CN118302649A

CN118302649A - Isolating electronic environment to improve channel estimation

Info

Publication number: CN118302649A
Application number: CN202280072108.4A
Authority: CN
Inventors: C·贝格; M·欧密尔
Original assignee: Cognitive Systems Corp
Current assignee: Cognitive Systems Corp
Priority date: 2021-10-29
Filing date: 2022-10-26
Publication date: 2024-07-05
Also published as: CN118828668A

Abstract

A system and method 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, the at least one processor being configured to execute instructions. Measured channel state information (M-CSI) and receiver front-end state information (RFE-SI) representing sensing measurement results are received. Based on the RFE-SI, sensing decision input information is determined.

Description

Isolating electronic environment to improve channel estimation

Cross Reference to Related Applications

The present application claims the benefit of U.S. provisional application No. 63/273,572 filed on 10/29 of 2021 and U.S. provisional application No. 63/284,305 filed on 11/30 of 2021, the entire contents of which are incorporated herein by reference.

Technical Field

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.

Background

Motion detection systems have been used to detect movement of an object, for example, in an indoor or outdoor area. In some example motion detection systems, infrared or optical sensors are used to detect movement of an object in the sensor field of view. Motion detection systems have been used in security systems, automatic control systems, and other types of systems. Wi-Fi sensing systems are one of the most recent additions to motion detection systems. The Wi-Fi sensing system may be a network of Wi-Fi enabled devices, which may be part of an IEEE 802.11 network. In an example, a Wi-Fi sensing system may be configured to detect a feature of interest in a sensing space. The sensing space may refer to any physical space in which the Wi-Fi sensing system may operate, such as a residential site, workplace, shopping mall, gym or stadium, garden, or any other physical space. Features of interest may include motion and motion tracking of objects, presence detection, intrusion detection, gesture recognition, fall detection, respiratory rate detection, and other applications.

In Wi-Fi sensing systems, wi-Fi sensing may be performed based on detecting disturbances 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 a wireless channel between the transmitter antenna and the receiver antenna. In an example, the transmitted signal may be generated at a baseband transmitter and received at a baseband receiver. In addition, the received signal may be processed at a baseband receiver to determine Channel State Information (CSI). CSI may be used to determine the motion of an object in the sensing space. In addition to the CSI of the OTA channel, the CSI obtained by the processing of the received signal by the baseband receiver may also contain disturbances occurring in or caused by the front-end components in the baseband transmitter and the baseband receiver. Since the disturbances caused by the front-end components are not the result of the motion of the object occurring in the sensing space, for accurate Wi-Fi sensing, the CSI used to determine the motion should contain only the disturbances occurring in the OTA channel and not any disturbances occurring in or caused by the front-end components in the baseband transmitter and the baseband receiver.

Disclosure of Invention

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 comprises the following steps: receiving, by the sensing decision unit, measured channel state information (M-CSI) representing sensed 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.

In some embodiments, the method further comprises: receiving, by a receiving device comprising a Receiver Front End (RFE) with a receiving antenna, a sensing transmission from a plurality of sensing transmitters; and generating, by the receiving device, the M-CSI based on the sensing transmission.

In some embodiments, the receiving device further comprises the at least one processor.

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

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

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

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

In some embodiments, determining the sense decision input information includes setting the sense 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.

In some embodiments, the RFE-SI includes Automatic Gain Controller (AGC) information.

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.

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.

In some embodiments, determining the sensing decision input information includes: generating processed channel state information (P-CSI) by multiplying the 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.

In some embodiments, determining the sensing decision input information includes: the sensing decision input information is set 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.

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

In some embodiments, determining the sensing decision input information includes: calculating the group delay of the M-CSI according to the down converter 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.

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

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 sensed measurements; receiving, by the sensing decision unit, RFE-SI; and determining, by the sensing decision unit and in accordance with the RFE-SI, sensing decision input information.

Other aspects and advantages of the present disclosure will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, illustrating by way of example the principles of the disclosure.

Drawings

The foregoing and other objects, aspects, features, and advantages of the present disclosure will become more apparent and better understood by referring to the following description taken in conjunction with the accompanying drawings in which:

fig. 1 is a diagram illustrating an example wireless communication system;

fig. 2A and 2B are diagrams illustrating example wireless signals transmitted between wireless communication devices;

fig. 3A and 3B are diagrams showing examples of channel responses calculated from wireless signals transmitted between the wireless communication apparatuses in fig. 2A and 2B;

FIGS. 4A and 4B are diagrams illustrating example channel responses associated with movement of objects in different regions of space;

FIGS. 4C and 4D are plots illustrating example channel responses of FIGS. 4A and 4B superimposed on example channel responses associated with no motion occurring in space;

Fig. 5 depicts an implementation of some architectures of an implementation of a system for Wi-Fi sensing, according to some embodiments;

Fig. 6 depicts measured channels relative to Over The Air (OTA) channels, in accordance with some embodiments;

Fig. 7 depicts a representation of a receiver chain of a receiving device according to some embodiments;

FIG. 8 depicts a Receiver Front End (RFE) disturbance correction architecture, in accordance with some embodiments;

FIG. 9 depicts an example of receiver front end state information (RFE-SI) in an RFE disturbance correction architecture, in accordance with some embodiments;

fig. 10 depicts a structure of a Phase Locked Loop (PLL) unit according to some embodiments;

Fig. 11 depicts an example of group delay for an ideal channel in accordance with some embodiments;

FIG. 12 depicts a block diagram of a zero intermediate frequency (zero IF) down converter with two branches, in accordance with some embodiments;

13A and 13B depict characteristics of an example of a notch filter in accordance with some embodiments;

FIG. 14 depicts a block diagram of a two-stage low-IF down-converter with two branches, in accordance with some embodiments;

FIG. 15 depicts a flowchart for determining sensing decision input information, according to some embodiments;

Fig. 16 depicts a flowchart for transmitting measured channel state information to a sensing decision unit, in accordance with some embodiments;

FIG. 17 depicts a flowchart for determining sense decision input information from RFE-SI, wherein RFE-SI includes a phase change indicator, in accordance with some embodiments;

FIG. 18 depicts a flowchart for determining sensing decision input information from RFE-SI, wherein RFE-SI contains downconverter type information, in accordance with some embodiments; and

Fig. 19A and 19B depict a flow chart for determining sensing decision input information from RFE-SI, which contains Automatic Gain Controller (AGC) information, in accordance with some embodiments.

Detailed Description

In some aspects of what is described herein, a wireless sensing system may be used in a variety of wireless sensing applications by processing wireless signals (e.g., radio frequency signals) transmitted through a space between wireless communication devices. An example wireless sensing application includes motion detection, which may include the following: motion of objects in detection space, motion tracking, breath detection, breath monitoring, presence detection, gesture recognition, human detection (moving and stationary human detection), human tracking, fall detection, velocity estimation, intrusion detection, walking detection, step count, breath rate detection, apnea estimation, gesture change detection, activity recognition, gait rate classification, gesture decoding, sign language recognition, hand tracking, heart rate estimation, breath rate estimation, room occupancy detection, human dynamic monitoring, and other types of motion detection applications. Other examples of wireless sensing applications include object recognition, voice recognition, keystroke detection and recognition, tamper detection, touch detection, attack detection, user authentication, driver fatigue detection, flow monitoring, smoking detection, campus violence detection, body counting, metal detection, body recognition, bicycle positioning, body alignment estimation, wi-Fi imaging, and other types of wireless sensing applications. For example, the wireless sensing system may operate as a motion detection system to detect the presence and location of motion based on Wi-Fi signals or other types of wireless signals. As described in more detail below, the wireless sensing system may be configured to control measurement rates, wireless connections, and device participation, for example, to improve system operation or achieve other technical advantages. In instances where the wireless sensing system is used in another type of wireless sensing application, the system improvements and technical advantages achieved when the wireless sensing system is used for motion detection are also achieved.

