second channel resources to a sensing transmission of the first second series of sensing transmissions received in response to the hybrid type trigger message and allocate a second portion of the second channel resources to a sensing transmission of the second second series of sensing transmissions received in response to the hybrid type trigger message.

[0178] According to one or more embodiments, a MU cascade sequence may be used in scenarios where the requirements of the sensing agent 516 require sensing transmissions from multiple remote devices 504-(1-N) that collectively exceed the available uplink bandwidth of the second TXOP. In one example, a situation where the sensing transmission requirements may exceed the available uplink bandwidth may occur when the sensing agent 516 may require a large number of remote devices to provide sensing transmissions in parallel. Such a situation is more likely to occur when the sensing agent 516 requires high bandwidth sensing transmissions from multiple remote devices 504-(1-N) to achieve a sensing goal, or when the amount of multiple remote devices 504-(1-N) is very large. In one implementation, a MU cascade sequence may enable the transmission of more complex blocks of sensing transmissions from multiple remote devices 504-(1-N) to the sensing device 502 within the same TXOP. In effect, a MU cascade sequence may enable both time division multiple access and frequency division multiple access.

[0179] According to one implementation, the MU cascading sequence may allow multiple UL-OFDMA sensing triggers and sensing transmissions to occur in a single TXOP. In one example, two or more trigger transmission pairs may be accommodated during the duration of the TXOP. In one implementation, the MU cascading sequence may allow the sensing agent 516 to solicit sensing transmissions from multiple remote devices in a single TXOP, even if the total aggregate bandwidth of those sensing transmissions exceeds the uplink channel bandwidth. In one implementation, in the MU cascading sequence, the AC of the TXOP is negotiated prior to the generation of the UL-OFDMA sensing trigger. In some examples, AC_VO or AC_VI are selected for the MU cascading sequence because they allow the transmission of multiple frames in the same TXOP (up to the duration of the TXOP). The duration of the TXOP for AC_VO and AC_VI is determined by the IEEE 802.11 system, and in an example, the sensing agent 516 may determine the AC of that TXOP according to the requirements of the sensing agent 516 at the time of negotiation. In one implementation, the sensing agent 516 may request a longer TXOP (over its AC) when a longer sequence of triggered sensing transmissions is needed.

[0180] According to some embodiments, the sensing target may require that the transmission bandwidth for the sum of all sensing transmissions is large and that the available bandwidth in the allocated channel may be insufficient to perform all sensing transmissions in parallel. In such a scenario, the channel usage may be maximized by allocating the entire channel bandwidth to a first set of remote devices to perform a first set of sensing transmissions, and then reallocating the same channel bandwidth to a second set of remote devices to perform a second set of sensing transmissions. In an example, the reallocation of the channel bandwidth may be repeated until all remote devices have performed sensing transmissions. In some embodiments, the sensing target may require that multiple sensing transmissions should be from the same remote device but with different transmission parameters. Thus, the same remote device may be triggered multiple times in the same TXOP with multiple UL-OFDMA sensing triggers. FIG. 14 illustrates an example MU cascaded sequence sensing transmission transaction 1410.

[0181] According to one or more embodiments, MU cascade sequences can be used to trigger sensing transmissions in scan mode, detection mode, and hybrid mode. In examples, MU cascade sequences can be used to scan large networks, to detect multiple features of interest, to detect features of interest while maintaining a full network scan, and to detect features of interest with large bandwidth sensing transmissions.

[0182] In one example, if the network of remote devices is very large, it may not be possible to scan the network with the available bandwidth in the TXOP. For example, this situation may occur when the available bandwidth in the TXOP is limited. In one example, only 20 MHz channels may be available. Thus, the number of RUs may be limited. In some examples, the bandwidth selected for the scan operation may be high compared to the available bandwidth. In such a scenario, the MU cascade sequence may be used to scan the network using sequential blocks, each block accommodating the maximum number of remote devices possible with the bandwidth for the scan operation allocated to each remote device. FIG. 15 illustrates an example MU cascade sequence sensing transmission transaction 1510 for scanning a large network. As shown in FIG. 15, there are a total of b remote devices in the network, and the b remote devices are scanned sequentially in two blocks.

[0183] In some examples, multiple features of interest may have been identified. A subset of remote devices supporting analysis of each feature of interest may be identified, and sensing transmissions from each subset of remote devices may be triggered. In one example, each subset of remote devices may be independent, mutually exclusive, or may share any number of remote devices. In some examples, each feature of interest may be analyzed by equal bandwidth sensing transmissions, and in other examples, different bandwidth sensing transmissions may be used. In one example, the bandwidth of the sensing transmissions used may be greater than the bandwidth used to scan the network.

[0184] According to some embodiments, the identified features of interest may include a first feature of interest and a second feature of interest. In such a scenario, the sensing agent 516 may determine a first selection of remote devices according to the first feature of interest and determine a second selection of remote devices according to the second feature of interest. Further, the sensing agent 516 may allocate a first portion of the second channel resources to the first selection of remote devices and allocate a second portion of the second channel resources to the second selection of remote devices.

[0185] FIG. 16 illustrates an example MU cascade sequence sensing transmission transaction 1610 for detecting multiple features of interest. In one implementation, there may be two features of interest that may be identified: a first feature of interest and a second feature of interest. In one example, there may be c remote devices associated with the first feature of interest and d remote devices associated with the second feature of interest. In one example, the c remote devices may be more numerous than the d remote devices. In this example, all available bandwidth of the TXOP is used for the first detection. However, there is unallocated bandwidth for the second detection because the c remote devices are more numerous than the d remote devices.

[0186] In one example, the feature of interest has been identified and can be analyzed in detail. In addition, the full network scan may continue with a second trigger, which is an example of a hybrid mode using a MU cascade sequence. In one example, the bandwidth of the sensing transmission used to detect the feature of interest may be greater than the bandwidth used to scan the network. FIG. 17 illustrates an example MU cascade sequence sensing transmission transaction 1710 for detecting the feature of interest while maintaining a full network scan. In one example, there may be f remote devices in the network. In addition, a subset of e remote devices may be included in the set of f remote devices. The e remote devices may be associated with the feature of interest. In one example, all available bandwidth of the TXOP is used first for detection and then for scanning.

