Isolating electronic environments to improve channel estimation

Abstract

Systems and methods for Wi-Fi sensing are provided. A method for Wi-Fi sensing is performed by a sensing decision unit operating on at least one processor configured to execute instructions. Measured channel state information (M-CSI) representing a sensing measurement and receiver front-end state information (RFE-SI) are received. Sensing decision input information is determined from the RFE-SI.

Description

[0001] This application is a divisional application of Inventive Patent Application 202280072108.4, filed October 26, 2022, entitled “Isolating Electronic Environments to Improve Channel Estimation.”

[0002] Cross Reference to Related Applications

[0003] This application claims the benefit of U.S. Provisional Application No. 63 / 273,572, filed October 29, 2021, and U.S. Provisional Application No. 63 / 284,305, filed November 30, 2021, the entire contents of which are incorporated herein by reference. TECHNICAL FIELD

[0004] The present disclosure relates generally to systems and methods for Wi-Fi sensing. In particular, the present disclosure relates to systems and methods for isolating electronic environments to improve channel estimation. BACKGROUND

[0005] Motion detection systems have been used to detect movement of objects, for example, in indoor or outdoor areas. In some example motion detection systems, infrared or optical sensors are used to detect movement of objects in the field of view of the sensors. Motion detection systems have been used in security systems, automated control systems, and other types of systems. Wi-Fi sensing systems are a recent addition to motion detection systems. A Wi-Fi sensing system can be a network of Wi-Fi enabled devices, which can be part of an IEEE 802.11 network. In an example, a Wi-Fi sensing system can be configured to detect features of interest in a sensing space. A sensing space can refer to any physical space in which a Wi-Fi sensing system can operate, such as a residential premises, a workplace, a shopping center, a gym or stadium, a garden, or any other physical space. Features of interest can include motion and motion tracking of objects, presence detection, intrusion detection, gesture recognition, fall detection, respiration rate detection, and other applications.

[0006] In a Wi-Fi sensing system, Wi-Fi sensing can be performed based on detecting perturbations in an over-the-air (OTA) channel, which is defined as the propagation of a transmitted signal between a transmitter antenna and a receiver antenna. The OTA channel is the wireless channel between the transmitter antenna and the receiver antenna. In an example, the transmitted signal can be generated at a baseband transmitter and received at a baseband receiver. Additionally, the received signal can be processed at the baseband receiver to determine channel state information (CSI). The CSI can be used to determine motion of an object in a sensing space. In addition to the CSI of the OTA channel, the CSI obtained through the processing of the received signal by the baseband receiver can also include perturbations that occur in or are caused by front-end components in the baseband transmitter and the baseband receiver. Since the perturbations caused by the front-end components are not a result of motion occurring in the sensing space by an object, for accurate Wi-Fi sensing, the CSI used to determine motion should only include perturbations occurring in the OTA channel and not include any perturbations occurring in or caused by the front-end components in the baseband transmitter and the baseband receiver. SUMMARY

[0007] The present disclosure relates generally to systems and methods for Wi-Fi sensing. In particular, the present disclosure relates to systems and methods for isolating an electronic environment to improve channel estimation.

[0008] Systems and methods for Wi-Fi sensing are provided. In an example embodiment, a method for Wi-Fi sensing is described. The method is performed by a sensing decision unit operating on at least one processor. The method includes receiving, by the sensing decision unit, measured channel state information (M-CSI) representing sensing measurements; receiving, by the sensing decision unit, receiver front-end state information (RFE-SI); and determining, by the sensing decision unit and in accordance with the RFE-SI, sensing decision input information.

[0009] In some embodiments, the method further includes receiving, by a receiving device including a receiver front-end (RFE) having a receive antenna, sensing transmissions from a plurality of sensing transmitters; and generating, by the receiving device, the M-CSI based on the sensing transmissions.

[0010] In some embodiments, the receiving device further includes the at least one processor.

[0011] In some embodiments, the RFE-SI is provided by a baseband processor of the receiving device to the sensing decision unit as a message.

[0012] In some embodiments, the RFE-SI is provided as one or more digital signals by at least one of a baseband processor of the receiving device and the RFE to the sensing decision unit.

[0013] In some embodiments, the RFE-SI is provided as one or more digital signals and one or more analog signals by at least one of a baseband processor of the receiving device and the RFE to the sensing decision unit.

[0014] In some embodiments, the RFE-SI includes a phase change indicator.

[0015] In some embodiments, determining the sensing decision input information includes setting the sensing decision input information to a null input in response to a determination that the phase change indicator indicates a phase change in the M-CSI.

[0016] In some embodiments, the RFE-SI includes automatic gain controller (AGC) information.

[0017] In some embodiments, determining the sensing decision input information includes setting the sensing decision input information to a null input in response to a determination that the AGC information does not exceed a first threshold.

[0018] In some embodiments, determining the sensing decision input information includes: generating processed channel state information (P-CSI) by multiplying a portion of the M-CSI by an AGC scaling factor in response to a determination that the AGC information does not exceed a first threshold; and setting the sensing decision input information to the P-CSI.

[0019] In some embodiments, determining the sensing decision input information includes: generating processed channel state information (P-CSI) by multiplying a portion of the M-CSI by an AGC scaling factor in response to a first determination that the AGC information does not exceed a first threshold and a second determination that a root mean square of the portion of the M-CSI does not exceed a second threshold; and setting the sensing decision output information to the P-CSI.

[0020] In some embodiments, determining the sensing decision input information includes: setting the sensing decision input information to the M-CSI in response to a first determination that the AGC information exceeds a first threshold and a second determination that a root mean square of the portion of the M-CSI exceeds a second threshold.

[0021] In some embodiments, the RFE-SI includes downconverter type information.

[0022] In some embodiments, determining the sensing decision input information includes calculating a group delay of the M-CSI according to the downconverter type information, generating processed channel state information (P-CSI) by adjusting the M-CSI according to the group delay, and setting the sensing decision input information to the P-CSI.

[0023] In some embodiments, the method further includes sending the sensing decision input information to a sensing algorithm manager.

[0024] In another example embodiment, a system for Wi-Fi sensing is described. The system includes at least one processor configured to execute instructions to operate a sensing decision unit, the instructions configured to receive, by the sensing decision unit, M-CSI representing sensing measurements; receive, by the sensing decision unit, RFE-SI; and determine, by the sensing decision unit and according to the RFE-SI, sensing decision input information.

[0025] Other aspects and advantages of the disclosure will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, illustrated by way of example of the principles of the disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0026] The foregoing and other objects, aspects, features, and advantages of the present disclosure will become more apparent and can be better understood with reference to the following description, taken in conjunction with the accompanying drawings, in which:

[0027] Figure 1 is a diagram illustrating an example wireless communication system;

[0028] Figure 2A and Figure 2B is a diagram illustrating example wireless signals communicated between wireless communication devices;

[0029] Figure 3A and Figure 3B is a diagram illustrating an example channel response calculated from wireless signals communicated between wireless communication devices in Figure 2A and Figure 2B

[0030] Figure 4A and Figure 4B is a diagram illustrating example channel responses associated with motion of objects in different regions of a space;

[0031] Figure 4C and Figure 4D is a diagram illustrating Figure 4A and Figure 4B ​a plot of an example channel response superimposed on an example channel response associated with no motion occurring in space;

[0032] Figure 5 An embodiment depicting some architecture of an embodiment of a system for Wi-Fi sensing according to some embodiments;

[0033] Figure 6 An embodiment depicting measured channel versus over-the-air (OTA) channel according to some embodiments;

[0034] Figure 7 An embodiment depicting a representation of a receiver chain of a receiving device according to some embodiments;

[0035] Figure 8 An embodiment depicting a receiver front-end (RFE) perturbation correction architecture according to some embodiments;

[0036] Figure 9 An embodiment depicting an instance of receiver front-end state information (RFE-SI) in a RFE perturbation correction architecture according to some embodiments;

[0037] Figure 10 An embodiment depicting a structure of a phase-locked loop (PLL) unit according to some embodiments;

[0038] Figure 11 An embodiment depicting an instance of group delay of an ideal channel according to some embodiments;

[0039] Figure 12 An embodiment depicting a block diagram of a zero intermediate frequency (zero-IF) downconverter with two branches according to some embodiments;

[0040] Figure 13A and Figure 13B An embodiment depicting characteristics of an instance of a notch filter according to some embodiments;

[0041] Figure 14 An embodiment depicting a block diagram of a two-stage low-IF downconverter with two branches according to some embodiments;

[0042] Figure 15 An embodiment depicting a flowchart for determining sensing decision input information according to some embodiments;

[0043] Figure 16 An embodiment depicting a flowchart for sending measured channel state information to a sensing decision unit according to some embodiments;

[0044] Figure 17 An embodiment depicting a flowchart for determining sensing decision input information from RFE-SI according to some embodiments, where the RFE-SI includes a phase change indicator;

[0045] Figure 18 A flowchart depicting determining sensing decision input information from RFE-SI, where the RFE-SI contains downconverter type information, is depicted in accordance with some embodiments; and

[0046] Figure 19A and Figure 19B A flowchart depicting determining sensing decision input information from RFE-SI, where the RFE-SI contains automatic gain controller (AGC) information, is depicted in accordance with some embodiments. DETAILED DESCRIPTION

[0047] In some aspects of the content described herein, a wireless sensing system can be used for various wireless sensing applications by processing wireless signals (e.g., radio frequency signals) transmitted through space between wireless communication devices. Example wireless sensing applications include motion detection, which can include detecting motion of objects in a space, motion tracking, breath detection, breath monitoring, presence detection, gesture detection, gesture recognition, human body detection (moving and stationary human body detection), human body tracking, fall detection, velocity estimation, intrusion detection, walking detection, step count, breath rate detection, apnea estimation, posture change detection, activity recognition, gait rate classification, hand gesture decoding, sign language recognition, hand tracking, heart rate estimation, breath rate estimation, room occupancy detection, human body 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, campus violence detection, human body counting, metal detection, human body identification, bicycle localization, human body queue estimation, Wi-Fi imaging, and other types of wireless sensing applications. For example, a wireless sensing system can 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, a wireless sensing system can be configured to control measurement rate, wireless connectivity, and device participation, for example, to improve system operation or achieve other technical advantages. In examples where a wireless sensing system is used for another type of wireless sensing application, the system improvements and technical advantages achieved when a wireless sensing system is used for motion detection are also achieved.

[0048] In some example wireless sensing systems, wireless signals contain components (e.g., synchronization preambles in Wi-Fi PHY frames, or another type of component) that wireless devices can use to estimate channel responses 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 channel information collected over time. In some instances, the wireless sensing system can operate similarly to a bistatic radar system, with a Wi-Fi access point (AP) assuming the receiver role and each Wi-Fi device (station or node or peer) connected to the AP assuming the transmitter role. The wireless sensing system can trigger the connected devices to generate transmissions and produce channel response measurements at the receiver device. This triggering process can be repeated periodically to obtain a series of time-varying measurements. A wireless sensing algorithm can then receive the time series of generated channel response measurements (e.g., computed by the Wi-Fi receiver) as input and, through a correlation or filtering process, can then make a determination (e.g., determine whether motion is present within the environment represented by the channel responses, for example, based on changes or patterns in the channel estimates). In instances where the wireless sensing system detects motion, the location of the motion within the environment can also be identified based on the motion detection results from multiple wireless devices.

[0049] Accordingly, wireless signals received at each of the wireless communication devices in the wireless communication network can be analyzed to determine channel information for various communication links (between respective pairs of wireless communication devices) in the network. The channel information can represent the physical medium that applies a transfer function to a wireless signal traversing the space. In some cases, the channel information includes a channel response. The channel response can characterize the physical communication path representing, for example, the combined effects of scattering, fading, and power attenuation within 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 typically used in multiple antenna (multiple-input / multiple-output (MIMO)) radio systems for directional signal transmission or reception. Beamforming can be achieved by operating elements in an antenna array in such a way that signals of a particular angle experience constructive interference, while signals of other angles experience destructive interference.

[0050] The channel information for each of the communication links can be analyzed (e.g., by a hub device or other device in the wireless communication network, or a sensing transmitter communicably coupled to the network) to, for example, detect whether motion has occurred in the space, determine a relative location of the detected motion, or both. In some aspects, the channel information for each of the communication links can be analyzed to detect whether an object is present, for example, when no motion is detected in the space.

[0051] In some cases, a wireless sensing system can control node measurement rates. For example, a Wi-Fi motion system can configure variable measurement rates (e.g., channel estimation / environment measurement / sampling rates) based on criteria given by the current wireless sensing application (e.g., motion detection). In some embodiments, for example, when there is no motion present or detected for a period of time, the wireless sensing system can reduce the rate of measuring the environment such that the frequency of connected devices being triggered is reduced. In some embodiments, for example, when there is motion, the wireless sensing system can increase the triggering rate to produce a time series of measurements with finer time resolution. Controlling variable measurement rates can enable energy savings (through device triggering), reduce processing (reducing data to correlate or filter), and improve resolution during a specified time.

[0052] In some cases, a wireless sensing system can perform band steering or client steering to nodes in an entire wireless network, for example, in a Wi-Fi multi-AP or extended service set (ESS) topology, multiple coordinating wireless APs each provide a basic service set (BSS) that can occupy different frequency bands and allow devices to move transparently between one participating AP to another (e.g., mesh). For example, in a home mesh network, Wi-Fi devices can connect to any of the APs, but typically choose the AP with good signal strength. The coverage footprint of mesh APs often overlap, typically placing each device within communication range or more than one AP. If the APs support multiple frequency bands (e.g., 2.4 GHz and 5 GHz), the wireless sensing system can keep the device connected to the same physical AP but instruct the wireless sensing system to use different frequency bands to obtain more diverse information, thereby helping to improve the accuracy or results of wireless sensing algorithms (e.g., motion detection algorithms). In some embodiments, the wireless sensing system can change a device from connecting to one mesh AP to connecting to another mesh AP. Such device steering can be performed based on criteria detected in a particular area during wireless sensing (e.g., motion detection), for example, to improve detection coverage or better locate motion within an area.

[0053] In some cases, beamforming can be performed between wireless communication devices based on some knowledge of the communication channel (e.g., through feedback properties generated by a receiver), which can be used to generate one or more steering properties (e.g., steering matrices) applied by a transmitter device to shape the transmitted beam / signal in one or more specific directions. Thus, changes in the steering or feedback properties used in the beamforming process indicate changes in the space accessed by the wireless communication system that can be caused by a moving object. For example, motion can be detected through substantial changes in the communication channel over a period of time, for example, as indicated by channel responses, or steering or feedback properties, or any combination thereof.

[0054] In some embodiments, for example, a steering matrix can be generated at a transmitter device (beamforming transmitting end) based on a feedback matrix provided by a receiver device (beamforming receiving end) based on channel sounding. Because the steering matrix and the feedback matrix are related to the propagation characteristics of the channel, these matrices change as objects move within the channel. Changes in the channel characteristics are reflected in these matrices accordingly, and by analyzing the matrices, motion can be detected and different characteristics of the detected motion can be determined. In some embodiments, a spatial map can be generated based on one or more beamforming matrices. The spatial map can indicate the general direction of objects in the space relative to the wireless communication device. In some cases, many beamforming matrices (e.g., feedback matrices or steering matrices) can be generated to represent a plurality of directions in which objects can be positioned relative to the wireless communication device. These many beamforming matrices can be used to generate a spatial map. The spatial map can be used to detect the presence of motion in the space or to detect the location of the detected motion.