In some example wireless sensing systems, the wireless signal contains components that the wireless device may use to estimate channel responses or other channel information (e.g., a synchronization preamble in a Wi-Fi PHY frame, or another type of component), and the wireless sensing system may detect motion by analyzing changes in the channel information collected over time (or another characteristic that depends on the wireless sensing application). In some examples, the wireless sensing system may operate similar to a bistatic radar system, where a Wi-Fi Access Point (AP) assumes a receiver role and each Wi-Fi device (site or node or peer) connected to the AP assumes a transmitter role. The wireless sensing system may trigger the connected device to generate a transmission and generate a channel response measurement at the receiver device. This triggering process may be repeated periodically to obtain a series of time-varying measurements. The wireless sensing algorithm may then receive as input a time series of generated channel response measurements (e.g., calculated by a Wi-Fi receiver), and through a correlation or filtering process, may then make a determination (e.g., determine whether there is motion within the environment represented by the channel response, e.g., based on changes or patterns in the channel estimate). In instances where the wireless sensing system detects motion, the location of the motion within the environment may also be identified based on the motion detection results in the plurality of wireless devices.

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

Channel information for each of the communication links may be analyzed (e.g., by a hub device or other device in the wireless communication network, or a sensing transmitter communicatively coupled to the network), for example, to detect whether motion has occurred in space, to determine the relative location of the detected motion, or both. In some aspects, channel information for each of the communication links may be analyzed to detect whether an object is present, for example, when motion is not detected in space.

In some cases, the wireless sensing system may control the node measurement rate. For example, wi-Fi motion systems may configure variable measurement rates (e.g., channel estimation/environmental measurement/sampling rates) based on criteria given by current wireless sensing applications (e.g., motion detection). In some embodiments, for example, when no motion is present or detected for a period of time, the wireless sensing system may reduce the rate of measuring the environment such that the frequency at which the connected device is triggered is reduced. In some embodiments, for example, when motion is present, the wireless sensing system may increase the trigger rate to produce a time series of measurements with finer temporal resolution. Controlling the variable measurement rate may enable power savings (triggered by the device), reduced processing (reducing the data to be correlated or filtered), and increased resolution during specified times.

In some cases, the wireless sensing system may perform band steering or client steering for nodes in the overall wireless network, e.g., in Wi-Fi multi-AP or Extended Service Set (ESS) topologies, multiple coordinator wireless APs each provide a Basic Service Set (BSS) that may occupy different frequency bands and allow devices to transparently move between one participating AP to another (e.g., mesh). For example, in a home mesh network, a Wi-Fi device may connect to any of the APs, but typically selects an AP with good signal strength. The coverage footprints of mesh APs typically overlap, typically placing each device within communication range or within more than one AP. If the AP supports multiple bands (e.g., 2.4GHz and 5 GHz), the wireless sensing system may 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 outcome of the wireless sensing algorithm (e.g., motion detection algorithm). In some embodiments, the wireless sensing system may change the device from being connected to one mesh AP to being connected to another mesh AP. Such device guidance may be performed, for example, during wireless sensing (e.g., motion detection) based on criteria detected in a particular area to improve detection coverage or better locate motion within the area.

In some cases, beamforming may be performed between wireless communication devices based on some knowledge of the communication channel (e.g., by feedback properties generated by the receiver), which may be used to generate one or more steering properties (e.g., steering matrices) that are applied by the transmitter device to shape the transmitted beams/signals in one or more particular directions. Thus, a change in the steering or feedback properties used in the beamforming process is indicative of a change in space accessed by the wireless communication system that may be caused by the moving object. For example, the motion may be detected by a substantial change in the communication channel over a period of time, e.g., as indicated by a channel response, or a pilot or feedback property, or any combination thereof.

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

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

In some cases, the wireless sensing system may allow the device to dynamically indicate its wireless sensing capabilities or wireless sensing willingness and communicate it to the wireless sensing system. For example, sometimes a device may not wish to be periodically interrupted or triggered to transmit a wireless signal that will allow an AP to produce channel measurements. For example, if the device is in a sleep state, frequent waking up of the device to transmit or receive wireless sensing signals may consume resources (e.g., cause the cell phone battery to discharge faster). These and other events may make the device willing or unwilling to engage in wireless sensing system operation. In some cases, a cell phone running using a battery may not want to participate, but when the cell phone is plugged into a charger, the cell phone may be willing to participate. Thus, if the cellular telephone is unplugged, the wireless sensing system may be instructed to exclude the cellular telephone from participation; and if the cellular telephone is plugged in, it may be indicated to the wireless sensing system to include the cellular telephone in wireless sensing system operation. In some cases, a device may not want to participate if the device is under load (e.g., the device is streaming audio or video) or busy performing a primary function; and when the load of the same device decreases and participation does not interfere with the primary function, the device may indicate to the wireless sensing system that it is willing to participate.

Example wireless sensing systems are described below in the context of motion detection (detecting motion of an object in space, motion tracking, respiration detection, respiration monitoring, presence 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, gesture change detection, activity recognition, gait rate classification, gesture decoding, sign language recognition, hand tracking, heart rate estimation, respiration rate estimation, room occupancy detection, human dynamic 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 are also applicable in instances where the wireless sensing system is used in another type of wireless sensing application.

In various embodiments of the present disclosure, the following provides non-limiting definitions of one or more terms to be used in a document.

The term "transmission parameters" may refer to a set of IEEE 802.11PHY transmitter configuration parameters that are defined as part of a transmission vector (TXVECTOR) corresponding to a particular PHY and may be configured for each PHY layer protocol data unit (PPDU) transmission.

The term "Null Data PPDU (NDP)" may refer to a PPDU that does not contain a data field. In an example, a null data PPDU may be used for the sensing transmission, where it is a MAC header containing the required information.

The term "Channel State Information (CSI)" may refer to properties of a communication channel that are known or measured by channel estimation techniques. CSI may represent how a wireless signal propagates from a sensing transmitter to a sensing receiver along multiple paths. CSI is typically a matrix of complex values representing the amplitude attenuation and phase shift of a signal, which provides an estimate of the communication channel.

The term "sensing transmitter" may refer to a device that transmits a transmission (e.g., PPDU) for sensing measurement results (e.g., channel state information) in a sensing session. In one example, a station is an example of a sensing transmitter. In some examples, in instances where the station is acting as a sensing receiver, the access point may also be a sensing transmitter for Wi-Fi sensing purposes.

The term "sensing receiver" may refer to a device that receives a transmission (e.g., PPDU) sent by a sensing transmitter in a sensing session and performs one or more sensing measurements (e.g., channel state information). An access point is an example of a sensing receiver. In some examples, the station may also be a sensing receiver, such as in a mesh network scenario.

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

The term "sensing initiator" may refer to a device that initiates a Wi-Fi sensing session. The role of the sensing initiator may be taken on by the sensing receiver, the sensing transmitter or a separate device containing the sensing algorithm.

The term "Wireless Local Area Network (WLAN) sensing session" may refer to a period of time in physical space during which an object may be detected, and/or characterized. In an example, during a WLAN sensing session, several devices participate and thereby facilitate the generation of sensing measurements.

The term "sensing trigger message" may 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 transmission may be carried by a UL-OFDMA sensing trigger or a UL-OFDMA composite sensing trigger. The sensing trigger message may also be referred to as a sensing initiation message.

The term "sensing response message" may refer to a message contained within a sensing transmission from a sensing transmitter to a sensing receiver. The sensing receiver performs a sensing measurement using a sensing transmission including a sensing response message.

The term "sensing transmission" may refer to a transmission from a sensing transmitter to a sensing receiver that may be used to make a sensing measurement. In an example, the sensing transmission may also be referred to as a wireless sensing signal or a wireless signal.

The term "sensing measurement" may refer to a measurement of the 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 one example, the sensing measurement may also be referred to as a channel response measurement.

The term "sensing target" may refer to a target that senses activity at a time. The sensing target is not static and may change over time. In an example, sensing a target may require sensing measurements of a particular type, a particular format, or a particular precision, resolution, or accuracy available to the sensing algorithm.