[0187] In one example, a feature of interest may have been identified. It may further be determined that a large bandwidth sensing transmission is required and that the available bandwidth in the TXOP is not sufficient to accommodate all sensing transmissions in parallel. In such a scenario, the sensing transmission may be triggered in a block based on an algorithm that delivers the sensing transmission in the fastest manner. FIG. 18 illustrates an example MU cascade sequence sensing transmission transaction 1810 for detecting a feature of interest using a large bandwidth sensing transmission. As shown in FIG. 18, there may be four remote devices (i.e., remote device 1, remote device 2, remote device 3, and remote device 4) associated with the feature of interest. Sensing transmissions to these four remote devices may be triggered in two consecutive blocks.

[0188] As described above, some embodiments of the present disclosure define two sensing message types for Wi-Fi sensing: a UL-OFDMA sensing trigger message and a sensing response message. In one example, the message types are carried in a newly defined IEEE 802.11 management frame. In some examples, the message types are carried in a newly defined IEEE 802.11 control frame. In some examples, a combination of management and control frames may be used to realize these sensing message types. In some examples, the timing configuration, transmission configuration, and steering matrix configuration may be carried by the UL-OFDMA sensing trigger message and the sensing response message. In one example, the timing configuration, transmission configuration, and steering matrix configuration may be implemented as IEEE 802.11 elements. In another example, the timing configuration, transmission configuration, and steering matrix configuration carried by the UL-OFDMA sensing trigger message or the sensing response message may be referred to in their entirety as sensing measurement parameter elements.

[0189] In one or more embodiments, according to some embodiments, the sensing message types can be identified by a message type field, and each sensing message type may or may not carry the other identified elements. Examples of sensing message types and components are shown in Table 3. [Table 3-1] [Table 3-2] [Table 3-3]

[0190] Exemplary transmission components (eg, required transmission configurations or delivered transmission configurations) for sensing transmission are provided in Table 4. [Table 4-1] [Table 4-2] [Table 5] [Table 6] [Table 7]

[0191] Table 4 describes the transmission components (requested transmission configuration or delivered transmission configuration) for sensing transmission. In one example, these data are encoded into elements for inclusion in sensing messages between the sensing device 502 and multiple remote devices 504-(1-N) or vice versa. In a measurement campaign involving multiple remote devices, these parameters may be defined for all remote devices (i.e., for each remote device). When transmitted from the sensing device to the remote device, these parameters may configure the remote device sensing transmission, and when transmitted from the remote device to the sensing device, these parameters may report the configuration used by the remote device for sensing transmission.

[0192] According to some implementations, the details of the steering matrix components are set forth in Table 8. [Table 8-1] [Table 8-2]

[0193] In one example, the data provided in Table 8 may be encoded into elements for inclusion in messages between the sensing device 502 and the multiple remote devices 504-(1-N). In a measurement campaign involving multiple remote devices, these parameters may be defined for all devices. When transmitted from the sensing device 502 to the multiple remote devices 504-(1-N), the steering matrix configuration fills a lookup table (which can then be accessed via an index).

[0194] 19A-19C depict a flowchart 1900 for generating sensing measurements based on features of interest, according to some embodiments.

[0195] To summarize one implementation of the flowchart 1900, in step 1902, a first channel resource is allocated to a first expected transmission from a plurality of remote devices. In step 1904, a first sensing trigger message configured to trigger a first series of sensing transmissions from a plurality of remote devices is transmitted. In step 1906, a first series of sensing transmissions transmitted in response to the first sensing trigger message is received. In step 1908, a first series of sensing measurements is generated based on the first series of sensing transmissions. In step 1910, an identification of a feature of interest is obtained according to the first series of sensing measurements. In step 1912, a selection of a remote device is determined according to the feature of interest. In step 1914, a second channel resource is allocated to a second expected transmission from the selection of remote devices. In step 1916, a second sensing trigger message configured to trigger a second series of sensing transmissions from the selection of remote devices is transmitted. A second series of sensing transmissions transmitted in response to the second sensing trigger message is received at step 1918. At step 1920, a second series of sensing measurements is generated based on the second series of sensing transmissions.

[0196] Step 1902 includes allocating a first channel resource to a first expected transmission from a plurality of remote devices. In one implementation, the sensing agent 516 may be configured to allocate the first channel resource to a first expected transmission from a plurality of remote devices 504-(1-N). In one implementation, the sensing agent 516 may include the first channel resource in a first TXOP and allocate the first channel resource to the plurality of remote devices 504-(1-N) according to a scan mode. In one example, the sensing agent 516 may allocate the first channel resource by allocating time and bandwidth in the first TXOP to the plurality of remote devices 504-(1-N).

[0197] Step 1904 includes transmitting a first sensing trigger message configured to trigger a first series of sensing transmissions from the multiple remote devices. According to one implementation, the sensing agent 516 can transmit the first sensing trigger message configured to trigger a first series of sensing transmissions from the multiple remote devices 504-(1-N). In one example, the first sensing trigger message can be a scan type trigger message that includes a requested transmission configuration and a resource allocation subfield corresponding to a scan mode.

[0198] Step 1906 includes receiving a first series of sensing transmissions transmitted in response to the first sensing trigger message. In one implementation, the sensing agent 516 can receive the first series of sensing transmissions transmitted in response to the first sensing trigger message. In one example, the first series of sensing transmissions can correspond to a scan mode.

[0199] Step 1908 includes generating a first series of sensing measurements based on the first series of sensing transmissions. In one implementation, the sensing agent 516 can generate the first series of sensing measurements based on the first series of sensing transmissions. According to one implementation, the sensing agent 516 can process the first series of sensing transmissions to generate the first series of sensing measurements.