[0055] In some cases, a motion detection system can control a variable device measurement rate in a motion detection process. For example, a feedback control system for a multi-node wireless motion detection system can adaptively change a sampling rate based on environmental conditions. In some cases, such control can improve the operation of a motion detection system or provide other technical advantages. For example, the measurement rate can be controlled in a way that optimizes or otherwise improves air interface time usage relative to detection capabilities suitable for a wide range of different environments and different motion detection applications. The measurement rate can be controlled in a way that reduces redundant measurement data to be processed, thereby reducing processor load / power requirements. In some cases, the measurement rate is controlled in an adaptive manner, for example, adaptive sampling can be controlled individually for each participating device. Adaptive sampling rates can be used with different use cases or device characteristics with a tuning control loop.

[0056] In some cases, a wireless sensing system can allow devices to dynamically indicate their wireless sensing capabilities or willingness and communicate them to the wireless sensing system. For example, sometimes a device can not want to be periodically interrupted or triggered to transmit wireless signals that would allow an AP to produce channel measurements. For example, if a device is in a sleep state, frequently waking the device to transmit or receive wireless sensing signals can consume resources (e.g., cause a cell phone battery to discharge faster). These and other events can make a device willing or unwilling to participate in wireless sensing system operations. In some cases, a cell phone operating using a battery can not want to participate, but when the cell phone is plugged into a charger, the cell phone can be willing to participate. Thus, if the cell phone is unplugged, the wireless sensing system can be indicated to exclude the cell phone from participating; and if the cell phone is plugged in, the wireless sensing system can be indicated to include the cell phone in wireless sensing system operations. In some cases, if a device is under load (e.g., the device is streaming audio or video) or is busy performing a primary function, the device can not want to participate; and when the load of the same device is reduced and participation would not interfere with the primary function, the device can indicate to the wireless sensing system that it is willing to participate.

[0057] The example wireless sensing system is described below in the context of motion detection (detecting motion of objects in a space, motion tracking, respiration detection, respiration monitoring, presence detection, gesture detection, gesture recognition, human detection (moving and stationary human detection), human tracking, fall detection, velocity estimation, intrusion detection, walking detection, step count, 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 operations, system improvements, and technical advantages achieved when the wireless sensing system operates as a motion detection system also apply in instances where the wireless sensing system is used for another type of wireless sensing application.

[0058] In various embodiments of the present disclosure, non-limiting definitions of one or more terms to be used in the document are provided below.

[0059] The term "transmit parameters" can refer to a set of IEEE 802.11 PHY transmitter configuration parameters defined as part of the transmission vector (TXVECTOR) corresponding to a particular PHY and configurable for each PHY layer protocol data unit (PPDU) transmission.

[0060] The term "null data PPDU (NDP)" can refer to a PPDU that does not contain a data field. In an example, a null data PPDU can be used for a sensing transmission, where it is the MAC header that contains the required information.

[0061] The term "channel state information (CSI)" can refer to known or measured properties of a communication channel through channel estimation techniques. CSI can represent how a wireless signal propagates along multiple paths from a sensing transmitter to a sensing receiver. CSI is typically a complex-valued matrix that represents the amplitude attenuation and phase shift of a signal, which provides an estimate of the communication channel.

[0062] The term "sensing transmitter" can refer to a device that transmits a transmission (e.g., PPDU) for sensing measurements (e.g., channel state information) in a sensing session. In an example, a station is an example of a sensing transmitter. In some examples, an access point can also be a sensing transmitter for Wi-Fi sensing purposes, in examples where the station functions as an example of a sensing receiver.

[0063] The term "sensing receiver" can refer to a device that receives a transmission (e.g., PPDU) transmitted by a sensing transmitter and performs one or more sensing measurements (e.g., channel state information) in a sensing session. An access point is an example of a sensing receiver. In some examples, a station can also be a sensing receiver, for example in mesh network scenarios.

[0064] The term "sensing space" can refer to any physical space in which a Wi-Fi sensing system can operate.

[0065] The term "sensing initiator" can refer to a device that initiates a Wi-Fi sensing session. The role of the sensing initiator can be assumed by a sensing receiver, a sensing transmitter, or a separate device that contains sensing algorithms.

[0066] The term "wireless local area network (WLAN) sensing session" can refer to a period of time in which objects in a physical space can be probed, detected, and / or characterized. In an example, during a WLAN sensing session, several devices participate and thereby contribute to the generation of sensing measurements.

[0067] The term "sensing trigger message" can refer to a message sent from a sensing transmitter to a sensing receiver to initiate or trigger one or more sensing transmissions. In some examples, the sensing transmissions can be carried by a UL-OFDMA sensing trigger or a UL-OFDMA composite sensing trigger. The sensing trigger message can also be referred to as a sensing initiation message.

[0068] The term "sensing response message" can refer to a message contained within a sensing transmission from a sensing transmitter to a sensing receiver. The sensing receiver uses the sensing transmission containing the sensing response message to perform sensing measurements.

[0069] The term "sensing transmission" can refer to a transmission from a sensing transmitter to a sensing receiver that can be used to make sensing measurements. In an example, a sensing transmission can also be referred to as a wireless sensing signal or a wireless signal.

[0070] The term“sensing measurement” can refer to a measurement of a channel state between a transmitter device (e.g., a sensing transmitter) and a receiver device (e.g., a sensing receiver) derived from a sensing transmission. In an example, a sensing measurement can also be referred to as a channel response measurement.

[0071] The term“sensing target” can refer to a target of a sensing activity at a time. The sensing target is not static and can change at any time. In an example, the sensing target can require a specific type, a specific format, or a specific accuracy, resolution, or precision of sensing measurements available to a sensing algorithm.

[0072] The term“sensing algorithm” can refer to a computational algorithm that implements a sensing target. A sensing algorithm can be executed on any device in a Wi-Fi sensing system.

[0073] The term“requested transmission configuration” can refer to a requested transmission parameter of a sensing transmitter to be used when sending a sensing transmission.

[0074] The term“Automatic Gain Controller (AGC)” can refer to a form of signal amplifier whose gain is automatically adjusted in correspondence with the strength of the received signal.

[0075] The term“Measured Channel State Information (M-CSI)” can represent how a wireless signal propagates from a transmitter to a receiver along multiple paths. M-CSI is typically a complex-valued matrix that represents the amplitude attenuation and phase shift of a signal, which provides an estimate of the communication channel. M-CSI can be provided by a baseband receiver (or baseband processor).

[0076] The term“Processed Channel State Information (P-CSI)” can refer to a corrected form of M-CSI that has been adjusted according to AGC information, phase variation indicators, and downconverter type information.

[0077] The term“group delay” can refer to a characteristic of a physical channel or an electronic element (e.g., a filter) that represents the amount of phase shift of a signal as a function of frequency caused by the physical channel and the electronic element.

[0078] The term“notch filter” can refer to a type of band-stop filter that attenuates frequencies within a specific range while passing all other frequencies without attenuation or with minimal attenuation.

[0079] The term“low intermediate frequency (low-IF) downconverter” can refer to a downconverter that uses a two-stage mixer. The first stage converts a radio frequency signal to a low-IF signal, and the second stage converts the IF signal to a baseband signal.

[0080] The term "phase-locked loop (PLL)" can refer to a phase negative feedback loop that generates an output signal whose phase is related to and tracks the phase of an input signal.

[0081] The term "over-the-air (OTA) channel" can refer to a wireless channel that is located between a transmitter antenna and a receiver antenna.

[0082] The term "zero-IF downconverter" can refer to a downconverter that uses a single stage of mixing to directly convert a received radio frequency signal to a baseband signal.

[0083] For the purpose of reading the following descriptions of various embodiments, it can be helpful to have the following descriptions of portions of the specification and their respective contents:

[0084] Section A describes wireless communication systems, wireless transmissions, and sensing measurements that can be used to practice the embodiments described herein.

[0085] Section B describes systems and methods useful for Wi-Fi sensing systems configured to transmit sensing transmissions and make sensing measurements.

[0086] Section C describes embodiments of systems and methods for isolating electronic environments to improve channel estimation.

[0087] A. Wireless Communication Systems, Wireless Transmissions, and Sensing Measurements

[0088] Figure 1 A wireless communication system 100 is shown. 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 can 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.).

[0089] The wireless communication devices 102A, 102B, 102C can operate in a wireless network, for example, in accordance with a wireless network standard or another type of wireless communication protocol. 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 in accordance with 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 in accordance with short-range communication standards (e.g., Bluetooth®, ZigBee, near-field communication (NFC), millimeter wave communication, etc.).

[0090] ​In some embodiments, the wireless communication devices 102A, 102B, 102C can be configured to communicate in a cellular network, e.g., 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 rates 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), and Time Division-Synchronous Code Division Multiple Access (TD-SCDMA); 4G standards such as Long Term Evolution (LTE) and LTE-Advanced (LTE-A); 5G standards, etc.

[0091] In Figure 1 In the illustrated example, the wireless communication devices 102A, 102B, 102C can be, or include, standard wireless network components. For example, the wireless communication devices 102A, 102B, 102C can be, or include, standard wireless access point (WAP) components. For example, the wireless communication devices 102A, 102B, 102C can be commercially available Wi-Fi access points (APs) or another type of wireless access point (WAP) that performs one or more operations described herein as instructions (e.g., software or firmware) embedded on a modem of the WAP. In some cases, the wireless communication devices 102A, 102B, 102C can be nodes of a wireless mesh network, e.g., 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 can be used. In some cases, one or more of the wireless communication devices 102A, 102B, 102C can be implemented as a WAP in a 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 are mobile devices (e.g., smartphones, smartwatches, tablet computers, laptop computers, etc.), wireless-enabled devices (e.g., smart thermostats, Wi-Fi-enabled cameras, smart televisions), or another type of device that communicates in a wireless network.

[0092] Wireless communication devices 102A, 102B, and 102C can be implemented without Wi-Fi components; for example, other types of standard or non-standard wireless communication can be used for motion detection. In some cases, wireless communication devices 102A, 102B, and 102C can be part of a dedicated motion detection system, or the wireless communication devices can be part of a dedicated motion detection system. For example, a dedicated motion detection system can include a hub device and one or more beacon devices (as remote sensor devices), and wireless communication devices 102A, 102B, and 102C can be a hub device or a beacon device in the motion detection system.

[0093] like Figure 1 As shown, wireless communication device 102C includes a modem 112, a processor 114, a memory 116, and a power supply unit 118; any wireless communication device 102A, 102B, or 102C in wireless communication system 100 may contain the same, additional, or different components, and the components may be configured as follows Figure 1 It may operate as shown or in another manner. In some embodiments, the modem 112, processor 114, memory 116, and power supply unit 118 of the wireless communication device are housed together in a common housing or other assembly. In some embodiments, one or more components of the wireless communication device may be housed individually, for example, in a separate housing or other assembly.

[0094] Modem 112 can transmit (receive, transmit, or both) wireless signals. For example, modem 112 can be configured to transmit radio frequency (RF) signals formatted according to wireless communication standards (e.g., Wi-Fi or Bluetooth). Modem 112 can be implemented as... Figure 1 The illustrated example wireless network modem 112 can also be implemented in another manner, such as utilizing other types of components or subsystems. In some embodiments, modem 112 includes a wireless electronics system and a baseband subsystem. In some cases, the baseband subsystem and wireless electronics system may be implemented on a shared chip or chipset, or the baseband subsystem and wireless electronics system may be implemented in a card or another type of assembled device. The baseband subsystem may be coupled to the wireless electronics system, for example, via leads, pins, wires, or other types of connections.

[0095] In some cases, the radio subsystem in modem 112 can include one or more antennas and radio frequency circuitry. RF circuitry can include, for example, circuitry to filter, amplify, or otherwise condition analog signals, circuitry to up-convert baseband signals to RF signals, circuitry to down-convert RF signals to baseband signals, etc. Such circuitry can include, for example, filters, amplifiers, mixers, local oscillators, etc. The radio subsystem can be configured to transmit radio frequency wireless signals over a wireless communication channel. For example, the radio subsystem can include a radio chip, an RF front end, and one or more antennas. The radio subsystem can include additional or different components. In some embodiments, the radio subsystem can be or include radio electronics (e.g., an RF front end, a radio chip, or similar components) from a conventional modem (e.g., from a Wi-Fi modem, a picocell modem, etc.). In some embodiments, the antennas include multiple antennas.

[0096] In some cases, the baseband subsystem in modem 112 can include, for example, digital electronics configured to process digital baseband data. For example, the baseband subsystem can include a baseband chip. The baseband subsystem can include additional or different components. In some cases, the baseband subsystem can include a digital signal processor (DSP) device or another type of processor device. In some cases, the baseband system includes digital processing logic to operate the radio subsystem, to transmit wireless network traffic through the radio subsystem, to detect motion based on motion detection signals received through the radio subsystem, or to perform other types of processes. For example, the baseband subsystem can include one or more chips, chipsets, or other types of devices configured to encode signals and deliver the encoded signals to the radio subsystem for transmission, or to identify and analyze data encoded 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 by other means).

[0097] In some cases, the radio subsystem of modem 112 receives baseband signals from the baseband subsystem, up-converts the baseband signals to radio frequency (RF) signals, and wirelessly transmits the RF signals (e.g., through an antenna). In some cases, the radio subsystem of modem 112 wirelessly receives RF signals (e.g., through an antenna), down-converts the RF signals to baseband signals, and sends the baseband signals to the baseband subsystem. The signals exchanged between the radio subsystem and the baseband subsystem can 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.

[0098] In some cases, the baseband subsystem of modem 112 can communicate wireless network traffic (e.g., data packets) over the radio subsystem in a wireless communication network on one or more network traffic channels. The baseband subsystem of modem 112 can also transmit or receive (or both) signals (e.g., motion probe signals or motion detection signals) over the radio subsystem on a dedicated wireless communication channel. In some cases, the baseband subsystem generates motion probe signals for transmission, e.g., to probe a motion space. In some cases, the baseband subsystem processes received motion detection signals (signals based on motion probe signals transmitted through a space), e.g., to detect motion of an object in the space.

[0099] Processor 114 can execute instructions, e.g., to generate output data based on input data. The instructions can include programs, code, scripts, or other types of data stored in memory. Additionally or alternatively, the instructions can be encoded as preprogrammed or programmable logic circuits, logic gates, or other types of hardware or firmware components. Processor 114 can be or include a general-purpose microprocessor, like a specialized co-processor, or another type of data processing device. In some cases, processor 114 performs high-level operations of wireless communication device 102C. For example, processor 114 can be configured to execute or interpret software, scripts, programs, functions, executables, or other instructions stored in memory 116. In some embodiments, processor 114 can be included in modem 112.

[0100] Memory 116 may include a computer-readable storage medium, such as a volatile memory device, a non-volatile memory device, or both. Memory 116 may include one or more read-only memory devices, random access memory devices, buffer memory devices, or combinations 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. Memory 116 may store instructions executable by processor 114. For example, instructions may include instructions for using interference buffers and motion detection buffers, such as... Figure 15 , 16 Instructions to time-align signals using one or more operations of the example procedures described in any of 17, 18, 19A, and 19B.

[0101] Power supply unit 118 provides power to other components of wireless communication device 102C. For example, other components may operate based on power supplied by power supply unit 118 via a voltage bus or other connection. In some embodiments, power supply unit 118 includes a battery or battery system, such as a rechargeable battery. In some embodiments, power supply 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 regulated for the components of wireless communication device 102C. Power supply unit 118 may include other components or operate in another manner.