The term "sensing algorithm" may refer to a computing algorithm that implements a sensing target. The sensing algorithm may be executed on any device in the Wi-Fi sensing system.

The term "requested transmission configuration" may refer to requested transmission parameters of a sensing transmitter to be used when sending a sensing transmission.

The term Automatic Gain Controller (AGC) may refer to a form of signal amplifier whose gain is automatically adjusted in response to received signal strength.

The term "measured channel state information (M-CSI)" may refer to how a wireless signal propagates from a transmitter to a receiver along multiple paths. M-CSI is typically a complex-valued matrix representing the amplitude attenuation and phase shift of a signal, which provides an estimate of the communication channel. The M-CSI may be provided by a baseband receiver (or baseband processor).

The term "processed channel state information (P-CSI)" may refer to a corrected form of M-CSI that has been adjusted according to AGC information, phase change indicator, and down-converter type information.

The term "group delay" may refer to the characteristics of a physical channel or an electronic component (e.g., a filter) that represents the amount of phase shift of a signal caused by the physical channel and the electronic component as a function of frequency.

The term "notch filter" may refer to a type of band reject filter that attenuates frequencies within a particular range while passing all other frequencies without attenuation or with minimal attenuation.

The term "low intermediate frequency (low IF) down-converter" may refer to a down-converter using a two-stage mixer. The first stage converts the radio frequency signal to a low Intermediate Frequency (IF) signal and the second stage converts the IF signal to a baseband signal.

The term "Phase Locked Loop (PLL)" may 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.

The term "Over The Air (OTA) channel" may refer to a wireless channel located between a transmitter antenna and a receiver antenna.

The term "zero-IF down-converter" may refer to a down-converter that directly converts a received radio frequency signal to a baseband signal using a single stage mixer.

The following description of the various portions of the specification and their respective content may be helpful for reading the following description of the various embodiments:

Section a describes a wireless communication system, wireless transmission, and sensing measurements that may be used to practice the embodiments described herein.

Section B describes systems and methods useful for Wi-Fi sensing systems configured to send sensing transmissions and make sensing measurements.

Section C describes embodiments of systems and methods for isolating an electronic environment to improve channel estimation.

A. wireless communication system, wireless transmission and sensing measurement results

Fig. 1 illustrates a wireless communication system 100. The wireless communication system 100 includes three wireless communication devices: a first wireless communication device 102A, a second wireless communication device 102B, and a third wireless communication device 102C. The wireless communication system 100 may include additional wireless communication devices and other components (e.g., additional wireless communication devices, one or more network servers, network routers, network switches, cables or other communication links, etc.).

The wireless communication devices 102A, 102B, 102C may operate in a wireless network, for example, according to a wireless network standard or another type of wireless communication protocol. For example, the wireless network may 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 (e.g., wi-Fi networks) configured to operate in accordance with one or more standards in the 802.11 family of standards developed by IEEE, and the like. Examples of PANs include those according to short-range communication standards (e.g.,Near Field Communication (NFC), zigBee), millimeter wave communication, and the like.

In some embodiments, the wireless communication devices 102A, 102B, 102C may be configured to communicate in a cellular network, for example, according to a cellular network standard. Examples of cellular networks include those 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 standard, etc.

In the example shown in fig. 1, the wireless communication devices 102A, 102B, 102C may be or include standard wireless network components. For example, the wireless communication devices 102A, 102B, 102C may 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 embedded as instructions (e.g., software or firmware) on a modem of the WAP. In some cases, the wireless communication devices 102A, 102B, 102C may be nodes of a wireless mesh network, such as a commercially available mesh network system (e.g., plasmid Wi-Fi, google Wi-Fi, qualcomm Wi-Fi SoN, etc.). In some cases, another type of standard or conventional Wi-Fi transmitter device may be used. In some cases, one or more of the wireless communication devices 102A, 102B, 102C may be implemented as WAPs in the mesh network, while other wireless communication devices 102A, 102B, 102C are implemented as leaf devices (e.g., mobile devices, smart devices, etc.) that access the mesh network through one of the WAPs. In some cases, one or more of the wireless communication devices 102A, 102B, 102C are mobile devices (e.g., smartphones, smartwatches, tablet computers, laptops, 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.

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

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

Modem 112 may transmit (receive, transmit, or both) wireless signals. For example, modem 112 may be configured to transmit Radio Frequency (RF) signals formatted according to a wireless communication standard (e.g., wi-Fi or bluetooth). The modem 112 may be implemented as the example wireless network modem 112 shown in fig. 1, or may be implemented in another manner, such as with other types of components or subsystems. In some implementations, the modem 112 includes a radio subsystem and a baseband subsystem. In some cases, the baseband subsystem and the radio subsystem may be implemented on a common chip or chipset, or the baseband subsystem and the radio subsystem may be implemented in a card or another type of assembled device. The baseband subsystem may be coupled to the radio subsystem, for example, by leads, pins, wires, or other types of connections.

In some cases, the radio subsystem in modem 112 may include one or more antennas and radio frequency circuitry. The RF circuitry may 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 radio frequency signals to baseband signals, and the like. Such circuitry may include, for example, filters, amplifiers, mixers, local oscillators, and the like. The radio subsystem may be configured to transmit radio frequency wireless signals over a wireless communication channel. For example, a radio subsystem may include a radio chip, an RF front end, and one or more antennas. The radio subsystem may contain additional or different components. In some implementations, the radio subsystem may be or include radio electronics (e.g., RF front-end, radio chip, or similar components) from a conventional modem (e.g., from a Wi-Fi modem, pico base station modem, etc.). In some implementations, the antenna includes a plurality of antennas.

In some cases, the baseband subsystem in modem 112 may include digital electronics configured to process digital baseband data, for example. For example, the baseband subsystem may include a baseband chip. The baseband subsystem may contain additional or different components. In some cases, the baseband subsystem may include a Digital Signal Processor (DSP) device or another type of processor device. In some cases, the baseband system includes digital processing logic to operate the radio subsystem, communicate radio network traffic through the radio subsystem, detect motion based on motion detection signals received through the radio subsystem, or perform other types of processes. For example, a baseband subsystem may contain one or more chips, chipsets, or other types of devices configured to encode signals and deliver the encoded signals to a 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).

In some cases, the radio subsystem in modem 112 receives the baseband signal from the baseband subsystem, up-converts the baseband signal to a Radio Frequency (RF) signal, and wirelessly transmits the RF signal (e.g., through an antenna). In some cases, the radio subsystem in modem 112 receives the radio frequency signal wirelessly (e.g., via an antenna), down-converts the radio frequency signal to a baseband signal, and sends the baseband signal to the baseband subsystem. The signals exchanged between the radio subsystem and the baseband subsystem may be digital signals or analog signals. In some examples, the baseband subsystem includes conversion circuitry (e.g., digital-to-analog converter, analog-to-digital converter) and exchanges analog signals with the radio subsystem. In some examples, the radio subsystem includes conversion circuitry (e.g., digital-to-analog converter, analog-to-digital converter) and exchanges digital signals with the baseband subsystem.

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

The processor 114 may execute instructions, for example, to generate output data based on data input. The instructions may comprise programs, code, scripts, or other types of data stored in a memory. Additionally or alternatively, the instructions may be encoded as preprogrammed or re-programmable logic circuits, logic gates, or other types of hardware or firmware components. Processor 114 may be or include a general purpose microprocessor such as a special purpose coprocessor or another type of data processing device. In some cases, the processor 114 performs advanced operations of the wireless communication device 102C. For example, the processor 114 may be configured to execute or interpret software, scripts, programs, functions, executable files, or other instructions stored in the memory 116. In some embodiments, the processor 114 may be included in the modem 112.

The memory 116 may include computer readable storage media such as volatile memory devices, non-volatile memory devices, or both. Memory 116 may comprise one or more read-only memory devices, random access memory devices, buffer memory devices, or a combination of these and other types of memory devices. In some cases, one or more components of the memory may be integrated with or otherwise associated with another component of the wireless communication device 102C. The memory 116 may store instructions executable by the processor 114. For example, the instructions may include instructions for time aligning signals using the interference buffer and the motion detection buffer, such as by one or more of the operations of the example processes as described in any of fig. 15, 16, 17, 18, 19A, and 19B.