[0200] Step 1910 includes obtaining an identification of the feature of interest according to the first series of sensing measurements. In one implementation, obtaining an identification of the feature of interest may include identifying the feature of interest based on the first series of sensing measurements. In one implementation, in response to the first series of sensing measurements, the sensing agent 516 may identify the feature of interest.

[0201] Step 1912 includes determining a selection of remote devices according to the feature of interest, the selection of remote devices being a subset of the plurality of remote devices. In one example, determining the selection of remote devices includes selecting remote devices from the plurality of remote devices 504-(1-N) that are in the vicinity of the feature of interest for inclusion in the selection of remote devices. In one implementation, the sensing agent 516 can determine the selection of remote devices according to the feature of interest.

[0202] Step 1914 includes allocating a second channel resource to a second expected transmission from the selection of remote devices. In one implementation, the sensing agent 516 can allocate the second channel resource to the second expected transmission from the selection of remote devices according to the detection mode. According to one implementation, the sensing agent 516 may include the second channel resource in a second TXOP. In some examples, the sensing agent 516 may include the second channel resource with the same TXOP used to allocate the first channel resource.

[0203] Step 1916 includes transmitting a second sensing trigger message configured to trigger a second series of sensing transmissions from a selection of remote devices. According to one implementation, the sensing agent 516 can transmit a second sensing trigger message configured to trigger a second series of sensing transmissions from a selection of remote devices. In one example, the second sensing trigger message can be a detection type trigger message including a requested transmission configuration and a resource allocation subfield corresponding to a detection mode. In some examples, the second sensing trigger message can include a hybrid type trigger message. The hybrid type trigger message can be configured to trigger a first second series of sensing transmissions corresponding to a scan mode from a first group of remote devices and a second second series of sensing transmissions corresponding to a detection mode from a second group of remote devices.

[0204] Step 1918 includes receiving a second series of sensing transmissions transmitted in response to the second sensing trigger message. According to one implementation, the sensing agent 516 can receive the second series of sensing transmissions transmitted in response to the second sensing trigger message. In one example, the second series of sensing transmissions can correspond to a detection mode. In one example, the second series of sensing transmissions can correspond to a hybrid mode.

[0205] Step 1920 includes generating a second series of sensing measurements based on the second series of sensing transmissions. In one implementation, the sensing agent 516 can generate the second series of sensing measurements based on the second series of sensing transmissions. According to one implementation, the sensing agent 516 can execute a sensing algorithm to process the second series of sensing transmissions to generate the second series of sensing measurements. In one example, the second series of sensing measurements is of a higher resolution than the first series of sensing measurements.

[0206] 20A-20D depict a flowchart 2000 for generating sensing measurements based on multiple features of interest, according to some embodiments.

[0207] To summarize one implementation of the flowchart 2000, in step 2002, a first channel resource is allocated to a first expected transmission from a plurality of remote devices. In step 2004, a first sensing trigger message configured to trigger a first series of sensing transmissions from the plurality of remote devices is transmitted. In step 2006, a first series of sensing transmissions transmitted in response to the first sensing trigger message is received. In step 2008, a first series of sensing measurements is generated based on the first series of sensing transmissions. In step 2010, an identification of a feature of interest is obtained according to the first series of sensing measurements. The features of interest include a first feature of interest and a second feature of interest. In step 2012, a first selection of remote devices is determined according to the first feature of interest. In step 2014, a second selection of remote devices is obtained according to the second feature of interest. In step 2016, a first portion of the second channel resource is allocated to the first selection of remote devices. In step 2018, a second portion of the second channel resources is allocated to a second selection of remote devices. In step 2020, a second sensing trigger message is transmitted to trigger a second series of sensing transmissions from the first selection of remote devices and the second selection of remote devices. In step 2022, the second series of sensing transmissions transmitted in response to the second sensing trigger message are received. In step 2024, a second series of sensing measurements is generated based on the second series of sensing transmissions.

[0208] Step 2002 includes allocating a first channel resource to a first expected transmission from a plurality of remote devices. In one implementation, the sensing agent 516 may be configured to allocate the first channel resource to a first expected transmission from a plurality of remote devices 504-(1-N). In one implementation, the sensing agent 516 may include the first channel resource in a first TXOP and allocate the first channel resource to the plurality of remote devices 504-(1-N) according to a scan mode. In one example, the sensing agent 516 may allocate the first channel resource by allocating time and bandwidth in the first TXOP to the plurality of remote devices 504-(1-N).

[0209] Step 2004 includes transmitting a first sensing trigger message configured to trigger a first series of sensing transmissions from the multiple remote devices. According to one implementation, the sensing agent 516 can transmit the first sensing trigger message configured to trigger a first series of sensing transmissions from the multiple remote devices 504-(1-N). In one example, the first sensing trigger message can be a scan type trigger message that includes a requested transmission configuration and a resource allocation subfield corresponding to a scan mode.

[0210] Step 2006 includes receiving a first series of sensing transmissions transmitted in response to the first sensing trigger message. In one implementation, the sensing agent 516 can receive the first series of sensing transmissions transmitted in response to the first sensing trigger message. In one example, the first series of sensing transmissions can correspond to a scan mode.

[0211] Step 2008 includes generating a first series of sensing measurements based on the first series of sensing transmissions. In one implementation, the sensing agent 516 can generate the first series of sensing measurements based on the first series of sensing transmissions.

[0212] Step 2010 includes obtaining an identification of a feature of interest according to the first series of sensing measurements. In one example, the feature of interest may include a first feature of interest and a second feature of interest. In one implementation, the sensing agent 516 may identify the feature of interest based on the first series of sensing measurements.

[0213] Step 2012 includes determining a first selection of remote devices according to the first characteristic of interest. In one example, the first selection of remote devices may be a subset of the plurality of remote devices 504-(1-N). In one implementation, the sensing agent 516 may determine the first selection of remote devices according to the first characteristic of interest.

[0214] Step 2014 includes determining a second selection of remote devices according to the second characteristic of interest. In one example, the second selection of remote devices may be a subset of the plurality of remote devices 504-(1-N). In one implementation, the sensing agent 516 may determine the second selection of remote devices according to the second characteristic of interest.