[0102] exist Figure 1 In the illustrated example, wireless communication devices 102A and 102B transmit wireless signals (e.g., according to wireless network standards, motion detection protocols, or others). For example, wireless communication devices 102A and 102B may broadcast wireless motion detection signals (e.g., reference signals, beacon signals, status signals, etc.), or the wireless communication devices may send wireless signals addressed to other devices (e.g., user equipment, client devices, servers, etc.), and these other devices (not shown) and wireless communication device 102C may receive the wireless signals transmitted by wireless communication devices 102A and 102B. In some cases, for example, according to wireless communication standards or other methods, the wireless signals transmitted by wireless communication devices 102A and 102B are repeated periodically.

[0103] In the example shown, wireless communication device 102C processes wireless signals from wireless communication devices 102A and 102B to detect motion of objects in the space accessed by the wireless signals, determine the location of the detected motion, or both. For example, wireless communication device 102C can perform the following... Figure 15 , 16one or more operations of the example processes described in any of 17, 18, 19A, and 19B, or another type of process for detecting motion or determining a location of detected motion. The space accessed by the wireless signals can be an indoor or outdoor space, which can include, for example, one or more fully or partially enclosed areas, open areas without an enclosure, etc. The space can be or can include the interior of a room, multiple rooms, a building, etc. In some cases, the wireless communication system 100 can be modified, e.g., such that the wireless communication device 102C can transmit wireless signals, and the wireless communication devices 102A, 102B can process the wireless signals from the wireless communication device 102C to detect motion or determine a location of detected motion.

[0104] The wireless signals for motion detection can include, for example, beacon signals (e.g., Bluetooth beacons, Wi-Fi beacons, other wireless beacon signals), another standard signal generated for other purposes according to a wireless network standard, or a non-standard signal generated for motion detection or other purposes (e.g., random signals, reference signals, etc.). In examples, motion detection can 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 will be added for the explicit purpose of motion detection, or the data used will nominally be for another purpose and be repurposed or reused for motion detection purposes. In some examples, the wireless signals propagate through an object (e.g., a wall) before or after interacting with a moving object, which can allow detection of movement of the moving object without an optical line of sight between the moving object and the transmission or reception hardware. Based on the received signals, the wireless communication device 102C can generate motion detection data. In some cases, the wireless communication device 102C can communicate the motion detection data to another device or system, such as a security system, which can include a control center for monitoring movement within a space such as a room, a building, an outdoor area, etc.

[0105] In some implementations, the wireless communication devices 102A, 102B can be modified to transmit motion probe signals (which can include, for example, reference signals, beacon signals, or another signal for probing a motion space) on a wireless communication channel (e.g., a frequency channel or a coding channel) separate from wireless network traffic signals. For example, the modulation applied to the payload of the motion probe signals, as well as the type of data or data structure in the payload, can be known by the wireless communication device 102C, which can reduce the amount of processing performed by the wireless communication device 102C for motion sensing. The header can include additional information, e.g., an indication of whether motion was detected by another device in the communication system 100, an indication of the type of modulation, an identification of the device that transmitted the signal, etc.

[0106] In Figure 1In the illustrated example, wireless communication system 100 is a wireless mesh network, with a wireless communication link between each of wireless communication devices 102. In the illustrated example, the wireless communication link between wireless communication device 102C and wireless communication device 102A can be used to probe motion detection field 110A, the wireless communication link between wireless communication device 102C and wireless communication device 102B can be used to probe motion detection field 110B, and the wireless communication link between wireless communication device 102A and wireless communication device 102B can be used to probe motion detection field 110C. In some cases, each wireless communication device 102 detects motion in the motion detection field 110 that the device accesses by processing received signals that are based on wireless signals transmitted by wireless communication devices 102 through the motion detection field 110. For example, when Figure 1 As the person 106 moves through motion detection field 110A and motion detection field 110C, wireless communication devices 102 can detect motion based on signals that they receive that are based on wireless signals transmitted through the respective motion detection fields 110. For example, wireless communication device 102A can detect motion of person 106 in motion detection fields 110A, 110C, wireless communication device 102B can detect motion of person 106 in motion detection field 110C, and wireless communication device 102C can detect motion of person 106 in motion detection field 110A.

[0107] In some cases, a motion detection field 110 can comprise, for example, air, a solid material, a liquid, or another medium through which wireless electromagnetic signals can propagate. In Figure 1 In the illustrated example, motion detection field 110A provides a wireless communication channel between wireless communication device 102A and wireless communication device 102C, motion detection field 110B provides a wireless communication channel between wireless communication device 102B and wireless communication device 102C, and motion detection field 110C provides a wireless communication channel between wireless communication device 102A and wireless communication device 102B. In some aspects of operation, wireless signals transmitted on the wireless communication channels (separate from or shared with wireless communication channels used for network traffic) are used to detect movement of objects in a space. The objects can be any type of static or movable object, and can be animate or inanimate. For example, the objects can be people (e.g., person 106), animals, vehicles, furniture, or other objects. Figure 1The objects shown are people (106), animals, inorganic objects, or other devices, equipment, or assemblies, objects defining all or part of the boundaries of a space (e.g., walls, doors, windows, etc.), or other types of objects. In some embodiments, motion information from wireless communication devices can be analyzed to determine the location of the detected motion. For example, as further described below, one of the wireless communication devices 102 (or another device communicatively coupled to wireless communication device 102) can determine that the detected motion is located near a particular wireless communication device.

[0108] Figure 2A and Figure 2B This is a diagram illustrating an example wireless signal transmitted between wireless communication devices 204A, 204B, and 204C. The wireless communication devices 204A, 204B, and 204C can be, for example... Figure 1 The wireless communication devices 102A, 102B, 102C, or other types of wireless communication devices are shown. Wireless communication devices 204A, 204B, and 204C transmit wireless signals through space 200. Space 200 may be completely or partially enclosed or open at one or more boundaries. Space 200 may be or may contain the interior of a room, multiple rooms, a building, an indoor area, an outdoor area, etc. In the example shown, the first wall 202A, the second wall 202B, and the third wall 202C at least partially enclose space 200.

[0109] exist Figure 2A and Figure 2B In the example shown, wireless communication device 204A can be used to repeatedly (e.g., periodically, intermittently, at predetermined intervals, non-predicted intervals, or random intervals, etc.) transmit wireless signals. Wireless communication devices 204B and 204C can be used to receive signals based on the signals transmitted by wireless communication device 204A. Wireless communication devices 204B and 204C each have a modem (e.g., Figure 1 The modem 112 shown is configured to process received signals to detect the movement of objects in space 200.

[0110] As shown in the figure, the object is located Figure 2A The first positioning 214A in the middle, and the object has been moved to Figure 2B The second positioning 214B. In Figure 2A and Figure 2B In this context, a moving object in space 200 is represented as a person, but the moving object can be another type of object. For example, a moving object can be an animal, an inorganic object (e.g., a system, device, equipment, or assembly), an object that defines all or part of the boundaries of space 200 (e.g., a wall, door, window, etc.), or another type of object.

[0111] like Figure 2Aand Figure 2B As shown, multiple example paths of the wireless signal transmitted from wireless communication device 204A are illustrated by dashed lines. Along the first signal path 216, the wireless signal is transmitted from wireless communication device 204A and reflected from the first wall 202A toward wireless communication device 204B. Along the second signal path 218, the wireless signal is transmitted from wireless communication device 204A and reflected from both the second wall 202B and the first wall 202A toward wireless communication device 204C. Along the third signal path 220, the wireless signal is transmitted from wireless communication device 204A and reflected from the second wall 202B toward wireless communication device 204C. Along the fourth signal path 222, the wireless signal is transmitted from wireless communication device 204A and reflected from the third wall 202C toward wireless communication device 204B.

[0112] exist Figure 2A In the middle, along the fifth signal path 224A, a wireless signal is transmitted from the wireless communication device 204A and reflected from the object at the first positioning 214A toward the wireless communication device 204C. Figure 2A and Figure 2B Between these points, the surface of the object moves within space 200 from a first location 214A to a second location 214B (e.g., a certain distance from the first location 214A). Figure 2B In the middle, along the sixth signal path 224B, a wireless signal is transmitted from the wireless communication device 204A and reflected from the object at the second location 214B toward the wireless communication device 204C. As the object moves from the first location 214A to the second location 214B, Figure 2B The sixth signal path 224B depicted in the diagram is longer than... Figure 2A The fifth signal path 224A is depicted in the diagram. In some instances, the signal path may be added, removed, or otherwise modified due to the movement of objects in space.

[0113] Figure 2A and Figure 2B The example wireless signal shown may undergo attenuation, frequency shift, phase shift, or other effects along its respective path, and may have portions propagating in another direction, for example, through the first wall 202A, the second wall 202B, and the third wall 202C. In some instances, the wireless signal is a radio frequency (RF) signal. The wireless signal may contain other types of signals.

[0114] exist Figure 2A and Figure 2B In the example shown, the wireless communication device 204A can repeatedly transmit wireless signals. Specifically, Figure 2A The wireless signal transmitted from the wireless communication device 204A at the first moment is shown, and Figure 2BThe same wireless signal transmitted from the wireless communication device 204A at a second, later time is shown. The transmitted signal can be transmitted continuously, periodically, at random or intermittent times, etc., or combinations thereof. The transmitted signal can have a plurality of frequency components in a frequency bandwidth. The transmitted signal can be transmitted from the wireless communication device 204A in an omnidirectional manner, a directional manner, or other manner. In the example shown, the wireless signal traverses a plurality of respective paths in the space 200, and the signal along each path can be attenuated and can have a phase or frequency offset due to path loss, scattering, reflection, etc.

[0115] As shown in FIG. 2, the wireless communication device 204A transmits a wireless signal. The transmitted signal can be transmitted continuously, periodically, at random or intermittent times, etc., or combinations thereof. The transmitted signal can have a plurality of frequency components in a frequency bandwidth. The transmitted signal can be transmitted from the wireless communication device 204A in an omnidirectional manner, a directional manner, or other manner. Figure 2A and Figure 2B As shown, the signals from the first through sixth paths 216, 218, 220, 222, 224A, and 224B combine at the wireless communication device 204C and the wireless communication device 204B to form a received signal. Due to the multiple paths in the space 200 affecting the transmitted signal, the space 200 can be represented as a transfer function (e.g., a filter) where the transmitted signal is input and the received signal is output. As objects move in the space 200, the attenuation or phase offset of the signals in the signal paths can change, and thus, the transfer function of the space 200 can 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 the transfer function, the received signal, will also change. The change in the received signal can be used to detect movement of the objects.

[0116] Mathematically, the transmitted signal f(t) transmitted from the first wireless communication device 204A can be described according to Equation (1):

[0117]

[0118] where ω n represents the frequency of the n-th frequency component of the transmitted signal, c n represents the complex coefficient of the n-th frequency component, and t represents time. In the case where the transmitted signal f(t) is transmitted from the first wireless communication device 204A, the output signal r k (t) from the path k can be described according to Equation (2):

[0119]

[0120] where, a n,k represents the attenuation factor (or channel response; e.g., due to scattering, reflection, and path loss) of the n-th frequency component along the path k, and φ n,kdenotes the phase of the signal at the nth frequency component along path k. The received signal R at the wireless communication device can then be described as the sum of all the output signals r from all paths to the wireless communication device k The sum of (t) is shown in equation (3):

[0121] R =∑ k r k (t)....(3)

[0122] Substituting equation (2) into equation (3) gives the following equation (4):

[0123]

[0124] The received signal R at the wireless communication device can then be analyzed. For example, the received signal R at the wireless communication device can be transformed to the frequency domain using a fast Fourier transform (FFT) or another type of algorithm. The transformed signal can represent the received signal R as a series of n complex values, one for each of the corresponding frequency components (at n frequencies ω n ). For a frequency component at frequency ω n , the complex value H n may be represented as the following equation (5):

[0125]

[0126] The complex value H n for a given frequency component ω n represents the relative amplitude and phase shift of the received signal at that frequency component ω n . As the object moves in space, the complex value H n changes due to changes in the channel response a n,k of the space. Thus, changes detected in the channel response can indicate movement of the object within the communication channel. In some cases, noise, interference, or other phenomena can affect the channel response detected by the receiver, and a motion detection system can reduce or isolate such effects to improve the accuracy and quality of the motion detection capabilities. In some embodiments, the overall channel response can be represented as the following equation (6):

[0127]

[0128] In some cases, the channel response h ch of the space can be determined, for example, based on an estimated mathematical theory. For example, a reference signal R ch may be modified with a candidate channel response (h ef ), and then a maximum likelihood method can be used to select the channel response that best matches the received signal (R cvd) best-matching candidate channel. In some cases, the estimated received signal ef ) is obtained from a convolution of a reference signal (R ch ) with a candidate channel response (h and then changing the channel coefficients of the channel response (h ch ) to minimize the squared error of the estimated received signal This can be mathematically stated as the following equation (7):

[0129]

[0130] using an optimization criterion

[0131]

[0132] The minimization or optimization process can utilize adaptive filtering techniques such as least mean square (LMS), recursive least square (RLS), batch least square (BLS), etc. The channel response can be a finite impulse response (FIR) filter, an infinite impulse response (IIR) filter, etc. As shown in the above equation, the received signal can be considered as a convolution of the reference signal and the channel response. The convolution operation implies that the channel coefficients have a certain degree of correlation with each delayed copy of the reference signal. Thus, the convolution operation as shown in the above equation indicates that the received signal appears at different delay points, each delayed copy weighted by the channel coefficients.

[0133] Figure 3A and Figure 3B are plots showing examples of channel responses 360, 370 calculated from wireless signals communicated between wireless communication devices 204A, 204B, 204C in Figure 2A and Figure 2B Figure 3A and Figure 3B also shows a frequency domain representation 350 of an initial wireless signal transmitted by the wireless communication device 204A. In the example shown, Figure 3A the channel response 360 in Figure 3B represents the signal received by the wireless communication device 204B when there is no motion in the space 200, and Figure 2B the channel response 370 in

[0134] in Figure 3A and Figure 3B ​In the example shown, for purposes of illustration, the wireless communication device 204A transmits a signal having a flat frequency profile (same amplitude for each frequency component fl, f2, and f3), 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 204 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 Figure 3A and Figure 3B the channel responses 360, 370 are different from the frequency domain representation 350 of the transmitted signal. When motion occurs in the space 200, the channel response will also change. For example, as shown in Figure 3B the channel response 370 associated with motion of an object in the space 200 is different from the channel response 360 associated with no motion in the space 200.

[0135] Furthermore, the channel response can be different from the channel response 370 when an object moves within the space 200. In some cases, the space 200 can be divided into unique regions, and the channel response associated with each region can share one or more characteristics (e.g., shape), as described below. Thus, motion of an object within different unique regions can be distinguished, and the location of the detected motion can be determined based on analysis of the channel response.

[0136] Figure 4A and Figure 4B are illustrations showing example channel responses 401, 403 associated with motion of an object 406 in unique regions 408, 412 of a space 400. In the example shown, the space 400 is a building, and the space 400 is divided into multiple unique regions: a first region 408, a second region 410, a third region 412, a fourth region 414, and a fifth region 416. In some cases, the space 400 can contain additional or fewer regions. As shown in Figure 4A and Figure 4B the regions within the space 400 can be defined by walls between rooms. Additionally, the regions can be defined by ceilings between floors of a building. For example, the space 400 can contain additional floors with additional rooms. Additionally, in some cases, the multiple regions of the space can be or include multiple floors in a multi-story building, multiple rooms in a building, or multiple rooms on a particular floor of a building. In Figure 4A In the example shown, while the object positioned in the first region 408 is represented as a person 406, the moving object can be another type of object, such as an animal or an inorganic object.