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

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

In the example shown, the wireless communication device 102C processes wireless signals from the wireless communication devices 102A, 102B to detect movement of an object in a space accessed by the wireless signals, to determine a location of the detected movement, or both. For example, the wireless communication device 102C may perform one or more operations of the example processes described below with respect to any of fig. 15, 16, 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 signal may be an indoor or outdoor space, which may contain, for example, one or more fully or partially enclosed areas, open areas without an enclosure, etc. The space may be or may contain an interior of a room, a plurality of rooms, a building, etc. In some cases, the wireless communication system 100 may be modified, for example, such that the wireless communication device 102C may transmit wireless signals, and the wireless communication devices 102A, 102B may process the wireless signals from the wireless communication device 102C to detect motion or determine the location of the detected motion.

The wireless signals for motion detection may 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 (e.g., random signal, reference signal, etc.) generated for motion detection or other purposes. In an example, motion detection may be performed by analyzing one or more training fields carried by a wireless signal or by analyzing other data carried by a signal. In some instances, the data will be added for the explicit purpose of motion detection, or the data used will nominally be used for another purpose and reused or reused for motion detection purposes. In some instances, the wireless signal propagates through an object (e.g., a wall) before or after interacting with the moving object, which may allow detection of movement of the moving object without an optical line of sight between the moving object and the transmitting or receiving hardware. Based on the received signals, the wireless communication device 102C may generate motion detection data. In some cases, the wireless communication device 102C may transmit the motion detection data to another device or system, such as a security system, which may include a control center for monitoring movement within a space, such as a room, building, outdoor area, or the like.

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

In the example shown in fig. 1, the wireless communication system 100 is a wireless mesh network with a wireless communication link between each of the wireless communication devices 102. In the example shown, the wireless communication link between wireless communication device 102C and wireless communication device 102A may be used to detect motion detection field 110A, the wireless communication link between wireless communication device 102C and wireless communication device 102B may be used to detect motion detection field 110B, and the wireless communication link between wireless communication device 102A and wireless communication device 102B may be used to detect motion detection field 110C. In some cases, each wireless communication device 102 detects motion in the motion detection field 110 accessed by the device by processing received signals based on wireless signals transmitted by the wireless communication device 102 through the motion detection field 110. For example, as the person 106 shown in fig. 1 moves in the motion detection fields 110A and 110C, the wireless communication device 102 may detect motion based on signals it receives that are based on wireless signals transmitted through the respective motion detection fields 110. For example, the wireless communication device 102A may detect movement of the person 106 in the movement detection fields 110A, 110C, the wireless communication device 102B may detect movement of the person 106 in the movement detection field 110C, and the wireless communication device 102C may detect movement of the person 106 in the movement detection field 110A.

In some cases, the motion detection field 110 may comprise, for example, air, a solid material, a liquid, or another medium through which wireless electromagnetic signals may propagate. In the example shown in fig. 1, the motion detection field 110A provides a wireless communication channel between the wireless communication device 102A and the wireless communication device 102C, the motion detection field 110B provides a wireless communication channel between the wireless communication device 102B and the wireless communication device 102C, and the motion detection field 110C provides a wireless communication channel between the wireless communication device 102A and the wireless communication device 102B. In some aspects of operation, wireless signals transmitted over a wireless communication channel (separate from or shared with wireless communication channels for network traffic) are used to detect movement of objects in space. The object may be any type of static or movable object and may be living or inanimate. For example, the object may be a person (e.g., person 106 shown in fig. 1), an animal, an inorganic object or another device, apparatus or combination, an object defining all or part of a boundary of a space (e.g., a wall, a door, a window, etc.), or another type of object. In some embodiments, motion information from the wireless communication device may be analyzed to determine the location of the detected motion. For example, as described further below, one of the wireless communication devices 102 (or another device that is communicatively coupled to the wireless communication device 102) may determine that the detected motion is located in the vicinity of the particular wireless communication device.

Fig. 2A and 2B are diagrams illustrating example wireless signals transmitted between wireless communication devices 204A, 204B, 204C. The wireless communication devices 204A, 204B, 204C may be, for example, the wireless communication devices 102A, 102B, 102C shown in fig. 1 or other types of wireless communication devices. The wireless communication devices 204A, 204B, 204C transmit wireless signals through the space 200. The space 200 may be fully or partially enclosed or open at one or more boundaries. The space 200 may be or may contain a room interior, multiple rooms, a building, an indoor area, an outdoor area, or the like. In the example shown, the first wall 202A, the second wall 202B, and the third wall 202C at least partially enclose the space 200.

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

As shown, the object is located at a first location 214A in fig. 2A, and the object has moved to a second location 214B in fig. 2B. In fig. 2A and 2B, the moving object in the space 200 is represented as a person, but the moving object may be another type of object. For example, the moving object may be an animal, an inorganic object (e.g., a system, apparatus, device, or assembly), an object defining all or part of the boundary of the space 200 (e.g., a wall, door, window, etc.), or another type of object.

As shown in fig. 2A and 2B, a plurality of example paths of wireless signals transmitted from wireless communication device 204A are shown by dashed lines. Along a first signal path 216, wireless signals are transmitted from the wireless communication device 204A and reflected from the first wall 202A toward the wireless communication device 204B. Along the second signal path 218, wireless signals are transmitted from the wireless communication device 204A and reflected from the second wall 202B and the first wall 202A toward the wireless communication device 204C. Along the third signal path 220, wireless signals are transmitted from the wireless communication device 204A and reflected from the second wall 202B toward the wireless communication device 204C. Along the fourth signal path 222, the wireless signal is transmitted from the wireless communication device 204A and reflected from the third wall 202C toward the wireless communication device 204B.

In fig. 2A, along a fifth signal path 224A, wireless signals are transmitted from the wireless communication device 204A and reflected from the object at the first location 214A toward the wireless communication device 204C. Between fig. 2A and 2B, the surface of the object moves in space 200 from first location 214A to second location 214B (e.g., a distance from first location 214A). In fig. 2B, wireless signals are transmitted from wireless communication device 204A and reflected from the object at second location 214B toward wireless communication device 204C along sixth signal path 224B. As the object moves from first location 214A to second location 214B, sixth signal path 224B depicted in FIG. 2B is longer than fifth signal path 224A depicted in FIG. 2A. In some instances, signal paths may be added, removed, or otherwise modified due to movement of objects in space.

The example wireless signals shown in fig. 2A and 2B may experience attenuation, frequency shift, phase shift, or other effects through their respective paths, and may have portions that propagate in another direction, for example, through the first wall 202A, the second wall 202B, and the third wall 202C. In some examples, the wireless signal is a Radio Frequency (RF) signal. The wireless signals may include other types of signals.

In the example shown in fig. 2A and 2B, the wireless communication device 204A may repeatedly transmit wireless signals. Specifically, fig. 2A shows a wireless signal transmitted from the wireless communication device 204A at a first time, and fig. 2B shows the same wireless signal transmitted from the wireless communication device 204A at a second later time. The transmitted signals may be transmitted continuously, periodically, at random or intermittent times, or the like, or a combination thereof. The transmitted signal may have a plurality of frequency components in a frequency bandwidth. The transmitted signal may be transmitted from the wireless communication device 204A in an omni-directional manner, a directional manner, or other manner. In the example shown, the wireless signal passes through multiple respective paths in space 200, and the signal along each path may be attenuated by path loss, scattering, reflection, etc., and may have a phase or frequency offset.