[0215] Step 2016 includes allocating a first portion of the second channel resources to the first selection of remote devices. In one implementation, the sensing agent 516 can allocate a first portion of the second channel resources to the first selection of remote devices.

[0216] Step 2018 includes allocating a second portion of the second channel resources to the second selection of remote devices. In one implementation, the sensing agent 516 can allocate a second portion of the second channel resources to the second selection of remote devices.

[0217] Step 2020 includes transmitting a second sensing trigger message configured to trigger a second series of sensing transmissions from the first selection of remote devices and the second selection of remote devices. According to one implementation, the sensing agent 516 can transmit the second sensing trigger message configured to trigger a second series of sensing transmissions from the first selection of remote devices and the second selection of remote devices. In one example, the second sensing trigger message can be a detection type trigger message including a requested transmission configuration and a resource allocation subfield corresponding to a detection mode. In some examples, the second sensing trigger message can be a hybrid type trigger message including a requested transmission configuration and a resource allocation subfield corresponding to a hybrid mode.

[0218] Step 2022 includes receiving a second series of sensing transmissions transmitted in response to the second sensing trigger message. According to one implementation, the sensing agent 516 can receive the second series of sensing transmissions transmitted in response to the second sensing trigger message. In one example, the second series of sensing transmissions can correspond to a detection mode. In another example, the second series of sensing transmissions can correspond to a hybrid mode.

[0219] Step 2024 includes generating a second series of sensing measurements based on the second series of sensing transmissions. In one implementation, the sensing agent 516 can generate the second series of sensing measurements based on the second series of sensing transmissions. In one example, the second series of sensing measurements is of a higher resolution than the first series of sensing measurements.

[0220] FIG. 21 depicts a flowchart 2100 for identifying features of interest according to some embodiments.

[0221] To summarize one implementation of flowchart 2100, a first series of sensing measurements is received from a sensing device in step 2102. One or more features of interest are identified in response to the first series of sensing measurements in step 2104. In step 2106, identification of the one or more features of interest is transmitted to the sensing device.

[0222] Step 2102 includes receiving a first series of sensing measurements from a sensing device. According to one embodiment, the sensing algorithm device 506 may receive the first series of sensing measurements from the sensing device 502.

[0223] Step 2104 includes identifying one or more features of interest in response to the first series of sensing measurements. In one implementation, the sensing algorithm device 506 can identify one or more features of interest based on the first series of sensing measurements. According to one implementation, the sensing algorithm device 506 can execute a sensing algorithm to identify the one or more features of interest.

[0224] Step 2106 includes transmitting an identification of the one or more features of interest to the sensing device. According to one implementation, the sensing algorithm device 506 can transmit an identification of the one or more features of interest to the sensing device 502.

[0225] Particular embodiments include the following: Embodiment 1 is a system including a sensing receiver including a transmitting antenna, a receiving antenna, and at least one processor, the at least one processor includes the following steps: allocating, by the at least one processor, a first channel resource to a first expected transmission from a plurality of sensing transmitters; transmitting, via the transmitting antenna, a first sensing sounding trigger frame configured to trigger a first series of sensing transmissions from the plurality of sensing transmitters; receiving, via the receiving antenna, the first series of sensing transmissions transmitted in response to the first sensing sounding trigger frame; generating, by the at least one processor, a first series of sensing measurements based on the first series of sensing transmissions; obtaining an identification of a feature of interest according to the first series of sensing measurements; and the at least one processor is configured to execute instructions to: determine, by the at least one processor, a selection of a sensing transmitter according to the feature of interest, the selection of sensing transmitter being a subset of the plurality of sensing transmitters; allocate, by the at least one processor, second channel resources to a second expected transmission from the selection of sensing transmitters; transmit, via the transmit antenna, a second sensing sounding trigger frame configured to trigger a second series of sensing transmissions from the selection of sensing transmitters; receive, via the receive antenna, the second series of sensing transmissions transmitted in response to the second sensing sounding trigger frame; and generate, by the at least one processor, a second series of sensing measurements based on the second series of sensing transmissions.

[0226] Embodiment 2 is a system of embodiment 1, in which the first sensing sounding trigger frame is a scan type trigger message including a requested transmission configuration and a resource allocation subfield corresponding to a scan mode, and the second sensing sounding trigger frame is a detection type trigger message including a requested transmission configuration and a resource allocation subfield corresponding to a detection mode.

[0227] Embodiment 3 is a system of embodiment 1 or embodiment 2, in which a first channel resource is included within a first transmission opportunity, a first series of sensing transmissions corresponds to a scan mode, and the first channel resource is allocated to a plurality of sensing transmitters according to the scan mode, and a second channel resource is included within a second transmission opportunity, a second series of sensing transmissions corresponds to a detection mode, and the second channel resource is allocated to a selection of sensing transmitters according to the detection mode.

[0228] Embodiment 4 is a system of embodiments 1 to 3, in which the first channel resource and the second channel resource are included in the same transmission opportunity, the first series of sensing transmissions corresponds to a scan mode, and the first channel resource is allocated to multiple sensing transmitters according to the scan mode, and the second series of sensing transmissions corresponds to a detection mode, and the second channel resource is allocated to a selection of sensing transmitters according to the detection mode.

[0229] Embodiment 5 is a system of any one of embodiments 1 to 4, in which a first channel resource is included within a first transmission opportunity, a first series of sensing transmissions corresponding to a scan mode, a second channel resource is included within a second transmission opportunity, the second sensing sounding trigger frame includes a hybrid type trigger message, the hybrid type trigger message is configured to trigger a first second series of sensing transmissions corresponding to the scan mode from a first group of sensing transmitters and to trigger a second second series of sensing transmissions corresponding to a detection mode from a second group of sensing transmitters, a first portion of the second channel resource is allocated to a sensing transmission of the first second series of sensing transmissions received in response to the hybrid type trigger message, and a second portion of the second channel resource is allocated to a sensing transmission of the second second series of sensing transmissions received in response to the hybrid type trigger message.