[0137] In the illustrated example, wireless communication device 402A is positioned in fourth region 414 of space 400, wireless communication device 402B is positioned in second region 410 of space 400, and wireless communication device 402C is positioned in fifth region 416 of space 400. Wireless communication devices 402 can operate in the same or similar manner as wireless communication devices 102 of Figure 1 wireless communication device 102. For example, wireless communication devices 402 can be configured to transmit and receive wireless signals, and detect whether motion has occurred in space 400 based on received signals. By way of example, wireless communication devices 402 can periodically or repeatedly transmit a motion probe signal through space 400, and receive a signal based on the motion probe signal. Wireless communication devices 402 can analyze the received signal to detect whether an object has moved in space 400, e.g., by analyzing a channel response associated with space 400 based on the received signal. In addition, in some embodiments, wireless communication devices 402 can analyze the received signal to identify a location of detected motion within space 400. For example, wireless communication devices 402 can analyze characteristics of a channel response to determine whether the channel response shares the same or similar characteristics as channel responses known to be associated with first through fifth regions 408, 410, 412, 414, 416 of space 400.

[0138] In the illustrated example, one (or more) of wireless communication devices 402 repeatedly transmits a motion probe signal (e.g., a reference signal) through space 400. In some cases, the motion probe signal can have a flat frequency profile, with an amplitude for each frequency component fl, f2, and f3. For example, the motion probe signal can have a frequency domain representation 350 as illustrated in Figure 3A and Figure 3B In some cases, the motion probe signal can have a different frequency profile. Due to the interaction of the reference signal with space 400 (and objects therein), a signal received at another wireless communication device 402 based on the motion probe signal transmitted from another wireless communication device 402 is different than the transmitted reference signal.

[0139] Based on the received signal, wireless communication devices 402 can determine a channel response for space 400. When motion occurs in a unique region within the space, unique characteristics can be seen in the channel response. For example, while the channel response can be slightly different for motion within the same region of space 400, the channel response associated with motion in a unique region can generally share the same shape or other characteristics. For example, Figure 4A Channel response 401 of FIG. 4A represents an example channel response associated with motion of object 406 in first region 408 of space 400, while channel response 401 of FIG. 4B represents an example channel response associated with motion of object 406 in second region 410 of space 400. Figure 4BChannel response 403 represents an example channel response associated with motion of object 406 in third region 412 of space 400. Channel responses 401, 403 are associated with signals received by same wireless communication device 402 in space 400.

[0140] Figure 4C and Figure 4D are plots showing Figure 4A and Figure 4B Channel responses 401, 403 are superimposed on channel response 460 associated with no motion in space 400. Figure 4C and 4D Also shown is a frequency domain representation 450 of an initial wireless signal transmitted by one or more of wireless communication devices 402A, 402B, 402C. When motion occurs in space 400, changes in channel response will occur relative to channel response 460 associated with no motion, and thus, motion of objects in space 400 can be detected by analyzing changes in channel response. Additionally, a relative location of detected motion within space 400 can be identified. For example, a shape of channel response associated with motion can be compared to reference information (e.g., using a trained AI model) to classify the motion as having occurred within a unique region of space 400.

[0141] When there is no motion in space 400 (e.g., when object 406 is not present), wireless communication device 402 can compute a channel response 460 associated with no motion. Channel response can change slightly due to a variety of factors; however, multiple channel responses 460 associated with different time periods can share one or more characteristics. In the example shown, channel response 460 associated with no motion has a decreasing frequency profile (amplitude of each frequency component fl, f2, and f3 is less than the previous). In some cases (e.g., based on different room layouts or placement of wireless communication device 402), the profile of channel response 460 can be different.

[0142] When motion occurs in space 400, channel response will change. For example, in Figure 4C and Figure 4DIn the illustrated example, the channel response 401 associated with the motion 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 motion 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 amplitude of the middle frequency component f2 is less than the outer frequency components fl and f3), while the channel response 403 has a convex asymptotic frequency profile (the amplitude of the middle frequency component f2 is greater than the outer frequency components fl and f3). In some cases (e.g., based on different room layouts or placement of the wireless communication device 402), the profiles of the channel responses 401, 403 can differ.

[0143] Analyzing the channel response can be thought of as similar to analyzing a digital filter. The channel response can be formed by reflections of objects in the space and reflections produced by moving or stationary people. When a reflector (e.g., a person) moves, it changes the channel response. This can translate into a change in the equivalent taps of a digital filter, which can be thought of as having poles and zeros (poles amplify frequency components of the channel response and appear as peaks or highs in the response, while zeros attenuate frequency components of the channel response and appear as troughs, lows, or zero values in the response). The changing digital filter can be characterized by the locations of its peaks and troughs, and the channel response can be similarly characterized by its peaks and troughs. For example, in some embodiments, analyzing the zeros and peaks in the frequency components of the channel response (e.g., by noting their locations on the frequency axis as well as their amplitudes) can detect motion.

[0144] In some embodiments, time series aggregation can be used to detect motion. Time series aggregation can be performed by observing the features of the channel response over a moving window and by aggregating the windowed results using statistical measures (e.g., mean, variance, principal components, etc.). During instances of motion, the typical digital filter features will shift in location and flip between some values due to the continuous changes of the scattering scene. That is, the equivalent digital filter exhibits a range of values for its peaks and zeros (due to the motion). By looking at this range of values, a unique profile (in examples, the profile can also be referred to as a signature) can be identified for unique regions within the space.

[0145] In some embodiments, artificial intelligence (AI) models can be used to process 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 Neighbors 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 values and output values, and are trained using a historical set of input and output values for which the correlation is known. In instances, artificial intelligence can also be referred to as machine learning.

[0146] In some embodiments, a distribution of channel responses associated with motion in unique regions of the space 400 can be learned. For example, machine learning can be used to classify channel response characteristics in which object motion is within a unique region 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) can assist the learning process. For example, with reference to the example shown in FIGS. 4A and 4B, the user can move in each of the first through fifth regions 408, 410, 412, 414, 416 during a learning phase, and can indicate (e.g., through a user interface on a mobile computing device) that he / she is moving in one of the particular regions in the space 400. For example, as the user moves through the first region 408 (e.g., as shown in FIG. 4A), the user can indicate on the mobile computing device that he / she is in the first region 408 (and, optionally, can name the region as the "bedroom," "living room," "kitchen," or another type of room in the building). As the user moves through the region, channel responses can be obtained, and the channel responses can be "labeled" with the user-indicated location (region). The user can repeat the same process for other regions of the space 400. The term "labeled" as used herein can refer to labeling and identifying channel responses with user-indicated locations or any other information. Figure 4A Figure 4B As the user moves through the region, channel responses can be obtained, and the channel responses can be "labeled" with the user-indicated location (region). The user can repeat the same process for other regions of the space 400. The term "labeled" as used herein can refer to labeling and identifying channel responses with user-indicated locations or any other information. Figure 4A

[0147] ​​The labeled channel responses can then be processed (e.g., by machine learning software) to identify unique characteristics of the channel responses associated with motion in the unique areas. Once identified, the identified unique characteristics can be used to determine the location of detected motion for newly computed channel responses. For example, the labeled channel responses can be used to train an AI model, and once trained, a newly computed channel response can be input to the AI model and the AI model can output the location of detected motion. For example, in some cases, the mean, range, and absolute value are input to the AI model. In some cases, the amplitude and phase of the complex channel response itself can also be input. These values allow the AI model to design an arbitrary front-end filter to pick the features most relevant to making accurate predictions of motion in unique areas of the space. In some embodiments, the AI model is trained by performing stochastic gradient descent. For example, the most active channel response changes during a certain area can be monitored during training, and specific channel changes can be heavily weighted (by training and adjusting the weights in the first layer to be relevant to those shapes, trends, etc.). The weighted channel changes can be used to create a metric that activates when a user is present in a certain area.

[0148] For extracted features, such as channel response zero-crossings and peaks, a time series can be created (of zero-crossings / peaks) using aggregations within a moving window, taking snapshots of a few features in the past and present, and using the aggregated values as inputs to the network. Thus, the network will try to aggregate values in a certain area to cluster them while adjusting its weights, which can be done by creating a decision surface based on a logistic classifier. The decision surface partitions different clusters, and subsequent layers can form classes based on individual clusters or combinations of clusters.

[0149] In some embodiments, the AI model contains two or more layers of inference. The first layer acts as a logistic classifier that can partition values of different concentrations into separate clusters, while the second layer combines some of these clusters together to create classes for unique areas. Additionally, subsequent layers can help extend unique areas onto more than two classes of clusters. For example, a fully connected AI model can contain an input layer corresponding to the number of features tracked, an intermediate layer corresponding to the number of effective clusters (by iterating between choices), and a final layer corresponding to different areas. In cases where full channel response information is input to the AI model, the first layer can act as a shape filter that can make certain shapes relevant. Thus, the first layer can lock onto a certain shape, the second layer can generate a measure of changes that occur in those shapes, and the third and subsequent layers can create combinations of those changes and map them to different areas within the space. The outputs of the different layers can then be combined by a fusion layer.

[0150] B. Wi-Fi sensing system example methods and apparatus

[0151] B. This section describes systems and methods useful for Wi-Fi sensing systems configured to transmit sensing transmissions and take sensing measurements.

[0152] Figure 5 Embodiments of some architectures of an implementation of a system 500 for Wi-Fi sensing according to some embodiments are depicted.

[0153] The system 500 (alternatively referred to as a Wi-Fi sensing system 500) can include a receiving device 502, a sensing decision unit 504, a plurality of sensing transmitters 506-(1-M), a sensing algorithm manager 508, and a network 560 that enables communication between system components for exchange of information. The system 500 can be an instance or example of the wireless communication system 100, and the network 560 can be an instance or example of a wireless network or cellular network, the details of which are provided with reference to Figure 1 and the description accompanying it.

[0154] According to an embodiment, the receiving device 502 can be configured to receive sensing transmissions (e.g., from each of the plurality of sensing transmitters 506-(1-M)) and perform one or more measurements (e.g., channel state information (CSI)) useful for Wi-Fi sensing. These measurements can be referred to as sensing measurements. The sensing measurements can be processed to obtain sensing results for the system 500, such as detecting motion or gestures. In an embodiment, the receiving device 502 can be an access point. In some embodiments, the receiving device 502 can function as a sensing initiator.

[0155] According to an implementation, the receiving device 502 can be implemented by a device such as the wireless communication device 102 as shown in Figure 1 In some implementations, the receiving device 502 can be implemented by a device such as the wireless communication device 204 as shown in Figure 2A and Figure 2B Additionally, the receiving device 502 can be implemented by a device such as the wireless communication device 306 as shown in Figure 4A and Figure 4BThe illustrated wireless communication device 402, among other devices, can be implemented. In an embodiment, the receiving device 502 can coordinate and control communications between the plurality of sensing transmitters 506-(1-M). According to an embodiment, the receiving device 502 can be enabled to control the measurement activities to ensure that the required sensing transmissions are made at the required times and to ensure accurate determination of the sensing measurements. In some embodiments, the receiving device 502 can process the sensing measurements to obtain the sensing results for the system 500. In some embodiments, the receiving device 502 can be configured to transmit the sensing measurements to the sensing decision unit 504, and the sensing decision unit 504 can be configured to process the sensing measurements to obtain the sensing results for the system 500. In an example, the sensing measurements processed at the sensing decision unit 504 can be referred to as measured CSI (M-CSI).

[0156] Referring again to Figure 5 In some embodiments, each of the plurality of sensing transmitters 506-(1-M) can form part of a basic service set (BSS) and can be configured to send sensing transmissions to the receiving device 502 based on which one or more sensing measurements (e.g., CSI) can be performed for Wi-Fi sensing. In an embodiment, each of the plurality of sensing transmitters 506-(1-M) can be a station. According to an embodiment, each of the plurality of sensing transmitters 506-(1-M) can be implemented by a device such as the wireless communication device 102 illustrated. Figure 1 In some embodiments, each of the plurality of sensing transmitters 506-(1-M) can be implemented by a device such as the wireless communication device 204 illustrated. Figure 2A and Figure 2B In some embodiments, each of the plurality of sensing transmitters 506-(1-M) can be implemented by a device such as the wireless communication device 402 illustrated. In some embodiments, the communications between the receiving device 502 and each of the plurality of sensing transmitters 506-(1-M) can be conducted through a station management entity (SME) and a media access control (MAC) layer management entity (MLME) protocol. Figure 4A and Figure 4B In some embodiments, the communications between the receiving device 502 and each of the plurality of sensing transmitters 506-(1-M) can be conducted through a station management entity (SME) and a media access control (MAC) layer management entity (MLME) protocol.

[0157] In some embodiments, the sensing decision unit 504 can be configured to receive sensing measurements from the receiving device 502 and process the sensing measurements. In an example, the sensing decision unit 504 can process the sensing measurements. According to some implementations, the sensing decision unit 504 can include / execute a sensing algorithm. In an embodiment, the sensing decision unit 504 can be a station. In some embodiments, the sensing decision unit 504 can be an access point. According to an implementation, the sensing decision unit 504 can be implemented by a device such as the wireless communication device 102 as shown in Figure 1 In some implementations, the sensing decision unit 504 can be implemented by a device such as the wireless communication device 204 as shown in Figure 2A and Figure 2B In addition, the sensing decision unit 504 can be implemented by a device such as the wireless communication device 402 as shown in Figure 4A and Figure 4B In some embodiments, the sensing decision unit 504 can be any computing device such as a desktop computer, a laptop computer, a tablet computer, a mobile device, a personal digital assistant (PDA), or any other computing device. In an embodiment, the sensing decision unit 504 can function as a sensing initiator, where a sensing algorithm determines the measurement activities and the sensing measurements required to complete the measurement activities. In an embodiment, the sensing decision unit 504 can be a sensing receiver. The sensing decision unit 504 can communicate the sensing measurements required to complete the measurement activities to the receiving device 502 to coordinate and control the communications among the plurality of sensing transmitters 506-(1-M). According to some implementations, the sensing decision unit 504 can provide the processed sensing measurements to the sensing algorithm manager 508 for identifying one or more features of interest.

[0158] According to some embodiments, the sensing algorithm manager 508 can be configured to receive the processed sensing measurements from the sensing decision unit 504. In an example, the sensing algorithm manager 508 can further process and analyze the processed sensing measurements to identify one or more features of interest. According to some implementations, the sensing algorithm manager 508 can include / execute a sensing algorithm. In an embodiment, the sensing algorithm manager 508 can be a station. In some embodiments, the sensing algorithm manager 508 can be an access point. According to an implementation, the sensing algorithm manager 508 can be implemented by a device such as the wireless communication device 102 as shown in Figure 1 In some implementations, the sensing algorithm manager 508 can be implemented by a device such as the wireless communication device 204 as shown in Figure 2A and Figure 2B In addition, the sensing algorithm manager 508 can be implemented by a device such as the wireless communication device 402 as shown in Figure 4A and Figure 4BThe illustrated wireless communication device 402, among other devices, is implemented. In some embodiments, the sensing algorithm manager 508 can be any computing device, such as a desktop computer, a laptop computer, a tablet computer, a mobile device, a PDA, or any other computing device. In embodiments, the sensing algorithm manager 508 can function as a sensing initiator, where the sensing algorithm determines the measurement activity and the sensing measurements required to complete the measurement activity.