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

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

Where ω _n represents the frequency of the nth frequency component of the transmitted signal, c _n represents the complex coefficient of the nth frequency component, and t represents time. In the case of transmitting the transmitted signal f (t) from the first wireless communication apparatus 204A, the output signal r _k (t) from the path k can be described according to equation (2):

Where α _n,k represents the attenuation factor (or channel response; e.g., due to scattering, reflection, and path loss) of the nth frequency component along path k, and φ _n,k represents the phase of the signal of the nth frequency component along path k. The received signal R at the wireless communication device may then be described as the sum of all output signals R _k (t) from all paths to the wireless communication device, which is shown in equation (3):

R＝∑_kr_k(t)....(3)

substituting equation (2) into equation (3) yields the following equation (4):

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

The complex value H _n of a given frequency component ω _n represents the relative amplitude and phase offset of the received signal at that frequency component ω _n. As the object moves in space, the complex value H _n changes due to the change in the channel response a _n,k of the space. Thus, a detected change in the channel response may be indicative of movement of an object within the communication channel. In some cases, noise, interference, or other phenomena may affect the channel response detected by the receiver, and the motion detection system may reduce or isolate such effects to improve the accuracy and quality of the motion detection capability. In some embodiments, the overall channel response may be expressed as the following equation (6):

In some cases, the spatial channel response h _ch may be determined, for example, based on estimated mathematical theory. For example, the reference signal R _ef may be modified with a candidate channel response (h _ch), and then the best matching candidate channel to the received signal (R _cvd) may be selected using the maximum likelihood method. In some cases, the estimated received signal is obtained from a convolution of the reference signal (R _ef) with the candidate channel response (h _ch) And then changing the channel coefficient of the channel response (h _ch) to cause the square error of the estimated received signalMinimizing. This can be mathematically described as the following equation (7):

usage optimization criteria

The minimization or optimization process may utilize adaptive filtering techniques such as Least Mean Squares (LMS), recursive Least Squares (RLS), batch Least Squares (BLS), and the like. The channel response may be a Finite Impulse Response (FIR) filter, an Infinite Impulse Response (IIR) filter, or the like. As shown in the above equation, the received signal may be considered as a convolution of the reference signal and the channel response. Convolution operation means that the channel coefficients have a degree of correlation with each of the delayed copies of the reference signal. Thus, the convolution operation as shown in the above equation shows that the received signal occurs at different delay points, each weighted by the channel coefficients.

Fig. 3A and 3B are plots showing examples of channel responses 360, 370 calculated from wireless signals transmitted between the wireless communication devices 204A, 204B, 204C in fig. 2A and 2B. Fig. 3A and 3B also illustrate a frequency domain representation 350 of the initial wireless signal transmitted by the wireless communication device 204A. In the example shown, the channel response 360 in fig. 3A represents the signal received by the wireless communication device 204B when there is no motion in the space 200, and the channel response 370 in fig. 3B represents the signal received by the wireless communication device 204B in fig. 2B after the object moves in the space 200.

In the example shown in fig. 3A and 3B, for purposes of illustration, the wireless communication device 204A transmits a signal having a flat frequency distribution (each frequency component f ₁、f₂ and f ₃ being the same in amplitude) as shown by 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 distribution, the received signal represents the channel response of the space 200. As shown in fig. 3A and 3B, the channel responses 360, 370 are different from the frequency domain representation 350 of the transmitted signal. When motion occurs in space 200, the channel response will also change. For example, as shown in fig. 3B, the channel response 370 associated with the motion of an object in space 200 is different from the channel response 360 associated with no motion in space 200.

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

Fig. 4A and 4B are diagrams illustrating example channel responses 401, 403 associated with movement of an object 406 in unique regions 408, 412 of space 400. In the example shown, the space 400 is a building, and the space 400 is divided into a plurality of distinct areas: a first region 408, a second region 410, a third region 412, a fourth region 414, and a fifth region 416. In some cases, space 400 may contain additional or fewer regions. As shown in fig. 4A and 4B, the area within the space 400 may be defined by walls between rooms. In addition, the area may be defined by ceilings between building floors. For example, space 400 may contain additional floors with additional rooms. In addition, in some cases, the plurality of areas of space may be or include a plurality of floors in a multi-story building, a plurality of rooms in a building, or a plurality of rooms on a particular floor of a building. In the example shown in fig. 4A, while the object positioned in the first region 408 is represented as a person 406, the moving object may be another type of object, such as an animal or an inorganic object.

In the example shown, wireless communication device 402A is positioned in a fourth region 414 of space 400, wireless communication device 402B is positioned in a second region 410 of space 400, and wireless communication device 402C is positioned in a fifth region 416 of space 400. The wireless communication device 402 may operate in the same or similar manner as the wireless communication device 102 of fig. 1. For example, the wireless communication device 402 may be configured to transmit and receive wireless signals and detect whether motion has occurred in the space 400 based on the received signals. For example, the wireless communication device 402 may periodically or repeatedly transmit motion detection signals through the space 400 and receive signals based on the motion detection signals. The wireless communication device 402 may analyze the received signal to detect whether an object is moving in the space 400, for example, by analyzing a channel response associated with the space 400 based on the received signal. Additionally, in some embodiments, the wireless communication device 402 may analyze the received signals to identify the location of the detected motion within the space 400. For example, the wireless communication device 402 may analyze characteristics of the channel response to determine whether the channel response shares the same or similar characteristics as are known to be associated with the first through fifth regions 408, 410, 412, 414, 416 of the space 400.

In the example shown, one (or more) of the wireless communication devices 402 repeatedly transmit a motion detection signal (e.g., a reference signal) through the space 400. In some cases, the motion detection signal may have a flat frequency distribution, with the amplitude of each frequency component f ₁、f₂ and f ₃. For example, the motion detection signal may have a frequency response similar to the frequency domain representation 350 shown in fig. 3A and 3B. In some cases, the motion detection signals may have different frequency distributions. Due to the interaction of the reference signal with the space 400 (and objects therein), a signal received at the other wireless communication device 402 that is based on the motion detection signal transmitted from the other wireless communication device 402 is different from the transmitted reference signal.

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

Fig. 4C and 4D are plots showing the channel responses 401, 403 of fig. 4A and 4B superimposed on the channel response 460 associated with no motion occurring in the space 400. Fig. 4C and 4D also illustrate a frequency domain representation 450 of an initial wireless signal transmitted by one or more of the wireless communication devices 402A, 402B, 402C. When motion occurs in space 400, a change in channel response will occur with respect to channel response 460 associated with no motion, and thus, motion of an object in space 400 may be detected by analyzing the change in channel response. In addition, the relative position of the detected motion within the space 400 may be identified. For example, the shape of the channel response associated with the motion may 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.

When there is no motion in the space 400 (e.g., when the object 406 is not present), the wireless communication device 402 may calculate a channel response 460 associated with the no motion. The channel response may vary slightly due to a number of factors; however, multiple channel responses 460 associated with different time periods may share one or more characteristics. In the example shown, the channel response 460 associated with no motion has a decreasing frequency distribution (each frequency component f ₁、f₂ and f ₃ has a smaller amplitude than the previous one). In some cases (e.g., based on different room layouts or placement of wireless communication devices 402), the distribution of channel responses 460 may be different.

When motion occurs in space 400, the channel response will change. For example, in the example shown in fig. 4C and 4D, the channel response 401 associated with the motion of the object 406 in the first region 408 is different than 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 than the channel response 460 associated with no motion. The channel response 401 has a concave parabolic frequency distribution (the magnitude of the intermediate frequency component f ₂ is smaller than the external frequency components f ₁ and f ₃), while the channel response 403 has a convex asymptotic frequency distribution (the magnitude of the intermediate frequency component f ₂ is larger than the external frequency components f ₁ and f ₃). In some cases (e.g., based on different room layouts or placement of the wireless communication device 402), the distribution of the channel responses 401, 403 may be different.

Analyzing the channel response may be considered similar to analyzing a digital filter. The channel response may be formed by reflections of objects in space and reflections produced by moving or stationary persons. When a reflector (e.g., a person) moves, it changes the channel response. This may translate to a change in the equivalent tap of the digital filter, which may be considered to have poles and zeros (poles amplify the frequency components of the channel response and appear as peaks or high points in the response, while zeros attenuate the frequency components of the channel response and appear as dips, low points or zero values in the response). The varying digital filter may be characterized by the locations of its peaks and valleys, and the channel response may be similarly characterized by its peaks and valleys. For example, in some embodiments, the zero values and peaks in the frequency components of the channel response are analyzed (e.g., by marking their locations on the frequency axis and their magnitudes), and motion may be detected.