[0230] Embodiment 6 is a system of embodiments 1 to 5, wherein the processor is further configured to execute instructions for allocating first channel resources, including allocating time and bandwidth within a transmission opportunity to multiple sensing transmitters.

[0231] Embodiment 7 is a system of embodiments 1 to 6, wherein the processor is further configured to execute instructions for obtaining, by at least one processor, identification information of the feature of interest by identifying the feature of interest in response to the first series of sensing measurements.

[0232] Example 8 is a system of any one of Examples 1 to 7, wherein the processor is further configured to execute instructions to obtain an identification of the feature of interest by transmitting a first series of sensing measurements to a sensing algorithm device and receiving, by at least one processor, an identification of the feature of interest from the sensing algorithm device.

[0233] Embodiment 9 is a system of any one of embodiments 1 to 8, wherein the processor is further configured to execute instructions to transmit a second sensing sounding trigger frame by transmitting a sensing sounding trigger frame configured to trigger a first group of sensing transmissions from a first group of sensing transmitters from the selection of sensing transmitters and to trigger a second group of sensing transmissions from a second group of sensing transmitters from the selection of sensing transmitters.

[0234] Embodiment 10 is a system of any one of embodiments 1 to 9, wherein the processor is further configured to execute instructions to transmit a first sensing sounding trigger frame configured to trigger a first group of sensing transmissions from a first group of sensing transmitters from the plurality of sensing transmitters and to trigger a second group of sensing transmissions from a second group of sensing transmitters from the plurality of sensing transmitters.

[0235] Example 11 is a system of any one of Examples 1 to 10, wherein the processor is further configured to execute instructions to determine a selection of a sensing transmitter by selecting a sensing transmitter from a plurality of sensing transmitters in the vicinity of the feature of interest for inclusion in the selection of the sensing transmitter.

[0236] A twelfth embodiment is the system of any one of the first to eleventh embodiments, wherein the second series of sensing measurements is of higher resolution than the first series of sensing measurements.

[0237] Embodiment 13 is a system of any one of embodiments 1 to 12, in which the features of interest include a first feature of interest and a second feature of interest, the processor is further configured to execute instructions for determining a selection of a sensing transmitter according to the features of interest by determining a first selection of a sensing transmitter according to the first feature of interest and determining a second selection of a sensing transmitter according to the second feature of interest, and the processor is further configured to execute instructions for allocating second channel resources to a second expected transmission from the selection of sensing transmitters by allocating a first portion of the second channel resources to the first selection of sensing transmitters and allocating a second portion of the second channel resources to the second selection of sensing transmitters.

[0238] Embodiment 14 is a system including a sensing receiver including a transmitting antenna, a receiving antenna, and at least one processor, the at least one processor being configured to execute instructions for: allocating, by the at least one processor, first channel resources to first expected transmissions from a first plurality of sensing transmitters, each of the first plurality of sensing transmitters being allocated a first respective portion of the first channel resources; generating, by the at least one processor, a series of sensing measurements based on the series of sensing transmissions; obtaining an identification of a feature of interest according to the series of sensing measurements; and allocating, by the at least one processor, second channel resources to a second plurality of sensing transmitters according to the identification of the feature of interest, each of the second plurality of sensing transmitters being allocated a second respective portion of the second channel resources, the second plurality of sensing transmitters being a subset of the first plurality of sensing transmitters, and at least one second respective portion of the second channel resources being greater than a corresponding first respective portion of the first channel resources.

[0239] Embodiment 15 is the system of embodiment 14, wherein at least one processor is further configured to transmit, via a transmit antenna, a sensing sounding trigger frame configured to trigger a series of sensing transmissions from a first plurality of sensing transmitters, and receive, via a receive antenna, the series of sensing transmissions transmitted in response to the sensing sounding trigger frame, and the sensing sounding trigger frame is a scan type trigger frame including a resource allocation subfield corresponding to a requested transmission configuration and scan mode.

[0240] Embodiment 16 is a system of embodiment 14 or embodiment 15, in which the first channel resource is included within the first transmission opportunity, the series of sensing transmissions is a first series of sensing transmissions corresponding to a scan mode, and the first channel resource is allocated to a first plurality of sensing transmitters according to the scan mode, and the second channel resource is included within the second transmission opportunity, and the second channel resource is allocated to a second plurality of sensing transmitters according to the detection mode.

[0241] Embodiment 17 is a system of embodiment 14 or embodiment 15, in which the first channel resource and the second channel resource are included within the same transmission opportunity, the series of sensing transmissions is a first series of sensing transmissions corresponding to a scanning mode, the first channel resource is allocated to a first plurality of sensing transmitters according to the scanning mode, and the second channel resource is allocated to a second plurality of sensing transmitters according to the detection mode.

[0242] An eighteenth embodiment is the system of any one of the fourteenth to seventeenth embodiments, in which allocating the first channel resource includes allocating time and bandwidth within a transmission opportunity to the first plurality of sensing transmitters.

[0243] Example 19 is a system of any one of Examples 14 to 18, in which obtaining identification information of the feature of interest includes identifying the feature of interest by at least one processor in response to the series of sensing measurements.

[0244] Embodiment 20 is a system of embodiments 14 to 19, in which obtaining identification information of the feature of interest includes transmitting a series of sensing measurements to a sensing algorithm device and receiving, by at least one processor, identification information of the feature of interest from the sensing algorithm device.

[0245] Example 21 is the system of Examples 14 to 20, in which allocating the second channel resources includes selecting a second plurality of sensing transmitters based on proximity to the feature of interest.

[0246] Embodiment 22 is a system of any one of embodiments 14 to 21, wherein the series of sensing measurements is a first series of sensing measurements, the series of sensing transmissions is a first series of sensing transmissions, and the at least one processor is further configured to generate a second series of sensing measurements having a higher resolution than the first series of sensing measurements based on the second series of sensing transmissions.