[0159] Referring to Figure 5 In more detail, the receiving device 502 can include a processor 510 and a memory 512. For example, the processor 510 and the memory 512 of the receiving device 502 can be the processor 114 and the memory 116, respectively, as illustrated. In an embodiment, the receiving device 502 can further include a transmit antenna 514, a receive antenna 516, a receiver front end (RFE) 518, and a baseband processor 528. According to an embodiment, the RFE 518 can include an automatic gain controller (AGC) 520, a frequency downconverter 522, and a phase-locked loop (PLL) unit 524, and the baseband processor 528 can include a generation unit 526. Figure 1

[0160] In some embodiments, an antenna can be used to transmit and receive signals in a half-duplex format. When an antenna is transmitting, the antenna can be referred to as a transmit antenna 514, and when an antenna is receiving, the antenna can be referred to as a receive antenna 516. One of ordinary skill in the art will understand that the same antenna can be a transmit antenna 514 in some instances and a receive antenna 516 in other instances. In the case of an antenna array, one or more antenna elements can be used to transmit or receive signals, for example, in a beamforming environment. In some instances, a group of antenna elements used to transmit a composite signal can be referred to as a transmit antenna 514, and a group of antenna elements used to receive a composite signal can be referred to as a receive antenna 516. In some instances, each antenna is equipped with its own transmit and receive paths, which can be alternately switched to connect to the antenna depending on whether the antenna is operating as a transmit antenna 514 or a receive antenna 516.

[0161] In an implementation, the AGC 520 can be a signal amplifier whose gain is automatically adjusted so that its output signal amplitude falls within a desired dynamic range acceptable to the signal processing units that follow in the receive chain. According to an implementation, the frequency downconverter 522 can be configured to convert received radio frequency signals back to intermediate frequency (IF) signals or baseband signals for further processing. According to an implementation, the frequency downconverter 522 can be a low-IF frequency downconverter or a zero-IF frequency downconverter.

[0162] ​In an embodiment, the PLL unit 524 can be configured to generate an output signal that is phase related to an input signal. According to an embodiment, the PLL unit 524 can be configured to provide one or more accurate and stable carrier frequency sources to the down-converter 522. In an embodiment, the one or more accurate and stable carrier frequency sources can be used for down-conversion of radio frequency signals, frequency synchronization, and timing synchronization. In an embodiment, the output signal of the PLL unit 524 is related to a received radio frequency signal.

[0163] In an embodiment, the generating unit 526 can be coupled to the processor 510 and the memory 512. In some embodiments, the generating unit 526, as well as other units, can include routines, programs, objects, components, data structures, etc., which can perform particular tasks or implement particular abstract data types. The generating unit 526 can also be implemented as a signal processor, a state machine, logic circuitry, and / or any other device or component that manipulates signals based on operational instructions.

[0164] In some embodiments, the generating unit 526 can be implemented in hardware, instructions executed by a processing unit, or a combination thereof. The processing unit can include a computer, a processor, a state machine, a logic array, or any other suitable device capable of processing instructions. The processing unit can be a general purpose processor that executes instructions to cause the general purpose processor to perform desired tasks, or the processing unit can be dedicated to performing the desired functions. In some embodiments, the generating unit 526 can be machine-readable instructions that, when executed by a processor / processing unit, perform any desired functions. The machine-readable instructions can be stored on an electronic memory device, a hard disk, an optical disk, or other machine-readable storage medium or non-transitory medium. In an embodiment, the machine-readable instructions can also be downloaded to the storage medium over a network connection. In an example, the machine-readable instructions can be stored in the memory 512.

[0165] In an embodiment, the generating unit 526 can be responsible for receiving sensing transmissions and associated transmission parameters, calculating sensing measurements, and processing the sensing measurements to achieve sensing objectives. In some embodiments, the generating unit 526 can be responsible for receiving data transmissions and processing the data transmissions to achieve data transmission objectives. In some embodiments, the generating unit 526 can be configured to transmit the sensing measurements to the sensing decision unit 504 for further processing. In an embodiment, the generating unit 526 can be configured to cause at least one of the transmit antennas 514 to send a message to each of the plurality of sensing transmitters 506-(1-M). Additionally, the generating unit 526 can be configured to receive the message from each of the plurality of sensing transmitters 506-(1-M) through at least one of the receive antennas 516.

[0166] In an embodiment, the RFE 518 and the baseband processor 528 can implement lower layers of the protocol stack, such as the physical (PHY) layer or lower portions of the MAC layer.

[0167] Referring again to Figure 5 , the sensing decision unit 504 can implement upper layers of the protocol stack, such as the medium access control (MAC) layer or the application layer. In an embodiment, the sensing decision unit 504 can include the processor 528 and the memory 530. For example, the processor 528 and the memory 530 of the sensing decision unit 504 can be the processor 114 and the memory 116, respectively, as shown in FIG. 1. In an embodiment, the sensing decision unit 504 can further include a transmit antenna 532, a receive antenna 534, a CSI equalization unit 536, and a group delay estimation and correction unit 538. Figure 1

[0168] In some embodiments, an antenna can be used to transmit and receive in a half-duplex format. When an antenna is transmitting, the antenna can be referred to as a transmit antenna 532, and when an antenna is receiving, the antenna can be referred to as a receive antenna 534. One of ordinary skill in the art will appreciate that the same antenna can be a transmit antenna 532 in some instances and a receive antenna 534 in other instances. In the case of an antenna array, one or more antenna elements can be used to transmit or receive signals, for example, in a beamforming environment. In some instances, a group of antenna elements used to transmit a composite signal can be referred to as a transmit antenna 532, and a group of antenna elements used to receive a composite signal can be referred to as a receive antenna 534. In some instances, each antenna is equipped with its own transmit and receive paths, which can be alternately switched to connect to the antenna depending on whether the antenna is operating as a transmit antenna 532 or a receive antenna 534.

[0169] In an embodiment, the CSI equalization unit 536 and the group delay estimation and correction unit 538 can be coupled to the processor 528 and the memory 530. In some embodiments, the CSI equalization unit 536 and the group delay estimation and correction unit 538, as well as other units, can include routines, programs, objects, components, data structures, etc., which can perform particular tasks or implement particular abstract data types. The CSI equalization unit 536 and the group delay estimation and correction unit 538 can also be implemented as a signal processor, a state machine, logic circuitry, and / or any other device or component that manipulates signals based on operational instructions.

[0170] ​In some embodiments, the CSI equalization unit 536 and the group delay estimation and correction unit 538 can be implemented in hardware, instructions executed by a processing unit, or a combination thereof. The processing unit can include a computer, a processor, a state machine, a logic array, or any other suitable device capable of processing instructions. The processing unit can be a general purpose processor that executes instructions to cause the general purpose processor to perform the desired tasks, or the processing unit can be dedicated to performing the desired functions. In some embodiments, the CSI equalization unit 536 and the group delay estimation and correction unit 538 can be machine-readable instructions that, when executed by a processor / processing unit, perform any desired functions. The machine-readable instructions can be stored on an electronic memory device, a hard disk, an optical disk, or other machine-readable storage medium or non-transitory medium. In an implementation, the machine-readable instructions can also be downloaded to the storage medium over a network connection. In an example, the machine-readable instructions can be stored in the memory 530.

[0171] According to an implementation, the sensing decision unit 504 can be configured to perform CSI processing. The CSI processing can be performed by the CSI equalization unit 536 and the group delay estimation and correction unit 538. In an example, the output from the logical CSI processing can be referred to as processed CSI (P-CSI). Additionally, in an example, the P-CSI can have undergone CSI equalization or group delay estimation and correction, or both.

[0172] In an implementation, the sensing transmitter 506-1 can include a processor 540-1 and a memory 542-1. For example, the processor 540-1 and the memory 542-1 of the sensing transmitter 506-1 can be the processor 114 and the memory 116, respectively, as shown in FIG. 1. In an embodiment, the sensing transmitter 506-1 can further include a transmit antenna 544-1, a receive antenna 546-1, a transmitter front end (TFE) 548-1, and a sensing agent 554-1. In an implementation, the TFE 548-1 can include an up-converter 550-1 and a power amplifier 552-1. Figure 1

[0173] ​In some embodiments, an antenna can be used to transmit and receive in a half-duplex format. When the antenna is transmitting, the antenna can be referred to as a transmit antenna 544-1, and when the antenna is receiving, the antenna can be referred to as a receive antenna 546-1. One of ordinary skill in the art will understand that the same antenna can be a transmit antenna 544-1 in some instances and a receive antenna 546-1 in other instances. In the case of an antenna array, one or more antenna elements can be used to transmit or receive signals, for example, in a beamforming environment. In some instances, a group of antenna elements used to transmit a composite signal can be referred to as a transmit antenna 544-1, and a group of antenna elements used to receive a composite signal can be referred to as a receive antenna 546-1. In some instances, each antenna is equipped with its own transmit and receive paths, which can be alternately switched to connect to the antenna depending on whether the antenna is operating as a transmit antenna 544-1 or a receive antenna 546-1.

[0174] According to an embodiment, the up-converter 550-1 can be configured to convert a baseband signal to a radio frequency signal. In an instance, the up-converter 550-1 can shift the frequency spectrum of a baseband signal to a desired radio band. In an embodiment, the power amplifier 552-1 can be configured to increase the magnitude of the power of a given input signal.

[0175] In an embodiment, the sensing agent 554-1 can be a block that exchanges physical layer parameters and instructions between the MAC layer and the application layer program or algorithm of the sensing transmitter 506-1. The sensing agent 554-1 can be configured to cause at least one of the transmit antennas 544-1 and at least one of the receive antennas 546-1 to exchange messages with the receiving device 502.

[0176] Although the receiving device 502, the sensing decision unit 504, and the sensing algorithm manager 508 are represented as separate devices in the system 500, the sensing decision unit 504 and the sensing algorithm manager 508 can be considered logical functional blocks and can reside on any device that can support the features described herein. For example, the receiving device 502 can incorporate the functions of the receiving device 502, the sensing decision unit 504, and the sensing algorithm manager 508. In another example, the receiving device 502 and the sensing decision unit 504 can be implemented on the same device, and the sensing algorithm manager 508 is implemented by a second remote device. In the case where the two functional blocks reside on the same device, then communication between the functional blocks can not require the transmission and reception of signals over the air through transmit and receive antennas.

[0177] For ease of explanation and understanding, the description provided above is made with reference to the sensing transmitter 506-1, however, the description applies equally to the remaining sensing transmitters 506-(2-M).

[0178] According to one or more embodiments, communications in the network 560 can be managed by one or more standards in the 802.11 family of standards developed by IEEE. Some example IEEE standards can include IEEE 802.11-2020, IEEE 802.11ax-2021, IEEE 802.11me, IEEE 802.11az, and IEEE 802.11be. IEEE 802.11-2020 and IEEE 802.11ax-2021 are fully approved standards, while IEEE 802.11me reflects ongoing maintenance updates to the IEEE 802.11-2020 standard, and IEEE 802.11be defines the next generation standard. IEEE 802.11az is an extension of the IEEE 802.11-2020 and IEEE 802.11ax-2021 standards that adds new functionality. In some embodiments, communications can be managed by other standards (other or additional IEEE standards or other types of standards). In some embodiments, portions of the system 500 of the network 560 that do not need to be managed by one or more standards in the 802.11 family of standards can be implemented by instances of any type of network, including wireless networks or cellular networks.

[0179] In an embodiment, Wi-Fi sensing can be performed based on detecting perturbations in an OTA channel. An OTA channel refers here to the propagation path of a signal between a transmitter antenna and a receiver antenna. Wi-Fi sensing can depend on a transmitted signal generated by a baseband transmitter and a received signal processed by a baseband receiver to compute CSI. The path between the baseband transmitter and the baseband receiver can be referred to as a measured channel, and in an instance, the measured channel is not equal to the OTA channel because the measured channel includes the processing effects of both the baseband transmitter and the baseband receiver. The baseband receiver can be interchangeably referred to as a baseband processor. In an instance, the CSI computed at the baseband receiver can be referred to as measured CSI (M-CSI).

[0180] Referring back to Figure 5According to one or more embodiments, the receiving device 502 can initiate a measurement activity (or Wi-Fi sensing session) for the purpose of Wi-Fi sensing. In the measurement activity, transmission exchanges between the receiving device 502 and a plurality of sensing transmitters 506-(1-M) can occur. In an example, these transmissions can be controlled with the MAC layer of the IEEE 802.11 stack. The representation of the propagation channel between the receiving device and the sensing transmitters is captured through the measure of channel state information (CSI).

[0181] According to an example embodiment, the receiving device 502 can initiate the measurement activity with one or more sensing trigger messages. In an embodiment, the generating unit 526 can be configured to generate a sensing trigger message to trigger a response from each of the plurality of sensing transmitters 506-(1-M). In an example, the sensing trigger message to each of the plurality of sensing transmitters 506-(1-M) can differ in content. The response to the sensing trigger message can be a sensing transmission. In an example, the sensing trigger message can contain a requested transmission configuration. Other examples of information / data contained in the sensing trigger message not discussed here are contemplated. According to an embodiment, the generating unit 526 can transmit the sensing trigger message to each of the plurality of sensing transmitters 506-(1-M). In an embodiment, the generating unit 526 can transmit the sensing trigger message to each of the plurality of sensing transmitters 506-(1-M) through the transmit antenna 514.

[0182] According to an embodiment, each of the plurality of sensing transmitters 506-(1-M) can receive the sensing trigger message from the receiving device 502. In response to receiving the sensing trigger message, each of the plurality of sensing transmitters 506-(1-M) can generate a sensing transmission. In an embodiment, each of the plurality of sensing transmitters 506-(1-M) can generate the sensing transmission using the requested transmission configuration defined by the sensing trigger message. Subsequently, each of the plurality of sensing transmitters 506-(1-M) can transmit the sensing transmission to the receiving device 502 in response to the sensing trigger message and according to the requested transmission configuration. In an example, the sensing transmission can contain a communicated transmission configuration corresponding to the requested transmission configuration.

[0183] According to an embodiment, the receiving device 502 can receive, from the plurality of sensing transmitters 506-(1-M), sensing transmissions transmitted in response to the one or more sensing trigger messages. The receiving device 502 can be configured to receive the sensing transmissions from the plurality of sensing transmitters 506-(1-M) through the receiving antenna 516. According to an embodiment, the generating unit 526 can be configured to generate, based on the sensing transmissions, sensing measurements representing measured channel state information (M-CSI).

[0184] C. Isolating the electronic environment to improve channel estimation

[0185] The present disclosure relates generally to systems and methods for Wi-Fi sensing. In particular, the present disclosure relates to systems and methods for isolating the electronic environment to improve channel estimation.

[0186] Figure 6 An instance 600 of measured channel versus OTA channel is depicted in accordance with some embodiments.

[0187] In an embodiment, the CSI obtained by processing the received signal at the baseband receiver contains the effects of the TFE 548-1 and the RFE 518 in addition to the components of the CSI of the OTA channel. Since the perturbations caused by the TFE 548-1 and the RFE 518 are not a result of objects in the sensing space, for accurate Wi-Fi sensing, the impact of the CSI caused by elements other than the OTA channel should be minimized.