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

In some embodiments, an Artificial Intelligence (AI) model may be used to process data. AI models may be of various types, such as linear regression models, logistic regression models, linear discriminant analysis models, decision tree models, naive bayes models, K-nearest neighbor models, learning vector quantization models, support vector machines, bagging and random forest models, and deep neural networks. In general, all AI models are intended to learn a function that provides the most accurate correlation between input and output values, and are trained using historical input and output sets of known correlations. In an example, artificial intelligence may also be referred to as machine learning.

In some embodiments, the distribution of channel responses associated with motion in unique regions of the space 400 may be learned. For example, machine learning may be used to classify channel response characteristics, where object motion is located within a unique region of space. In some cases, a user associated with the wireless communication device 402 (e.g., an owner or other occupant of the space 400) may assist in the learning process. For example, referring to the example shown in fig. 4A and 4B, a user may move in each of the first through fifth regions 408, 410, 412, 414, 416 during a learning phase, and may indicate (e.g., through a user interface on the 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 may indicate on the mobile computing device that he/she is located in the first region 408 (and the region may be named "bedroom", "living room", "kitchen", or another type of room of the building, as the case may be). As the user moves through the area, a channel response may be obtained and may be "tagged" with the location (area) indicated by the user. The user may repeat the same process for other areas of the space 400. The term "marking" as used herein may refer to marking and identifying the channel response with a user-indicated location or any other information.

The marked channel response may then be processed (e.g., by machine learning software) to identify unique characteristics of the channel response associated with the motion in the unique region. Once identified, the identified unique characteristics may be used to determine the location of the detected motion for the newly calculated channel response. For example, the AI model may be trained using the labeled channel responses, and once trained, the newly calculated channel responses may be input to the AI model, and the AI model may output the location of the detected motion. For example, in some cases, the average, range, and absolute values are input to the AI model. In some cases, the amplitude and phase of the complex channel response itself may also be input. These values allow the AI model to design arbitrary front-end filters to pick the features most relevant to making accurate predictions of motion in unique regions of space. In some embodiments, the AI model is trained by performing a random gradient descent. For example, the channel response changes that are most active during a certain region may be monitored during training, and certain channel changes may be weighted to a large extent (by training and adjusting weights in the first layer to correlate to those shapes, trends, etc.). The weighted channel variation can be used to create a metric that is activated when a user is present in a certain area.

For extracted features, such as channel response zeros and peaks, a time series (of zeros/peaks) may be created using aggregation within a moving window, taking snapshots of past and present few features, and using the aggregate values as inputs to the network. Thus, the network will attempt to aggregate values in a certain region to cluster them while adjusting its weight, which can be done by creating a decision surface based on a logical classifier. The decision surface partitions the different clusters and subsequent layers may form categories based on individual clusters or combinations of clusters.

In some embodiments, the AI model contains two or more layers of inference. The first layer acts as a logical classifier that can divide values of different concentrations into individual clusters, while the second layer combines some of these clusters together to create categories for unique regions. In addition, subsequent layers may help extend the unique region over clusters of more than two categories. For example, a fully connected AI model may contain input layers corresponding to the number of tracked features, intermediate layers corresponding to the number of valid clusters (by iterating between selections), and final layers corresponding to different regions. In the case where complete channel response information is input to the AI model, the first layer may act as a shape filter that may correlate certain shapes. Thus, a first layer may lock onto a certain shape, a second layer may generate measures of changes that occur in those shapes, and a third and subsequent layers may create a combination of those changes and map the changes to different regions within space. The outputs of the different layers may then be combined by a fusion layer.

Example method and apparatus for wi-Fi sensing system

Fig. 5 depicts an implementation of some architectures of an implementation of a system 500 for Wi-Fi sensing, according to some embodiments.

The system 500 (alternatively referred to as Wi-Fi sensing system 500) may 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 among system components for information exchange. The system 500 may be an instance or example of the wireless communication system 100 and the network 560 may be an instance or example of a wireless network or cellular network, details of which are provided with reference to fig. 1 and accompanying description.

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

According to one embodiment, the receiving device 502 may be implemented by a device such as the wireless communication device 102 shown in fig. 1. In some embodiments, the receiving device 502 may be implemented by a device such as the wireless communication device 204 shown in fig. 2A and 2B. The reception device 502 may be implemented by the wireless communication device 402 shown in fig. 4A and 4B. In one embodiment, the receiving device 502 may coordinate and control communications between multiple sensing transmitters 506- (1-M). According to an embodiment, the receiving device 502 may be enabled to control 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 may process the sensed measurements to obtain sensed results of the system 500. In some embodiments, the receiving device 502 may be configured to transmit the sensing measurements to the sensing decision unit 504, and the sensing decision unit 504 may be configured to process the sensing measurements to obtain the sensing results of the system 500. In an example, the sensed measurements processed at the sensing decision unit 504 may be referred to as measured CSI (M-CSI).

Referring again to fig. 5, in some embodiments, each of the plurality of sensing transmitters 506- (1-M) may form part of a Basic Service Set (BSS) and may be configured to send a sensing transmission to the receiving device 502 based on which one or more sensing measurements (e.g., CSI) may be performed for Wi-Fi sensing. In an embodiment, each of the plurality of sensing transmitters 506- (1-M) may be a station. According to an embodiment, each of the plurality of sensing transmitters 506- (1-M) may be implemented by a device such as the wireless communication device 102 shown in FIG. 1. In some embodiments, each of the plurality of sensing transmitters 506- (1-M) may be implemented by a device such as the wireless communication device 204 shown in fig. 2A and 2B. In addition, each of the plurality of sensing transmitters 506- (1-M) may be implemented by a device such as the wireless communication device 402 shown in FIGS. 4A and 4B. In some embodiments, communication between the receiving device 502 and each of the plurality of sensing transmitters 506- (1-M) may be via a Station Management Entity (SME) and a Medium Access Control (MAC) layer management entity (MLME) protocol.

In some embodiments, the sensing decision unit 504 may be configured to receive the sensing measurements from the receiving device 502 and process the sensing measurements. In an example, the sensing decision unit 504 may process the sensing measurement. According to some embodiments, the sensing decision unit 504 may contain/perform a sensing algorithm. In an embodiment, the sensing decision unit 504 may be a site. In some embodiments, the sensing decision unit 504 may be an access point. According to an implementation, the sensing decision unit 504 may be implemented by a device such as the wireless communication device 102 shown in fig. 1. In some implementations, the sensing decision unit 504 may be implemented by a device such as the wireless communication device 204 shown in fig. 2A and 2B. In addition, the sensing decision unit 504 may be implemented by a device such as the wireless communication device 402 shown in fig. 4A and 4B. In some embodiments, the sensing decision unit 504 may 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 may function as a sensing initiator, wherein the sensing algorithm determines the measurement activity and the sensed measurement results required to complete the measurement activity. In an embodiment, the sensing decision unit 504 may be a sensing receiver. The sensing decision unit 504 may transmit the sensed measurements required to complete the measurement activity to the receiving device 502 to coordinate and control communications between the plurality of sensing transmitters 506- (1-M). According to some implementations, the sensing decision unit 504 may provide the processed sensing measurements to the sensing algorithm manager 508 for identifying one or more features of interest.