[0247] Embodiment 23 is a system of any of embodiments 14 to 22, in which the features of interest include a first feature of interest and a second feature of interest, and allocating the second channel resource based on identification information of the features of interest includes determining a first selection of a sensing transmitter according to the identification information of the first feature of interest, and determining a second selection of a sensing transmitter according to the identification information of the second feature of interest, and the first selection of a sensing transmitter and the second selection of a sensing transmitter constitute a second plurality of sensing transmitters.

[0248] Embodiment 24 is a system of any one of embodiments 15 to 23, in which a first channel resource is included within a first transmission opportunity, the series of sensing transmissions is a first series of sensing transmissions corresponding to a scan mode, a second channel resource is included within a second transmission opportunity, the second sensing sounding trigger frame includes a hybrid type trigger frame, the hybrid type trigger frame is configured to trigger a first second series of sensing transmissions corresponding to the scan mode from a first group of sensing transmitters and to trigger a second second series of sensing transmissions corresponding to the hybrid mode from a second group of sensing transmitters, a first portion of the second channel resource is allocated to a sensing transmission of the first second series of sensing transmissions received in response to the hybrid type trigger frame, and a second portion of the second channel resource is allocated to a sensing transmission of the second second series of sensing transmissions received in response to the hybrid type trigger frame.

[0249] Embodiment 25 is a system of embodiments 15 to 24, wherein the sensing sounding trigger frame is a first sensing sounding trigger frame, and the at least one processor is further configured to transmit a second sensing sounding trigger frame configured to trigger a first group of second sensing transmissions from a first group of sensing transmitters from the second plurality of sensing transmitters, and to trigger a second group of sensing transmissions from a second group of sensing transmitters from the second plurality of sensing transmitters.

[0250] Embodiment 26 is a system of embodiments 14 to 25, in which at least one processor is further configured to transmit, via a transmitting antenna, a sensing sounding trigger frame configured to trigger a series of sensing transmissions from a first plurality of sensing transmitters, and receive, via a receiving antenna, the series of sensing transmissions transmitted in response to the sensing sounding trigger frame, and transmitting the sensing sounding trigger frame includes transmitting a sensing sounding trigger frame configured to trigger a first group of sensing transmissions from a first group of sensing transmitters from the first plurality of sensing transmitters, and to trigger a second group of sensing transmissions from a second group of sensing transmitters from the first plurality of sensing transmitters.

[0251] Although various embodiments of the methods and systems have been described, these embodiments are exemplary and in no way limit the scope of the described methods or systems. Those skilled in the art may make changes in form and detail of the described methods and systems without departing from the broadest scope of the described methods and systems. Thus, the scope of the methods and systems described herein should not be limited by any of the exemplary embodiments, but should be defined according to the appended claims and their equivalents.

Claims

1. 1. A method for Wi-Fi sensing performed by a sensing receiver including a transmitting antenna, a receiving antenna, and at least one processor configured to execute instructions, comprising: allocating, by the at least one processor, first channel resources to a first plurality of sensing transmitters, the first channel resources for each of the first plurality of sensing transmitters being a first respective portion of a channel bandwidth; generating, by the at least one processor, a sequence of sensing measurements based on the sequence of sensing transmissions from each of the first plurality of sensing transmitters; allocating, by the at least one processor, second channel resources to a second plurality of sensing transmitters; a second channel resource for each of the second plurality of sensing transmitters is a second respective portion of the channel bandwidth; the second plurality of sensing transmitters is a subset of the first plurality of sensing transmitters; The method, wherein the second channel resource of at least one sensing transmitter of the second plurality of sensing transmitters is greater than the first channel resource of that sensing transmitter.

2. transmitting, via the transmit antenna, a sensing trigger frame configured to trigger the sequence of sensing transmissions from each of the first plurality of sensing transmitters; receiving, via the receiving antenna, the sequence of sensing transmissions transmitted in response to the sensing trigger frame; The method of claim 1 , wherein the sensing trigger frame is a scan type trigger frame that includes a resource allocation subfield corresponding to a requested transmission configuration and scan mode.

3. the first channel resource is included within a first transmission opportunity; the series of sensing transmissions is a first series of sensing transmissions corresponding to a scan mode; the first channel resources are allocated to the first plurality of sensing transmitters according to the scanning mode; the second channel resource is included within a second transmission opportunity; The method of claim 1 , wherein the second channel resources are allocated to the second plurality of sensing transmitters according to a detection mode.

4. the first channel resource and the second channel resource are included within the same transmission opportunity; the series of sensing transmissions is a first series of sensing transmissions corresponding to a scan mode; the first channel resources are allocated to the first plurality of sensing transmitters according to the scanning mode; The method of claim 1 , wherein the second channel resources are allocated to the second plurality of sensing transmitters according to a detection mode.

5. The method of claim 1 , wherein allocating the first channel resources comprises allocating time and bandwidth resources within a transmission opportunity to the first plurality of sensing transmitters.

6. obtaining an identity of a feature of interest according to the series of sensing measurements; allocating the second channel resources in accordance with the identification of the feature of interest; The method of claim 1 , wherein obtaining the identification of the feature of interest comprises identifying, by the at least one processor, the feature of interest in response to the series of sensing measurements.

7. Obtaining the identification of the feature of interest comprises: transmitting, by the at least one processor, the set of sensing measurements to a sensing algorithm device; and receiving, by the at least one processor, the identification of the feature of interest from the sensing algorithm device.

8. The method of claim 6 , wherein allocating the second channel resources includes selecting the second plurality of sensing transmitters based on proximity to the feature of interest.

9. The series of sensing measurements is a first series of sensing measurements, the series of sensing transmissions is a second series of sensing transmissions, and the method further comprises: The method of claim 1 , further comprising generating a second series of sensing measurements based on a second series of sensing transmissions, the second series having a higher resolution than the first series of sensing measurements.