[0188] As Figure 6 mentioned, the TFE 548-1 can contain the up-converter 550-1 and the power amplifier 552-1. Additionally, the RFE 518 can contain the AGC 520, the down-converter 522, the PLL unit 524, and the band-pass filter (BPF) 602. In an embodiment, the TFE 548-1 and the RFE 518 can cause perturbations in the M-CSI.

[0189] In an implementation, the gain of AGC 520 can decrease when the input signal is strong and increase when the input signal is weak. The gain of AGC 520 can be interchangeably referred to as AGC gain. The AGC gain can be applied equally across the entire frequency band of the input signal, thereby minimizing gain distortion of the processed input signal. Thus, when an object movement occurs in the OTA channel, the AGC gain can change uniformly (i.e., equally across all the entire frequency band) as the strength of the input signal changes. Accordingly, the amplitudes of all M-CSI tones can change based on the change in the AGC gain. According to an implementation, the AGC gain can be sensitive to interfering signals that can reach the input port of AGC 520. For example, signals emitted from nearby devices (e.g., devices that can not be related to the Wi-Fi sensing or sensing target) can reach the input port of AGC 520 as interference along with the desired signal. In some instances where the interference is strong and the desired signal is weak, the signal-to-interference-and-noise ratio (SINR) can be low. In an implementation, AGC 520 can not distinguish between the interference and the desired signal. In an instance, AGC 520 can treat the superposition of strong interference and weak signal as a strong input signal, and the AGC gain can decrease to a low value. Accordingly, the weak desired signal can not be amplified sufficiently, and detecting small CSI changes due to the movement of an object occurring in the OTA channel can become difficult, especially when there are multiple transmitters positioned in the same vicinity.

[0190] In an implementation, when a signal is received and applied to the input port of AGC 520, the amplitude of the signal is amplified by the AGC gain of AGC 520 that is set at that time. In cases where the AGC gain is applied unequally across the frequency band (e.g., in the case of very wideband signals), gain distortion can be characterized across the frequency band, and the AGC gain information can include multiple values that can each be applicable to a portion of the received signal, where the multiple values can include values that cover the entire frequency band of the received signal. In an instance, the multiple values can be computed from an AGC gain mask that describes the frequency response of AGC across the frequency band. In an instance, the AGC gain mask consists of two or more values that scale the value of AGC gain according to a frequency range that is a subset of the frequency band. In an instance, the ACG gain mask is stored by AGC 520 for the purpose of use in the described manner.

[0191] In one implementation, group delay is a characteristic of a physical channel or component (e.g., a filter). Group delay can represent the change in phase shift of a signal relative to frequency caused by the channel or component. In one instance, the group delay of an ideal channel (e.g., a distortion-free line-of-sight wireless orthogonal frequency division multiplexing (OFDM) channel or a distortion-free filter) is a straight line with a negative slope. However, for a non-ideal channel, the group delay of M-CSI is not a straight line. Instead, the group delay of M-CSI is a superposition of the group delays of all involved components, including the group delay of the ideal OFDM channel, the group delay due to real channel distortion, and the group delay of the non-ideal filter, and may have discontinuities. Before M-CSI can be used for sensing, the group delay of the ideal OFDM channel needs to be estimated with sufficient accuracy.

[0192] According to one embodiment, the baseband processor 528 of the receiving device 502 can be configured to perform CSI measurements to calculate M-CSI based on sensed transmissions received from a plurality of sense transmitters 506-(1-M). In some embodiments, the receiving device 502 can calculate the contribution of RFE 518 to M-CSI. In one example, RFE 518 can include analog and digital components. For example, RFE 518 can include analog and digital components through which the received signal travels from a reference point to a point where the generation unit 526 of the receiving device 502 can read the received signal. Figure 7 The image shows a representation 700 of the receiver chain of the receiving device 502. For example... Figure 7 The in-phase (I) and quad-phase (Q) modulation symbols arrive at the receiver front end, where synchronization, including frequency and timing recovery, is performed. Additionally, the time-domain guard period (cyclic prefix) is removed, and the receiver performs a Fast Fourier Transform (FFT) on the received signals (e.g., I and Q modulation symbols). Guard tone and DC tone are then removed. M-CSI is then generated before data demapping, deinterleaving (using a deinterleaver), de-puncturing, decoding (using a Viterbi decoder), and final descrambling (using a descrambler). Data bits are generated as a result of descrambling. The generated M-CSI is provided to generation unit 526.

[0193] According to one embodiment, M-CSI is modeled as including two components: the contribution of the physical channel between the receiving device 502 and each of the plurality of sensing transmitters 506-(1-M), including the features of interest in the sensing space; and the contribution of the receiving device 502's RFE 518.

[0194] In an embodiment, upon receiving the M-CSI, the receiving device 502 can send the M-CSI to the sensing decision unit 504. According to an embodiment, the receiving device 502 can also send receiver front-end state information (RFE-SI) along with the M-CSI to the sensing decision unit 504. In some embodiments, the baseband processor can send the M-CSI and the RFE-SI to the sensing decision unit 504. In an example, the RFE-SI can include at least one of the following: a phase variation indicator, an automatic gain controller (AGC) information, and a down-converter type information. Other examples of the RFE-SI not discussed here are contemplated herein. In an embodiment, the term "information" is used to capture signals and messages representing aspects of the RFE 518 equivalently.

[0195] Figure 8 An RFE perturbation correction architecture 800 according to some embodiments is depicted.

[0196] As Figure 8 mentioned, the RFE perturbation correction architecture 800 includes the RFE 518, the baseband processor 528, the sensing decision unit 504, and the sensing algorithm manager 508. The RFE 518 can include the AGC 520, the down-converter 522, and the PLL unit 524. Additionally, the baseband processor 528 can include an analog-to-digital (A / D) converter 804, a demodulator 806, and a CSI measurement unit 808. The sensing decision unit 504 includes a CSI equalization unit 536 and a group delay estimation and correction unit 538. In an embodiment, the CSI equalization unit 536, the group delay estimation and correction unit 538, and the sensing algorithm manager 508 can facilitate CSI processing.

[0197] In an embodiment, the baseband processor 528 can perform a plurality of sensing measurements based on the CSI contributed by the physical channel between the receiving device 502 and each of the plurality of sensing transmitters 506-(1-M) and the CSI contributed by the RFE 518 of the receiving device 502. The baseband processor 528 can then output the M-CSI representing each of the sensing measurements. In an embodiment, the M-CSI and the RFE-SI can be passed to the sensing decision unit 504 over the MLME interface or as dedicated data transfer from application to application. As Figure 8 mentioned, the RFE-SI can include AGC information (represented by arrow "A"), a phase variation indicator (represented by arrow "B"), and a down-converter type information (represented by arrow "C").

[0198] Although Figure 8The AGC information, phase change indicator, and downconverter type information are shown as bypassing the baseband processor 528, but in some embodiments, the AGC information, phase change indicator, and downconverter type information can be fed into the baseband processor 528 by the RFE 518, and the baseband processor 528 can output the AGC information, phase change indicator, and downconverter type information to the sensing decision unit 504.

[0199] In an embodiment, upon receiving the AGC information, an A / D converter of the baseband processor 528 can convert the AGC information from analog form to digital form. In an embodiment, the A / D converter can be the A / D converter 804 of the baseband processor 528. The baseband processor 528 can then pass the digital AGC information to the sensing decision unit 504. Similarly, upon receiving the phase change indicator, an A / D converter of the baseband processor 528 can convert the phase change indicator from analog form to digital form. In an embodiment, the A / D converter can be the same A / D converter that converted the AGC information, or the A / D converter can be the A / D converter 804 of the baseband processor 528. The baseband processor 528 can then pass the digital phase change indicator to the sensing algorithm manager 508. Additionally, upon receiving the downconverter type information, an A / D converter of the baseband processor 528 can convert the downconverter type information from analog form to digital form. In an embodiment, the A / D converter can be the same A / D converter that converted the AGC information and the phase change indicator, or the A / D converter can be the A / D converter 804 of the baseband processor 528. The baseband processor 528 can then pass the digital downconverter type information to the sensing decision unit 504.

[0200] According to an embodiment, the baseband processor 528 of the receiving device 502 can provide the RFE-SI as a message to the sensing decision unit 504 and the sensing algorithm manager 508. In an example embodiment, the baseband processor 528 can provide the RFE-SI as a single message through the MLME and the SME. In an embodiment, at least one of the baseband processor 528 and the RFE 518 of the receiving device 502 can provide the RFE-SI as one or more digital signals to the sensing decision unit 504 and the sensing algorithm manager 508. In some embodiments, at least one of the baseband processor 528 and the RFE 518 of the receiving device 502 can provide the RFE-SI as one or more digital signals and one or more analog signals to the sensing decision unit 504 and the sensing algorithm manager 508. In an example, the RFE-SI can be provided to the sensing decision unit 504 along with the M-CSI on a frame-by-frame basis. In an embodiment, the format of the signals and messages passed from the RFE 518 and the baseband processor 528 to the sensing decision unit 504 and the sensing algorithm manager 508 can be a standard format.

[0201] Figure 9 An example 900 of the RFE-SI in the RFE perturbation correction architecture 800 according to some embodiments is depicted. As discussed above, the baseband processor 528 can provide the RFE-SI as an RFE-SI message (denoted by arrow “D”) to the sensing decision unit 504 and the sensing algorithm manager 508. Additionally, the RFE 518 can provide the RFE-SI as an RFE-SI signal (denoted by arrow “E”) to the sensing decision unit 504 and the sensing algorithm manager 508. In an embodiment, either or both of the RFE-SI message and the RFE-SI signal can be present at any time. Figure 9

[0202] Figure 10 A structure 1000 of the PLL unit 524 according to some embodiments is depicted.

[0203] As Figure 10 ​The PLL unit 524 can include a phase detector 1002, a loop filter 1004, and a voltage-controlled oscillator (VCO) 1006. In an example, the phase detector 1002 can also be referred to as an interchangeable phase comparator. In an example, the loop filter 1004 can be a low-pass filter. In an implementation, the VCO 1006 can generate a sinusoidal waveform as its output. The sinusoidal waveform can be referred to as a VCO output waveform. In an implementation, the VCO output waveform can be sent back to the phase detector 1002 (indicated by arrow “F”). The VCO output waveform can also be sent to the frequency downconverter 522 as an output (indicated by arrow “G”). In an implementation, the phase detector 1002 can compare the phase of the VCO output waveform to the phase of the input waveform to generate an output voltage proportional to the difference between the two phase inputs. The phase detector 1002 can pass the output voltage to the loop filter 1004. In an implementation, the loop filter 1004 can filter the output voltage to suppress high-frequency components, such as interference and leakage of the input waveform through the phase detector 1002. The filtered output voltage can then be applied to the VCO 1006 to control the frequency of the VCO 1006. In an example, and since phase is the integral of frequency, the filtered output voltage applied to the VCO 1006 can also control the phase of the VCO output waveform. In an example, a higher filtered output voltage results in a higher frequency of the VCO 1006.

[0204] In an implementation, the phase detector 1002, the loop filter 1004, and the VCO 1006 can create a phase negative feedback loop that can pull the phase of the VCO output waveform to track the phase changes of the input waveform. In an implementation, when the phase negative feedback loop is in a locked state (i.e., in sync), the VCO output waveform can have the same frequency and phase as the input waveform, and thus be in sync with the input waveform.

[0205] In some examples, the PLL unit 524 can be in an unlocked state (i.e., the phase negative feedback loop is not in a locked state) due to, for example, strong impulse noise or interference or an unstable power supply. In the unlocked state, the VCO output waveform provided to the frequency downconverter 522 can have a phase offset or phase drift (equivalent to a frequency offset), which can be reflected in the M-CSI as distortion. This distortion in the M-CSI can be interpreted by the sensing algorithm as a perturbation in the OTA channel, resulting in a false detection.

[0206] In an example, the output voltage applied to the VCO 1006 can remain constant or near constant when the PLL unit 524 is in a locked state. In contrast, the output voltage applied to the VCO 1006 can vary more widely when the PLL unit 524 is in an unlocked state. Thus, the output voltage is an indicator of the phase variation that can exist in the M-CSI due to the VCO 1006. The output voltage can be referred to as a phase variation indicator, and it is provided to the sensing algorithm.

[0207] In an example, the phase variation indicator can be an analog signal that can be digitized before being provided to the sensing algorithm. For example, the analog phase variation indicator can be input to the baseband processor 528. In an implementation, the baseband processor 528 can convert the analog phase variation indicator to a digital phase variation indicator, and can provide the digital phase variation indicator to the sensing algorithm. In some embodiments, the PLL unit 524 can be a digital PLL, and the phase variation indicator can already exist in digital form. Additionally, in some embodiments, the sensing decision unit 504 can include an A / D converter that can convert the analog phase variation indicator to a digital signal. Thus, the voltage output from the loop filter 1004 and applied to the VCO 1006 can be provided as a phase variation indicator to the sensing algorithm. In an example, the phase variation indicator can indicate that the PLL unit 524 is unlocked, and in this case, the sensing algorithm can not consider CSI variations to avoid false motion detection. In some implementations, the phase variation indicator can be further filtered before it is used by the sensing algorithm. In an example, the phase variation indicator can be low-pass filtered to suppress high frequency variations that can be artifacts of other signal impairments.

[0208] A signal, such as a multi-tone OFDM signal, that includes a series of frequency components passing through an ideal system, such as an ideal channel or an ideal filter, experiences the same time delay across all frequency components. Thus, the phase shift of each frequency component can be proportional to the frequency of each frequency component. Figure 11 An example 1100 of the group delay of an ideal channel, such as an undistorted channel (also referred to as an undistorted line-of-sight wireless OFDM channel) or an undistorted filter, is shown in FIG. 11. As described in FIG. 11, Figure 11 The group delay of an undistorted channel is a straight line with a negative slope. In cases where the Wi-Fi channel is not ideal, the group delay of the M-CSI can not be as described in example 1100. In such cases, the group delay of the M-CSI can be a superposition of the group delays contributed by each signal processing element, including the group delay of the ideal channel.

[0209] In an embodiment, for M-CSI to be used for motion sensing, it can be necessary to estimate the group delay of the channel with sufficient accuracy. However, the group delay of the M-CSI can include the group delay of the filter used in the downconverter 522, and the nature or form of the group delay of the filter used in the downconverter 522 can depend on the type of downconverter 522 implemented (i.e., whether the downconverter 522 is a low-IF downconverter or a zero-IF downconverter).

[0210] According to an embodiment, the radio frequency signal can be mathematically expressed using Equation (8) provided below.

[0211]

[0212] where Real{x} represents the real part x of a complex number, f c represents the carrier frequency, I(t) represents the in-phase component of the baseband signal, and Q(t) represents the quadrature component of the baseband signal. In an embodiment, the downconverter 522 can be configured to recover the in-phase component I(t) and the quadrature component Q(t) from the received radio frequency signal.

[0213] Figure 12 A block diagram of a zero-IF downconverter 1200 having two branches is depicted in accordance with some embodiments.