According to some embodiments, the sensing algorithm manager 508 may be configured to receive the processed sensing measurements from the sensing decision unit 504. In an example, the sensing algorithm manager 508 may further process and analyze the processed sensing measurements to identify one or more features of interest. According to some embodiments, the sensing algorithm manager 508 may contain/execute sensing algorithms. In an embodiment, the sensing algorithm manager 508 may be a site. In some embodiments, the sensing algorithm manager 508 may be an access point. According to one embodiment, the sensing algorithm manager 508 may be implemented by a device such as the wireless communication device 102 shown in fig. 1. In some embodiments, the sensing algorithm manager 508 may be implemented by a device such as the wireless communication device 204 shown in fig. 2A and 2B. In addition, the sensing algorithm manager 508 may be implemented by a device such as the wireless communication device 402 shown in fig. 4A and 4B. In some embodiments, the sensing algorithm manager 508 may 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 an embodiment, the sensing algorithm manager 508 may function as a sensing initiator, where the sensing algorithm determines the measurement activity and the sensed measurement results required to complete the measurement activity.

Referring to fig. 5 in more detail, the receiving device 502 may include a processor 510 and a memory 512. For example, the processor 510 and the memory 512 of the receiving device 502 may be the processor 114 and the memory 116, respectively, as shown in fig. 1. In an embodiment, the receiving device 502 may 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, RFE 518 may include an Automatic Gain Controller (AGC) 520, a down converter 522, and a Phase Locked Loop (PLL) unit 524, and baseband processor 528 may include a generation unit 526.

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

In one embodiment, AGC 520 may 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 embodiment, the down converter 522 may be configured to convert the received radio frequency signal back to an Intermediate Frequency (IF) signal or a baseband signal for further processing. According to an embodiment, the down converter 522 may be a low IF down converter or a zero IF down converter.

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

In an embodiment, the generation unit 526 may be coupled to the processor 510 and the memory 512. In some embodiments, the generation unit 526, as well as other units, may contain routines, programs, objects, components, data structures, etc., that may perform particular tasks or implement particular abstract data types. The generation unit 526 may 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.

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

In an embodiment, generation unit 526 may be responsible for receiving the sensing transmissions and associated transmission parameters, calculating sensing measurements, and processing the sensing measurements to achieve the sensing objective. In some embodiments, the generation unit 526 may be responsible for receiving data transmissions and processing the data transmissions to achieve data transmission goals. In some embodiments, the generation unit 526 may be configured to transmit the sensed measurement to the sensing decision unit 504 for further processing. In an embodiment, the generation unit 526 may be configured to cause at least one of the transmit antennas 514 to transmit a message to each of the plurality of sense transmitters 506- (1-M). In addition, the generation unit 526 may be configured to receive messages from each of the plurality of sensing transmitters 506- (1-M) through at least one of the receiving antennas 516.

In an embodiment, RFE 518 and baseband processor 528 may implement lower layers of a protocol stack, such as a Physical (PHY) layer or a lower portion of a MAC layer.

Referring again to fig. 5, the sensing decision unit 504 may implement upper layers of a protocol stack, such as a Medium Access Control (MAC) layer or an application layer. In an implementation, the sensing decision unit 504 may include a processor 528 and a memory 530. For example, the processor 528 and the memory 530 of the sensing decision unit 504 may be the processor 114 and the memory 116, respectively, as shown in fig. 1. In an embodiment, the sensing decision unit 504 may further include a transmit antenna 532, a receive antenna 534, a CSI equalization unit 536, and a group delay estimation and correction unit 538.

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

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

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

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

In an embodiment, the sensing transmitter 506-1 may include a processor 540-1 and a memory 542-1. For example, the processor 540-1 and memory 542-1 of the sensing transmitter 506-1 may be the processor 114 and memory 116, respectively, as shown in FIG. 1. In an embodiment, the sensing transmitter 506-1 may further comprise a transmitting antenna 544-1, a receiving antenna 546-1, a Transmitter Front End (TFE) 548-1, and a sensing agent 554-1. In one embodiment, TFE 548-1 may comprise an up-converter 550-1 and a power amplifier 552-1.

In some embodiments, antennas may be used for transmitting and receiving in a half-duplex format. When an antenna is transmitting, the antenna may be referred to as transmit antenna 544-1, and when an antenna is receiving, the antenna may be referred to as receive antenna 546-1. Those of ordinary skill in the art will appreciate that the same antenna may be the transmit antenna 544-1 in some cases and the receive antenna 546-1 in other cases. In the case of an antenna array, one or more antenna elements may be used to transmit or receive signals, for example, in a beamforming environment. In some examples, a set of antenna elements for transmitting the composite signal may be referred to as transmit antenna 544-1 and a set of antenna elements for receiving the composite signal may be referred to as receive antenna 546-1. In some examples, each antenna is equipped with its own transmit and receive paths that may be alternately switched to connect to the antenna depending on whether the antenna is operating as transmit antenna 544-1 or receive antenna 546-1.

According to one embodiment, the up-converter 550-1 may be configured to convert a baseband signal to a radio frequency signal. In one example, up-converter 550-1 may shift the spectrum of the baseband signal to a desired radio frequency band. In an embodiment, the power amplifier 552-1 may be configured to increase the amplitude of the power of a given input signal.

In an embodiment, the sensing agent 554-1 may be a block that exchanges physical layer parameters and instructions between the MAC layer of the sensing transmitter 506-1 and an application layer program or algorithm. The sensing agent 554-1 may 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.

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 may be considered logical functional blocks and may reside on any device that may support the features described herein. For example, the receiving device 502 may combine 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 may be implemented on the same device, and the sensing algorithm manager 508 is implemented by a second remote device. In the case where two functional blocks reside on the same device, then communication between the functional blocks may not require transmitting and receiving signals over the air through the transmit and receive antennas.

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

In accordance with one or more embodiments, communications in network 560 may be managed by one or more standards in the 802.11 family of standards developed by IEEE. Some example IEEE standards may 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, whereas IEEE 802.11me reflects continuous 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, which adds new functionality. In some embodiments, communications may 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 may be implemented by instances of any type of network, including wireless networks or cellular networks.

In an embodiment, wi-Fi sensing may be performed based on detecting a disturbance in an OTA channel. An OTA channel is referred to herein as the propagation path of a signal between a transmitter antenna and a receiver antenna. Wi-Fi sensing may depend on the transmitted signal generated by the baseband transmitter and the received signal processed by the baseband receiver to calculate CSI. The path between the baseband transmitter and the baseband receiver may be referred to as a measured channel, and in one example, the measured channel is not equal to an OTA channel because the measured channel includes the processing effects of both the baseband transmitter and the baseband receiver. The baseband receiver may be interchangeably referred to as a baseband processor. In an example, the CSI calculated at the baseband receiver may be referred to as measured CSI (M-CSI).

Referring back to fig. 5, according to one or more embodiments, the receiving device 502 may initiate a measurement activity (or Wi-Fi sensing session) for Wi-Fi sensing purposes. During measurement activities, transmission exchanges between the receiving device 502 and the plurality of sensing transmitters 506- (1-M) may occur. In one example, the MAC layer of the IEEE 802.11 stack may be utilized to control these transmissions. A representation of the propagation channel between the receiving device and the sensing transmitter is captured by a measure of Channel State Information (CSI).

According to an example embodiment, the receiving device 502 may initiate the measurement activity by one or more sensing trigger messages. In an embodiment, the generation unit 526 may 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 sense trigger message for each of the plurality of sense transmitters 506- (1-M) may differ in content. The response to the sensing trigger message may be a sensing transmission. In an example, the sensing trigger message may include the requested transmission configuration. Other examples of information/data contained in the sensing trigger message not discussed herein are contemplated herein. According to an embodiment, the generation unit 526 may send a sensing trigger message to each of the plurality of sensing transmitters 506- (1-M). In an embodiment, the generation unit 526 may send a sensing trigger message to each of the plurality of sensing transmitters 506- (1-M) via the transmit antenna 514.

According to an embodiment, each of the plurality of sensing transmitters 506- (1-M) may receive a 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) may generate a sensing transmission. In an embodiment, each of the plurality of sensing transmitters 506- (1-M) may generate a sensing transmission using the requested transmission configuration defined by the sensing trigger message. Subsequently, each of the plurality of sensing transmitters 506- (1-M) may send a 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 may include a communicated transmission configuration corresponding to the requested transmission configuration.