10. the features of interest include a first feature of interest and a second feature of interest; Allocating the second channel resources based on the identification of the feature of interest comprises: determining a first selection of a sensing transmitter according to an identity of the first feature of interest; determining a second selection of a sensing transmitter according to the identity of the second feature of interest; The method of claim 7 , wherein the first selection of sensing transmitters and the second selection of sensing transmitters constitute the second plurality of sensing transmitters.

11. the first channel resource is included within a first transmission opportunity; the series of sensing transmissions is a first series of sensing transmissions corresponding to a scan mode; the second channel resource is included within a second transmission opportunity; the second sensing trigger frame comprises a hybrid type trigger frame, the hybrid type trigger frame configured to trigger a first second series of sensing transmissions from a first group of sensing transmitters corresponding to the scan mode and to trigger a second series of sensing transmissions from a second group of sensing transmitters corresponding to a hybrid mode; a first portion of the second channel resources is allocated to a sensing transmission of the first second series of sensing transmissions received in response to the hybrid-type trigger frame; The method of claim 2 , wherein a second portion of the second channel resources is allocated to a sensing transmission of the second series of sensing transmissions received in response to the hybrid-type trigger frame.

12. the sensing trigger frame is a first sensing trigger frame, The at least one processor 3. The method of claim 2, further configured for transmitting a second sensing trigger frame configured to trigger a first group of second sensing transmissions from a first group of sensing transmitters of the second plurality of sensing transmitters and to trigger a second group of sensing transmissions from a second group of sensing transmitters of the second plurality of sensing transmitters.

13. transmitting, via the transmit antenna, a sensing trigger frame configured to trigger the sequence of sensing transmissions from the first plurality of sensing transmitters; receiving, via the receiving antenna, the sequence of sensing transmissions transmitted in response to the sensing trigger frame; 2. The method of claim 1 , wherein transmitting the sensing trigger frame includes transmitting the sensing trigger frame configured to trigger a first group of sensing transmissions from a first group of sensing transmitters of the first plurality of sensing transmitters and to trigger a second group of sensing transmissions from a second group of sensing transmitters of the first plurality of sensing transmitters.

14. 1. A system comprising: a sensing receiver including a transmitting antenna, a receiving antenna, and at least one processor; The at least one processor allocating, by the at least one processor, first channel resources to a first plurality of sensing transmitters, the first channel resources for each of the first plurality of sensing transmitters being a first respective portion of a channel bandwidth; generating, by the at least one processor, a sequence of sensing measurements based on the sequence of sensing transmissions from each of the first plurality of sensing transmitters; and configured to execute instructions, by the at least one processor, to allocate second channel resources to a second plurality of sensing transmitters; a second channel resource for each of the second plurality of sensing transmitters is a second respective portion of the channel bandwidth; the second plurality of sensing transmitters is a subset of the first plurality of sensing transmitters; The second channel resource of at least one sensing transmitter of the second plurality of sensing transmitters is greater than the first channel resource of that sensing transmitter.

15. The at least one processor transmitting, via the transmit antenna, a sensing trigger frame configured to trigger the sequence of sensing transmissions from each of the first plurality of sensing transmitters; receiving, via the receive antenna, the sequence of sensing transmissions transmitted in response to the sensing trigger frame; 15. The system of claim 14, wherein the sensing trigger frame is a scan type trigger frame that includes a resource allocation subfield corresponding to a requested transmission configuration and scan mode.

16. the first channel resource is included within a first transmission opportunity; the series of sensing transmissions is a first series of sensing transmissions corresponding to a scan mode; the first channel resources are allocated to the first plurality of sensing transmitters according to the scanning mode; the second channel resource is included within a second transmission opportunity; The system of claim 14 , wherein the second channel resources are allocated to the second plurality of sensing transmitters according to a detection mode.

17. the first channel resource and the second channel resource are included within the same transmission opportunity; the series of sensing transmissions is a first series of sensing transmissions corresponding to a scan mode; the first channel resources are allocated to the first plurality of sensing transmitters according to the scanning mode; The system of claim 14 , wherein the second channel resources are allocated to the second plurality of sensing transmitters according to a detection mode.

18. 15. The system of claim 14, wherein allocating the first channel resources comprises allocating time and bandwidth resources within a transmission opportunity to the first plurality of sensing transmitters.

19. obtaining an identity of a feature of interest according to the series of sensing measurements; allocating the second channel resources in accordance with the identification of the feature of interest; The system of claim 14 , wherein obtaining the identification of the feature of interest comprises identifying, by the at least one processor, the feature of interest in response to the series of sensing measurements.

20. Obtaining the identification of the feature of interest comprises: transmitting, by the at least one processor, the set of sensing measurements to a sensing algorithm device; and receiving, by the at least one processor, the identification of the feature of interest from the sensing algorithm device.

21. 20. The system of claim 19, wherein allocating the second channel resources includes selecting the second plurality of sensing transmitters based on proximity to the feature of interest.

22. The series of sensing measurements is a first series of sensing measurements, the series of sensing transmissions is a second series of sensing transmissions, and the at least one processor is configured to: The system of claim 14 , further configured to generate a second series of sensing measurements based on a second series of sensing transmissions, the second series of sensing measurements having a higher resolution than the first series of sensing measurements.

23. the features of interest include a first feature of interest and a second feature of interest; Allocating the second channel resources based on the identification of the feature of interest comprises: determining a first selection of a sensing transmitter according to an identity of the first feature of interest; determining a second selection of a sensing transmitter according to the identity of the second feature of interest; 21. The system of claim 20, wherein the first selection of sensing transmitters and the second selection of sensing transmitters constitute the second plurality of sensing transmitters.

24. the first channel resource is included within a first transmission opportunity; the series of sensing transmissions is a first series of sensing transmissions corresponding to a scan mode; the second channel resource is included within a second transmission opportunity; the second sensing trigger frame includes a hybrid type trigger frame configured to trigger a first second series of sensing transmissions from a first group of sensing transmitters corresponding to the scan mode and to trigger a second series of sensing transmissions from a second group of sensing transmitters corresponding to a hybrid mode; a first portion of the second channel resources is allocated to a sensing transmission of the first second series of sensing transmissions received in response to the hybrid-type trigger frame; 16. The system of claim 15, wherein a second portion of the second channel resources is allocated to a sensing transmission of the second series of sensing transmissions received in response to the hybrid-type trigger frame.