[0214] In an embodiment, the zero-IF downconverter 1200 can be a downconverter having a single mixer stage for converting a received radio frequency signal to a baseband signal in a single step. In an example, the radio frequency signal can be received by the receive antenna 516 of the receiving device 502. As Figure 12 depicted, the zero-IF downconverter 1200 can include two branches, namely a first branch 1202 and a second branch 1204. Further, as Figure 12 depicted, the outputs of the first branch 1202 and the second branch 1204 are the in-phase I(t) baseband signal and the quadrature Q(t) baseband signal, respectively. The first branch 1202 can include a first mixer 1206, a first low-pass filter 1208, and a first notch filter 1210. In an embodiment, the first mixer 1206 can be a non-linear device that multiplies the radio frequency signal with a local carrier f c whose frequency and phase are synchronized with the radio frequency signal. In an example, the local carrier f cgenerated by the PLL unit 524. According to an embodiment, the output of the first mixer 1206 can include a baseband signal, a high frequency component, and a direct current (DC) component. In an example, of these components, only the baseband signal is useful and is the desired signal. The undesired high frequency component can be suppressed (or attenuated) by the first low pass filter 1208, and the DC component can be suppressed by the first notch filter 1210. Additionally, the second branch 1204 can include a second mixer 1212, a second low pass filter 1214, and a second notch filter 1216.

[0215] According to aspects of the disclosure, the description of the first branch 1202, the first mixer 1206, the first low pass filter 1208, and the first notch filter 1210 apply equally to the second branch 1204, the second mixer 1212, the second low pass filter 1214, and the second notch filter 1216, respectively.

[0216] In an embodiment, a notch filter can be a type of band-stop filter that can attenuate frequencies within a particular range while passing all other frequencies without attenuation (or with minimal attenuation). Figure 13A and Figure 13B The characteristics of an example of a notch filter according to some embodiments are depicted. In Figure 13A In particular, plot 1302 shows the variation of the amplitude of the notch filter with respect to frequency (clearly showing the frequency-selective attenuation). In Figure 13B In particular, plot 1304 shows the variation of the phase shift of the notch filter with respect to frequency (i.e., the group delay). It is shown that the group delay has a phase discontinuity (i.e., a phase jump) at the center frequency f0of the notch filter.

[0217] According to an embodiment, the group delay of the output of the notch filter can have a phase discontinuity at the middle of the frequency band. For example, for a 20 MHz frequency band comprising 52 subcarriers, the group delay can have a discontinuity between the 26th subcarrier and the 27th subcarrier. In an embodiment, in order to accurately estimate the group delay from the M-CSI, the effect of this discontinuity is eliminated. To this end, the tones of the M-CSI can be divided into two sets, each set being independently processed to yield an estimate of the group delay while avoiding the discontinuity. For example, for a 20 MHz frequency band comprising 52 subcarriers, the group delay of the first 26 tones of the M-CSI and the group delay of the last 26 tones of the M-CSI can be separately and independently estimated to yield two components of the estimated group delay. Thus, the effect of the phase discontinuity caused by the notch filter can be avoided during the estimation. In an embodiment, after separately estimating the two components of the group delay, the discontinuity of the group delay can be corrected or removed by further processing, and in some embodiments, a single group delay can be computed that mitigates the discontinuity caused by the notch filter 1210 or the notch filter 1216.

[0218] Figure 14 A block diagram of a two-stage low-IF downconverter 1400 with two branches is depicted in accordance with some embodiments.

[0219] In an embodiment, the two-stage low-IF downconverter 1400 can be a downconverter with two stages of mixers (i.e., a first stage and a second stage). The first stage can convert a received radio frequency signal to a low-IF signal, where a bandpass filter can allow only the desired IF signal to pass. Additionally, the bandpass filter can attenuate all other undesired lower and higher frequency components. The second stage can convert the IF signal to a baseband signal. As Figure 14 depicted, the low-IF downconverter 1400 can include two branches, a first branch 1402 and a second branch 1404, and the outputs of the first branch 1402 and the second branch 1404 are in-phase I(t) baseband signal and quadrature Q(t) baseband signal, respectively. The first branch 1402 can include a first mixer 1406, a first bandpass filter 1408, a second mixer 1410, and a first lowpass filter 1412. Additionally, the second branch 1404 can include a third mixer 1414, a second bandpass filter 1416, a fourth mixer 1418, and a second lowpass filter 1420.

[0220] In an embodiment of the low-IF downconverter 1400, the resulting baseband signal in each of the first branch 1402 and the second branch 1404 can not include a DC component. Thus, the low-IF downconverter 1400 can not require a notch filter, and thus the group delay of the M-CSI can not have a discontinuity within its frequency band.

[0221] Referring again to Figure 5 In an embodiment, the sensing decision unit 504 can be configured to receive the M-CSI representing sensing measurements from the receiving device 502. Additionally, the sensing decision unit 504 can be configured to receive the RFE-SI from the receiving device 502. In an example embodiment, the sensing decision unit 504 can receive the M-CSI and the RFE-SI from the receiving device 502 through the receiving antenna 534. In an embodiment, the sensing decision unit 504 can receive the M-CSI through the MLME and the SME.

[0222] According to an embodiment, upon receiving the M-CSI and the RFE-SI, the sensing decision unit 504 can be configured to eliminate or reduce the impact of the disturbance caused by the RFE 518 in the M-CSI on the sensing decision. In an embodiment, the sensing decision unit 504 can determine sensing decision input information from the M-CSI and the RFE-SI. In an example, the sensing decision input information can include processed channel state information (P-CSI).

[0223] According to some embodiments, the CSI equalization unit 536 can determine whether the phase variation indicator indicates a phase variation in the M-CSI. In response to determining that the phase variation indicator indicates a phase variation in the M-CSI, the CSI equalization unit 536 can set the sensing decision input information to a null input. In an example, the CSI equalization unit 536 can discard the M-CSI and can not further pass the M-CSI to, for example, the sensing algorithm manager 508.

[0224] According to some embodiments, the CSI equalization unit 536 can be configured to determine, from the AGC information, an AGC gain applied by the AGC 520 to the sensing transmission captured in the M-CSI to perform equalization of the M-CSI. In an example, the AGC information can be equivalent to the AGC gain applied by the AGC 520 to the sensing transmission. In some embodiments, the CSI equalization unit 536 can perform equalization of the M-CSI based on both the AGC information and the strength of the M-CSI. In an example, the strength of the M-CSI or a portion thereof can be represented by a root mean square value of the amplitudes of all or a portion of the M-CSI tones.

[0225] In an embodiment, the CSI equalization unit 536 can make a first determination of whether the AGC information exceeds a first threshold. In an embodiment, the CSI equalization unit 536 can be configured to make a second determination of whether the strength of the portion of the M-CSI exceeds a second threshold. In response to determining that the AGC information does not exceed the first threshold and that the strength of the portion of the M-CSI does not exceed the second threshold, the CSI equalization unit 536 can perform a gain adjustment on the M-CSI. In an embodiment, the CSI equalization unit 536 can perform the gain adjustment by multiplying the M-CSI or portions of the M-CSI by an AGC scaling factor. This operation generates P-CSI. According to an embodiment, the CSI equalization unit 536 can set the sensing decision input information to the P-CSI.

[0226] In an embodiment, the CSI equalization unit 536 can multiply the amplitudes of all of the M-CSI tones by an AGC scaling factor to apply a gain to all or a portion of the M-CSI tones provided by the baseband processor 528. In an example, the CSI equalization unit 536 can multiply the amplitudes of all or a portion of the M-CSI tones provided by the baseband processor 528 by an AGC scaling factor that is proportional to the inverse of the AGC information to create P-CSI. In an embodiment, the CSI equalization unit 536 can use Equation (9) provided below to determine the P-CSI.

[0227]

[0228] where AGC scale is the AGC scaling factor, a is a multiplier, and b is an offset.

[0229] In some embodiments, the CSI equalization unit 536 can be configured to filter the AGC information using a low pass filter prior to making the first determination and the second determination.

[0230] According to some embodiments, the determination that the AGC information does not exceed the first threshold can indicate that the RFE 518 is largely saturated by an interferer, such that the AGC gain is significantly reduced, and the likelihood of resolution of signal perturbations (passed to the A / D converter 804 of the baseband processor 528) can be very low due to the interference signal dominating the available A / D resolution. In such cases, the accuracy of the resulting measurements can be insufficient to perform Wi-Fi sensing even subsequent to multiplication by the CSI equalization unit 536. In an example, the CSI equalization unit 536 can set the sensing decision input information to a null input in response to the determination that the AGC information does not exceed the first threshold, or in another example, the CSI equalization unit can discard the M-CSI and not further pass the M-CSI to, for example, the sensing algorithm manager 508.

[0231] According to some embodiments, CSI equalization unit 536 can set the sensing decision input information to M-CSI in response to a first determination that the AGC information exceeds a first threshold and a second determination that a root mean square of the portion of M-CSI exceeds a second threshold.

[0232] In an embodiment, CSI equalization unit 536 can calculate a strength of relevant tones of M-CSI. In an example, the relevant tones of M-CSI can be the tones of M-CSI that correspond to the sensing transmissions from sensing transmitters 506-(1-M) received by receiving device 502. In an example, the relevant tones of M-CSI can be a subset or a portion of all tones of M-CSI. If the strength of the relevant tones of M-CSI is below a second threshold, CSI equalization unit 536 can create P-CSI by multiplying the amplitudes of the relevant tones of M-CSI tones by the AGC scaling factor determined according to equation (9). In some embodiments, if the AGC information is below the first threshold, however the strength of the relevant tones of M-CSI is greater than the second threshold, M-CSI can not be strong enough to detect subject movement. Accordingly, CSI equalization unit 536 can set P-CSI to be equal to M-CSI, and P-CSI can be considered equivalent to M-CSI. In an embodiment, setting P-CSI to be M-CSI corresponding to a low AGC gain can facilitate improving the detectability of subject movement.

[0233] According to an embodiment, group delay estimation and correction unit 538 can calculate a group delay of M-CSI according to downconverter type information. In an embodiment, group delay estimation and correction unit 538 can process all tones of M-CSI together as a single piece of information. In an embodiment, group delay estimation and correction unit 538 can generate P-CSI by adjusting M-CSI according to downconverter type information. Additionally, group delay estimation and correction unit 538 can set the sensing decision input information to P-CSI.

[0234] In one implementation, the group delay estimation and correction unit 538 can determine whether the downconverter 522 is a zero-IF downconverter or a low-IF downconverter. In response to determining that the downconverter 522 is a zero-IF downconverter, the group delay estimation and correction unit 538 can independently calculate the group delay on a lower portion and an upper portion of the signal bandwidth and combine the individual calculations of the group delay. Additionally, the group delay estimation and correction unit 538 can generate the P-CSI from a single calculation of the combined group delay. Additionally, in response to determining that the downconverter 522 is a low-IF downconverter, the group delay estimation and correction unit 538 can calculate the group delay on the entire signal bandwidth. Additionally, the group delay estimation and correction unit 538 can generate the P-CSI from the calculated group delay. In an example, in response to determining that the downconverter 522 is a low-IF downconverter, the group delay estimation and correction unit 538 can not perform any processing on the signal and generate the P-CSI without any estimation of the group delay.

[0235] According to an implementation, the sensing decision unit 504 can be configured to send the sensing decision input information (i.e., the P-CSI) to the sensing algorithm manager 508 to make the sensing decision. In an example implementation, the sensing decision unit 504 can send the sensing decision input information to the sensing algorithm manager 508 through the transmit antenna 532.

[0236] Figure 15 A flowchart 1500 for determining sensing decision input information is depicted in accordance with some embodiments.

[0237] In a brief overview of one implementation of the flowchart 1500, at step 1502, the M-CSI representing sensing measurements is received. At step 1504, the RFE-SI is received. At step 1506, the sensing decision input information is determined from the RFE-SI.

[0238] Step 1502 includes receiving the M-CSI representing sensing measurements. According to an implementation, the sensing decision unit 504 can be configured to receive the M-CSI representing sensing measurements from the receiving device 502.

[0239] Step 1504 includes receiving RFE-SI. According to an implementation, sensing decision unit 504 can be configured to receive RFE-SI from receiving device 502. In an example, RFE-SI can include at least one of: a phase change indicator, automatic gain controller (AGC) information, and downconverter type information. In an implementation, sensing decision unit 504 can receive RFE-SI as a message through baseband processor 528 of receiving device 502. In some implementations, sensing decision unit 504 can receive RFE-SI as one or more digital signals through at least one of baseband processor 528 of receiving device 502 and RFE 518. In some implementations, sensing decision unit 504 can receive RFE-SI as one or more digital signals and one or more analog signals through at least one of baseband processor 528 of receiving device 502 and RFE 518.

[0240] Step 1506 includes determining sensing decision input information from RFE-SI. According to an implementation, sensing decision unit 504 can be configured to determine sensing decision input information from RFE-SI.

[0241] Figure 16 A flow diagram 1600 for transmitting M-CSI to sensing decision unit 504 is depicted in accordance with some embodiments.

[0242] In brief overview of an implementation of flow diagram 1600, at step 1602, sensing transmissions are received from a plurality of sensing transmitters 506-(1-M). At step 1604, M-CSI is generated based on the sensing transmissions. At step 1606, the M-CSI is transmitted to sensing decision unit 504.

[0243] Step 1602 includes receiving sensing transmissions from a plurality of sensing transmitters 506-(1-M). According to an implementation, receiving device 502 can be configured to receive sensing transmissions from a plurality of sensing transmitters 506-(1-M).

[0244] Step 1604 includes generating M-CSI based on the sensing transmissions. According to an implementation, receiving device 502 can be configured to generate M-CSI based on the sensing transmissions.

[0245] Step 1606 includes transmitting the M-CSI to sensing decision unit 504. According to an implementation, receiving device 502 can be configured to transmit the M-CSI to sensing decision unit 504.

[0246] Figure 17 A flow diagram 1700 for determining sensing decision input information from RFE-SI, where RFE-SI includes a phase change indicator, is depicted in accordance with some embodiments.

[0247] In brief overview of one embodiment of flowchart 1700, at step 1702, M-CSI is received that is representative of sensing measurements. At step 1704, RFE-SI is received, where the RFE-SI includes a phase change indicator. At step 1706, sensing decision input information is determined from the RFE-SI, where determining the sensing decision input information includes setting the sensing decision input information to a null input responsive to a determination that the phase change indicator indicates a phase change in the M-CSI.

[0248] Step 1702 includes receiving M-CSI that is representative of sensing measurements. According to an embodiment, sensing decision unit 504 can be configured to receive M-CSI that is representative of sensing measurements from receiving device 502.

[0249] Step 1704 includes receiving RFE-SI, where the RFE-SI includes a phase change indicator. According to an embodiment, sensing decision unit 504 can be configured to receive RFE-SI from receiving device 502. In one example, the RFE-SI can include a phase change indicator.

[0250] Step 1706 includes determining sensing decision input information from the RFE-SI, where determining the sensing decision input information includes setting the sensing decision input information to a null input responsive to a determination that the phase change indicator indicates a phase change in the M-CSI. According to an embodiment, sensing decision unit 504 can be configured to determine whether the phase change indicator indicates a phase change in the M-CSI. Responsive to a determination that the phase change indicator indicates a phase change in the M-CSI, sensing decision unit 504 can set the sensing decision input information to a null input.

[0251] Figure 18 A flowchart 1800 is depicted for determining sensing decision input information from RFE-SI, where the RFE-SI includes downconverter type information, according to some embodiments.

[0252] In brief overview of one embodiment of flowchart 1800, at step 1802, M-CSI is received that is representative of sensing measurements. At step 1804, RFE-SI is received, where the RFE-SI includes downconverter type information. At step 1806, sensing decision input information is determined from the RFE-SI, where determining the sensing decision input information includes: calculating a group delay of the M-CSI from the downconverter type information; generating P-CSI by adjusting the M-CSI from the group delay; and setting the sensing decision input information to the P-CSI. At step 1808, the sensing decision input information is sent to sensing algorithm manager 508.