25. the sensing trigger frame is a first sensing trigger frame, The at least one processor 16. The system of claim 15, further configured to transmit a second sensing trigger frame configured to trigger a first group of second sensing transmissions from a first group of sensing transmitters of the second plurality of sensing transmitters and to trigger a second group of sensing transmissions from a second group of sensing transmitters of the second plurality of sensing transmitters.

26. The at least one processor transmitting, via the transmit antenna, a sensing trigger frame configured to trigger the sequence of sensing transmissions from the first plurality of sensing transmitters; receiving, via the receive antenna, the sequence of sensing transmissions transmitted in response to the sensing trigger frame; 15. The system of claim 14, wherein transmitting the sensing trigger frame includes transmitting the sensing trigger frame configured to trigger a first group of sensing transmissions from a first group of sensing transmitters of the first plurality of sensing transmitters and to trigger a second group of sensing transmissions from a second group of sensing transmitters of the first plurality of sensing transmitters.

27. 1. A method for Wi-Fi sensing performed by a sensing initiator including at least one transmit antenna, at least one receive antenna, and at least one processor configured to execute instructions, comprising: allocating, by the at least one processor, channel resources to a plurality of sensing responders, the channel resources for each of the plurality of sensing responders being a portion of a channel bandwidth; obtaining, by the at least one processor, a first sensing measurement based on a first sensing transmission from each of a first plurality of sensing responders, the first plurality of sensing responders being a first subset of the plurality of sensing responders, the first sensing transmission being received during a negotiated time interval for a frame exchange; obtaining, by the at least one processor, second sensing measurements based on second sensing transmissions from each of a second plurality of sensing responders, the second plurality of sensing responders being a second subset of the plurality of sensing responders, the second sensing transmissions being received during the negotiated time interval for a frame exchange; A method comprising:

28. 28. The method of claim 27, wherein the negotiated time interval for frame exchange is a transmission opportunity (TXOP).

29. 30. The method of claim 27, wherein the first subset of the plurality of sensing responders and the second subset of the plurality of sensing responders are non-overlapping.

30. transmitting, via the at least one transmit antenna, a first sensing trigger frame configured to trigger the first sensing transmissions from the first subset of the plurality of sensing responders; 30. The method of claim 27, further comprising: receiving, via the at least one receive antenna, the first sensing transmission transmitted in response to the first sensing trigger frame.

31. 30. The method of claim 29, wherein the first sensing trigger frame includes at least one of a requested transmission configuration and a resource allocation subfield.

32. 30. The method of claim 28, wherein allocating the channel resources comprises allocating at least one of time and bandwidth resources within the TXOP to the multiple sensing responders.

33. 33. The method of claim 32, further comprising transmitting a resource allocation message to at least one of the first subset of the plurality of sensing responders and the second subset of the plurality of sensing responders, the resource allocation message including information regarding allocated channel resources.

34. transmitting, via the at least one transmit antenna, a second sensing trigger frame configured to trigger the second sensing transmissions from the second subset of the plurality of sensing responders; 31. The method of claim 30, further comprising: receiving, via the at least one receive antenna, the second sensing transmission transmitted in response to the second sensing trigger frame.

35. 35. The method of claim 34, wherein the second sensing trigger frame is transmitted one short interframe space (SIFS) after the period during which the first sensing transmission is received.

36. 1. A system for Wi-Fi sensing, comprising: A sensing initiator including at least one transmitting antenna, at least one receiving antenna, and at least one processor; The at least one processor allocating, by the at least one processor, channel resources to a plurality of sensing responders, the channel resources for each of the plurality of sensing responders being a portion of a channel bandwidth; obtaining, by the at least one processor, a first sensing measurement based on a first sensing transmission from each of a first plurality of sensing responders, the first plurality of sensing responders being a first subset of the plurality of sensing responders, the first sensing transmission being received during a negotiated time interval for a frame exchange; obtaining, by the at least one processor, second sensing measurements based on second sensing transmissions from each of a second plurality of sensing responders, the second plurality of sensing responders being a second subset of the plurality of sensing responders, the second sensing transmissions being received during the negotiated time interval for a frame exchange; 23. A system configured to execute instructions to:

37. 37. The system of claim 36, wherein the negotiated time interval for exchanging frames is a transmission opportunity (TXOP).

38. 37. The system of claim 36, wherein the first subset of the plurality of sensing responders and the second subset of the plurality of sensing responders are non-overlapping.

39. The at least one processor transmitting, via the at least one transmit antenna, a first sensing trigger frame configured to trigger the first sensing transmissions from the first subset of the plurality of sensing responders; receiving, via the at least one receive antenna, the first sensing transmission transmitted in response to the first sensing trigger frame; 37. The system of claim 36, further configured to execute instructions to:

40. 40. The system of claim 39, wherein the first sensing trigger frame includes at least one of a requested transmission configuration and a resource allocation subfield.

41. 40. The system of claim 37, wherein allocating the channel resources comprises allocating at least one of time and bandwidth resources within the TXOP to the multiple sensing responders.

42. 42. The system of claim 41, further comprising transmitting a resource allocation message including information regarding allocated channel resources to at least one of the first subset of the plurality of sensing responders and the second subset of the plurality of sensing responders.

43. The at least one processor transmitting, via the at least one transmit antenna, a second sensing trigger frame configured to trigger the second sensing transmissions from the second subset of the plurality of sensing responders; receiving, via the at least one receive antenna, the second sensing transmission transmitted in response to the second sensing trigger frame; 40. The system of claim 39, further configured to execute instructions to:

44. 44. The system of claim 43, wherein the second sensing trigger frame is transmitted one short interframe space (SIFS) after the period during which the first sensing transmission is received.

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