[0253] Step 1802 includes receiving M-CSI representing sensing measurements. According to an embodiment, sensing decision unit 504 can be configured to receive M-CSI representing sensing measurements from receiving device 502.

[0254] Step 1804 includes receiving RFE-SI, where RFE-SI includes downconverter type information. According to an embodiment, sensing decision unit 504 can be configured to receive RFE-SI from receiving device 502. In an example, RFE-SI can include downconverter type information.

[0255] Step 1806 includes determining sensing decision input information from RFE-SI, where determining sensing decision input information includes: calculating a group delay of M-CSI from downconverter type information; generating P-CSI by adjusting M-CSI from the group delay; and setting sensing decision input information to P-CSI. According to an embodiment, sensing decision unit 504 can be configured to determine sensing decision input information based on: calculating a group delay of M-CSI from downconverter type information; generating P-CSI by adjusting M-CSI from the group delay; and setting sensing decision input information to P-CSI.

[0256] Step 1808 includes sending sensing decision input information to sensing algorithm manager 508. According to an embodiment, sensing decision unit 504 can be configured to send sensing decision input information to sensing algorithm manager 508.

[0257] Figure 19A and Figure 19B A flowchart 1900 for determining sensing decision input information from RFE-SI, where RFE-SI includes AGC information, is depicted in accordance with some embodiments.

[0258] In brief overview of an embodiment of flowchart 1900, at step 1902, M-CSI representing sensing measurements is received. At step 1904, RFE-SI is received, where RFE-SI includes AGC information. At step 1906, it is determined whether AGC information exceeds a first threshold. At step 1908, it is determined whether a root mean square of a portion of M-CSI exceeds a second threshold. At step 1910, sensing decision input information is set to a null input. At step 1912, P-CSI is generated by multiplying the portion of M-CSI by an AGC scaling factor. At step 1914, sensing decision input information is set to P-CSI. At step 1916, sensing decision input information is sent to sensing algorithm manager 508.

[0259] Step 1902 includes receiving M-CSI representing sensing measurements. According to an implementation, sensing decision unit 504 can be configured to receive M-CSI representing sensing measurements from receiving device 502.

[0260] Step 1904 includes receiving RFE-SI, where RFE-SI includes AGC information. According to an implementation, sensing decision unit 504 can be configured to receive RFE-SI from receiving device 502. In an example, RFE-SI can include AGC information.

[0261] Step 1906 includes determining whether AGC information exceeds a first threshold. According to an implementation, sensing decision unit 504 can be configured to determine whether AGC information exceeds a first threshold. If it is determined that AGC information exceeds a first threshold, flowchart 1900 proceeds to step 1910 ("YES" branch), and if it is determined that AGC information does not exceed a first threshold, flowchart 1900 proceeds to step 1912 ("NO" branch).

[0262] Step 1908 includes determining whether a root mean square of a portion of M-CSI exceeds a second threshold. According to an implementation, sensing decision unit 504 can be configured to determine whether a root mean square of the portion of M-CSI exceeds a second threshold. If it is determined that a root mean square of the portion of M-CSI exceeds a second threshold, flowchart 1900 proceeds to step 1910 ("YES" branch), and if it is determined that a root mean square of the portion of M-CSI does not exceed a second threshold, flowchart 1900 proceeds to step 1912 ("NO" branch).

[0263] Step 1910 includes setting sensing decision input information to M-CSI input. According to an implementation, sensing decision unit 504 can be configured to set sensing decision input information to M-CSI.

[0264] Step 1912 includes generating P-CSI by multiplying the portion of M-CSI by an AGC scaling factor. According to an implementation, sensing decision unit 504 can be configured to generate P-CSI by multiplying the portion of M-CSI by an AGC scaling factor.

[0265] Step 1914 includes setting sensing decision input information to P-CSI. According to an implementation, sensing decision unit 504 can be configured to set sensing decision input information to P-CSI.

[0266] Step 1916 includes sending sensing decision input information to sensing algorithm manager 508. According to an implementation, sensing decision unit 504 can be configured to send sensing decision input information to sensing algorithm manager 508.

[0267] Example 1 is a method for Wi-Fi sensing, the method performed by a sensing decision unit operating on at least one processor. The method includes receiving, by the sensing decision unit, measured channel state information (M-CSI) representing sensing measurements; receiving, by the sensing decision unit, receiver front end state information (RFE-SI); and determining, by the sensing decision unit and in accordance with the RFE-SI, sensing decision input information.

[0268] Example 2 is the method of Example 1, further comprising receiving, by a receiving apparatus including a receiver front end (RFE) having a receive antenna, sensing transmissions from a plurality of sensing transmitters; and generating, by the receiving apparatus, the M-CSI based on the sensing transmissions.

[0269] Example 3 is the method of Example 2, wherein the receiving apparatus further includes the at least one processor.

[0270] Example 4 is the method of Example 2 or 3, wherein the RFE-SI is provided as a message by a baseband processor of the receiving apparatus to the sensing decision unit.

[0271] Example 5 is the method of any one of Examples 2-4, wherein the RFE-SI is provided as one or more digital signals by at least one of a baseband processor of the receiving apparatus and the RFE to the sensing decision unit.

[0272] Example 6 is the method of any one of Examples 2-5, wherein the RFE-SI is provided as one or more digital signals and one or more analog signals by at least one of a baseband processor of the receiving apparatus and the RFE to the sensing decision unit.

[0273] Example 7 is the method of any one of Examples 1-6, wherein the RFE-SI includes a phase change indicator.

[0274] Example 8 is the method of Example 7, wherein determining the sensing decision input information includes setting the sensing decision input information to a null input in response to a determination that the phase change indicator indicates a phase change in the M-CSI.

[0275] Example 9 is the method of any one of Examples 1-8, wherein the RFE-SI includes automatic gain controller (AGC) information.

[0276] Example 10 is the method of Example 9, wherein determining the sensing decision input information includes setting the sensing decision input information to null input responsive to a determination that the AGC information does not exceed a first threshold.

[0277] Example 11 is the method of Example 9 or 10, wherein determining the sensing decision input information includes: generating processed channel state information (P-CSI) by multiplying a portion of the M-CSI by an AGC scaling factor responsive to a determination that the AGC information does not exceed a first threshold; and setting the sensing decision input information to the P-CSI.

[0278] Example 12 is the method of any of Examples 9 to 11, wherein determining the sensing decision input information includes: generating processed channel state information (P-CSI) by multiplying a portion of the M-CSI by an AGC scaling factor responsive to a first determination that the AGC information does not exceed a first threshold and a second determination that an intensity of the portion of the M-CSI does not exceed a second threshold; and setting the sensing decision input information to the P-CSI.

[0279] Example 13 is the method of any of Examples 9 to 12, wherein determining the sensing decision input information includes: setting the sensing decision input information to the M-CSI responsive to a first determination that the AGC information exceeds a first threshold and a second determination that an intensity of a portion of the M-CSI exceeds a second threshold.

[0280] Example 14 is the method of any of Examples 1 to 13, wherein the RFE-SI includes downconverter type information.

[0281] Example 15 is the method of Example 14, wherein determining the sensing decision input information includes: calculating a group delay of the M-CSI from the downconverter type information; generating processed channel state information (P-CSI) by adjusting the M-CSI from the group delay; and setting the sensing decision input information to the P-CSI.

[0282] Example 16 is the method of any of Examples 11 to 15, further comprising sending the sensing decision input information to a sensing algorithm manager.

[0283] Example 17 is the method of any of Examples 12 to 16, further comprising sending the sensing decision input information to a sensing algorithm manager.

[0284] Example 18 is the method of any of Examples 15-17, further comprising sending the sensing decision input information to a sensing algorithm manager.

[0285] Example 19 is a system for Wi-Fi sensing. The system comprises at least one processor configured to execute instructions to operate a sensing decision unit, the instructions configured to: receive measured channel state information (M-CSI) representing sensing measurements; receive receiver front-end state information (RFE-SI); and determine sensing decision input information as a function of the RFE-SI.

[0286] Example 20 is the system of Example 19, further comprising a receiving device that includes a receiver front-end (RFE) having a receive antenna, and is configured to: receive sensing transmissions from a plurality of sensing transmitters; and generate the M-CSI based on the sensing transmissions.

[0287] Example 21 is the system of Example 20, wherein the at least one processor is included in the receiving device.

[0288] Example 22 is the system of Example 20 or 21, wherein the receiving device further comprises a baseband processor configured to provide the RFE-SI as a message to the sensing decision unit.

[0289] Example 23 is the system of any of Examples 20-22, wherein the receiving device is further configured to provide the RFE-SI as one or more digital signals to the sensing decision unit.

[0290] Example 24 is the system of any of Examples 20-23, wherein the receiving device is further configured to provide the RFE-SI as one or more digital signals and one or more analog signals to the sensing decision unit.

[0291] Example 25 is the system of any of Examples 19-24, wherein the RFE-SI includes a phase change indicator.

[0292] Example 26 is the system of Example 25, wherein the instructions to determine the sensing decision input information include instructions to set the sensing decision input information to a null input in response to a determination that the phase change indicator indicates a phase change in the M-CSI.

[0293] Example 27 is the system of any of Examples 19-26, wherein the RFE-SI includes automatic gain controller (AGC) information.

[0294] Example 28 is the system of Example 27, wherein the instructions to determine the sensing decision input information include instructions to set the sensing decision input information to empty input in response to a determination that the AGC information does not exceed a first threshold.

[0295] Example 29 is the system of Example 27 or 28, wherein the instructions to determine the sensing decision input information include instructions to: generate processed channel state information (P-CSI) by multiplying a portion of the M-CSI by an AGC scaling factor in response to a determination that the AGC information does not exceed a first threshold; and set the sensing decision input information to the P-CSI.

[0296] Example 30 is the system of any of Examples 27 to 29, wherein the instructions to determine the sensing decision input information include instructions to: generate processed channel state information (P-CSI) by multiplying a portion of the M-CSI by an AGC scaling factor in response to a first determination that the AGC information does not exceed a first threshold and a second determination that an intensity of the portion of the M-CSI does not exceed a second threshold; and set the sensing decision output information to the P-CSI.

[0297] Example 31 is the system of any of Examples 27 to 30, wherein the instructions to determine the sensing decision input information include instructions to: set the sensing decision input information to the M-CSI in response to a first determination that the AGC information exceeds a first threshold and a second determination that an intensity of a portion of the M-CSI exceeds a second threshold.

[0298] Example 32 is the system of any of Examples 19 to 31, wherein the RFE-SI includes downconverter type information.

[0299] Example 33 is the system of Example 32, wherein the instructions to determine the sensing decision input information include instructions to: calculate a group delay of the M-CSI from the downconverter type information; generate processed channel state information (P-CSI) by adjusting the M-CSI according to the group delay; and set the sensing decision input information to the P-CSI.

[0300] Example 34 is the system of any of Examples 29 to 33, wherein the at least one processor is further configured with instructions to send the sensing decision input information to a sensing algorithm manager.

[0301] Example 35 is the system of any of Examples 30-34, wherein the at least one processor is further configured with instructions to send the sensing decision input information to a sensing algorithm manager.

[0302] Example 36 is the system of any of Examples 33-35, wherein the at least one processor is further configured with instructions to send the sensing decision input information to a sensing algorithm manager.

[0303] While various embodiments of methods and systems have been described, these embodiments are illustrative only and are not intended to limit the scope of the described methods or systems in any way. Alterations and further modifications of the described methods and systems can be practiced by those skilled in the relevant art without departing from the spirit of the described methods and systems. Accordingly, the scope of the methods and systems described herein should not be limited by any of the illustrative embodiments, and should instead be defined in accordance with the following claims and their equivalents.

Claims

1. A method for Wi-Fi sensing, the method performed by a sensing initiator comprising at least one processor, the method comprising: obtaining, by the sensing initiator, sensing measurements comprising channel state information, CSI; obtaining, by the sensing initiator, receiver front-end state information, RFE-SI, comprising automatic gain controller, AGC, information; and transmitting, by the sensing initiator, the sensing measurements and the RFE-SI to a sensing algorithm using a MAC layer management entity, MLME, interface.

2. The method of claim 1, wherein the sensing measurements are based on one or more sensing transmissions from a sensing transmitter to a sensing receiver.

3. The method of claim 2, wherein the sensing transmissions are null data PHY layer protocol data units or null data, NDPs, PPDU.

4. The method of claim 3, wherein the sensing transmissions are initiated by the sensing initiator. the sensing initiator is a sensing receiver, the method further comprising:

5. The method of claim 1, wherein, receiving, by a receiver front-end, RFE, having a receive antenna of the sensing receiver, sensing transmissions from a plurality of sensing transmitters; and generating, by a baseband receiver of the sensing receiver, the CSI based on the sensing transmissions. the RFE-SI is provided by at least one of the baseband receiver and the RFE to the at least one processor as a message.

6. The method of claim 5, wherein, the RFE-SI is provided by at least one of the baseband receiver and the RFE to the at least one processor as one or more digital signals.

7. The method of claim 5, wherein, the RFE-SI is provided by at least one of the baseband receiver and the RFE to the at least one processor as one or more digital signals and one or more analog signals.

8. The method of claim 5, wherein, the RFE-SI comprises a phase change indicator.

9. The method of claim 1, wherein, the RFE-SI comprises down-converter type information.

10. The method of claim 1, wherein, the sensing initiator is a sensing transmitter.

11. The method of claim 1, wherein, 12. The method of claim 11, further comprising: receiving, by a receive antenna of the sensing transmitter, one or more sensing measurement reports comprising the RFE-SI and the sensing measurements from one or more sensing receivers.

13. A system for Wi-Fi sensing, the system comprising: a sensing initiator comprising at least one processor configured to execute instructions configured for: obtaining sensing measurements comprising channel state information, CSI; obtaining receiver front-end state information, RFE-SI, comprising automatic gain controller, AGC, information; and transmitting the sensing measurements and the RFE-SI to a sensing algorithm using a MAC layer management entity, MLME, interface.

14. The system of claim 13, wherein the sensing measurements are based on one or more sensing transmissions from a sensing transmitter to a sensing receiver.

15. The system of claim 14, wherein the sensing transmissions are null data PHY layer protocol data units or null data, NDPs, PPDU.

16. The system of claim 15, wherein the sensing transmissions are initiated by the sensing initiator. the sensing initiator is a sensing receiver, the sensing receiver comprising:

17. The system of claim 13, wherein, ​ a receiver front end, RFE, having a receive antenna and a baseband receiver, and further configured for: receiving, by the RFE, sensing transmissions from a plurality of sensing transmitters; and generating, by the baseband receiver, the CSI based on the sensing transmissions.

18. The system of claim 17, wherein, at least one of the baseband receiver and the RFE is configured to provide the RFE-SI as a message to the at least one processor.

19. The system of claim 17, wherein, at least one of the baseband receiver and the RFE is configured to provide the RFE-SI as one or more digital signals to the at least one processor.

20. The system of claim 17, wherein, at least one of the baseband receiver and the RFE is configured to provide the RFE-SI as one or more digital signals and one or more analog signals to the at least one processor.

21. The system of claim 13, wherein, the RFE-SI includes a phase change indicator.

22. The system of claim 13, wherein, the RFE-SI includes down-converter type information.

23. The system of claim 13, wherein, the sensing initiator is a sensing transmitter.

24. The system of claim 23, wherein, the sensing transmitter is configured to receive, from one or more sensing receivers through a receive antenna, one or more sensing measurement reports including RFE-SI.

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