According to an embodiment, the receiving device 502 may receive from the plurality of sensing transmitters 506- (1-M) a sensing transmission sent in response to the one or more sensing trigger messages. The receiving device 502 may be configured to receive the sensing transmissions from the plurality of sensing transmitters 506- (1-M) via the receiving antenna 516. According to an embodiment, the generating unit 526 may be configured to generate a sensing measurement representing the measured channel state information (M-CSI) based on the sensing transmission.

C. isolating electronic environment to improve channel estimation

Fig. 6 depicts an example 600 of a measured channel relative to an OTA channel, in accordance with some embodiments.

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

As depicted in FIG. 6, TFE 548-1 may include an up-converter 550-1 and a power amplifier 552-1. In addition, RFE 518 may include AGC 520, down converter 522, PLL unit 524, and Band Pass Filter (BPF) 602. In one embodiment, TFE 548-1 and RFE 518 may cause disturbances in the M-CSI.

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

In one embodiment, when a signal is received and applied to an input port of AGC 520, the amplitude of the signal is amplified by the AGC gain of AGC 520, which is set at that time. In the case where the AGC gain is applied differently across the frequency band (e.g., in the case of very wideband signals), the gain distortion may be characterized across the frequency band, and the AGC gain information may contain a plurality of values that are each applicable to a portion of the received signal, where the plurality of values may contain values that cover the frequency band of the entire received signal. In one example, the plurality of values may be calculated from an AGC gain mask describing the frequency response of the AGC across the frequency band. In an example, the AGC gain mask is comprised of two or more values that scale the value of the AGC gain according to a frequency range that is a subset of the frequency band. In an example, the ACG gain mask is stored by AGC 520 for purposes of use in the manner described.

In one implementation, group delay is a characteristic of a physical channel or element (e.g., a filter). Group delay may represent the change in the amount of phase shift of a signal with respect to frequency caused by a channel or element. In an example, 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 non-ideal channels, the group delay of the M-CSI is not straight line. In contrast, the group delay of M-CSI is a superposition of all the group delays involved in the part, including the group delay of the ideal OFDM channel, the group delay due to the real channel distortion, and the group delay of the non-ideal filter, and may have discontinuities. Before the M-CSI can be used for sensing, the group delay of the ideal OFDM channel needs to be estimated with sufficient accuracy.

According to an embodiment, baseband processor 528 of receiving apparatus 502 may be configured to perform CSI measurements to calculate M-CSI based on the received sensing transmissions from the plurality of sensing transmitters 506- (1-M). In some embodiments, receiving device 502 may calculate the contribution of RFE 518 to the M-CSI. In an example, RFE 518 may include analog and digital components. For example, RFE 518 may contain analog and digital components by which the received signal may travel from a reference point to a point where generation unit 526 of receiving device 502 may read the received signal. A representation 700 of the receiver chain of the receiving device 502 is shown in fig. 7. As illustrated in fig. 7, the in-phase (I) and four-phase (Q) modulation symbols arrive at the front end of the receiver, where synchronization including frequency and timing recovery is performed. In addition, the time domain guard period (cyclic prefix) is removed and the receiver performs a Fast Fourier Transform (FFT) on the received signal (e.g., I and Q modulation symbols). The guard tone and DC tone are then removed. The M-CSI is then generated before data demapping, de-interleaving (using a de-interleaver), de-puncturing (de-puncturing), decoding (using a viterbi decoder), and finally descrambling (using a descrambler). As a result of the descrambling, data bits are generated. The generated M-CSI is provided to generation component 526.

According to one embodiment, the M-CSI is modeled as comprising 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 sensing features of interest in space; and the contribution of RFE 518 of receiving apparatus 502.

In an embodiment, after receiving the M-CSI, the receiving device 502 may send the M-CSI to the sensing decision unit 504. According to an embodiment, the receiving device 502 may also send receiver front-end status information (RFE-SI) along with the M-CSI to the sensing decision unit 504. In some implementations, the baseband processor may send the M-CSI and RFE-SI to the sensing decision unit 504. In an example, the RFE-SI may include at least one of: phase change indicator, automatic Gain Controller (AGC) information, and downconverter type information. Other examples of RFE-SI not discussed herein are contemplated herein. In an embodiment, the term "information" is used to equally capture signals and messages representing aspects of RFE 518.

Fig. 8 depicts an RFE disturbance correction architecture 800 according to some embodiments.

As depicted in fig. 8, the RFE disturbance correction architecture 800 includes an RFE 518, a baseband processor 528, a sensing decision unit 504, and a sensing algorithm manager 508.RFE 518 may include AGC 520, down converter 522, and PLL unit 524. In addition, baseband processor 528 may 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, CSI equalization unit 536, group delay estimation and correction unit 538, and sensing algorithm manager 508 may facilitate CSI processing.

In an embodiment, baseband processor 528 may perform a plurality of sensing measurements based on CSI contributed by the physical channel between receiving device 502 and each of the plurality of sensing transmitters 506- (1-M) and CSI contributed by RFE 518 of receiving device 502. The baseband processor 528 may then output M-CSI representing each of the sensed measurements. In an embodiment, the M-CSI and RFE-SI may be passed to the sensing decision unit 504 through the MLME interface or as dedicated data transmissions from application to application. As illustrated in fig. 8, RFE-SI may contain AGC information (represented by arrow "a"), a phase change indicator (represented by arrow "B"), and downconverter type information (represented by arrow "C").

Although fig. 8 shows that the AGC information, phase change indicator, and downconverter type information bypasses baseband processor 528, in some embodiments the AGC information, phase change indicator, and downconverter type information may be fed into baseband processor 528 by RFE 518, and baseband processor 528 may output the AGC information, phase change indicator, and downconverter type information to sensing decision unit 504.

In one embodiment, the a/D converter of baseband processor 528 may convert the AGC information from analog to digital form after receiving the AGC information. In one embodiment, the A/D converter may be the A/D converter 804 of the baseband processor 528. The baseband processor 528 may then pass the digital AGC information to the sensing decision unit 504. Similarly, upon receiving the phase change indicator, the a/D converter of baseband processor 528 may convert the phase change indicator from analog form to digital form. In an embodiment, the a/D converter may be the same a/D converter that converts the AGC information, or the a/D converter may be the a/D converter 804 of the baseband processor 528. The baseband processor 528 may then pass the digital phase change indicator to the sensing algorithm manager 508. In addition, the a/D converter of baseband processor 528 may convert the downconverter type information from analog to digital form after receiving the downconverter type information. In an embodiment, the a/D converter may be the same a/D converter that converts the AGC information and the phase change indicator, or the a/D converter may be the a/D converter 804 of the baseband processor 528. The baseband processor 528 may then pass the digital down-converter type information to the sensing decision unit 504.

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

FIG. 9 depicts an example 900 of an RFE-SI in an RFE disturbance correction architecture 800, in accordance with some embodiments. As depicted in fig. 9, baseband processor 528 may provide RFE-SI as an RFE-SI message (represented by arrow "D") to sensing decision unit 504 and sensing algorithm manager 508. Additionally, RFE 518 may provide RFE-SI as an RFE-SI signal (represented by arrow "E") to sensing decision unit 504 and sensing algorithm manager 508. In an embodiment, either or both of the RFE-SI message and the RFE-SI signal may be present at any time.

Fig. 10 depicts a structure 1000 of PLL unit 524 according to some embodiments.

As illustrated in fig. 10, PLL unit 524 may include a phase detector 1002, a loop filter 1004, and a Voltage Controlled Oscillator (VCO) 1006. In one example, the phase detector 1002 may also be referred to as an interchangeable phase comparator. In an example, loop filter 1004 may be a low pass filter. In one embodiment, VCO 1006 may generate a sinusoidal waveform as its output. The sinusoidal waveform may be referred to as a VCO output waveform. In one embodiment, the VCO output waveform may be sent back to the phase detector 1002 (represented by arrow "F"). The VCO output waveform may also be sent as an output (represented by arrow "G") to the down converter 522. In an embodiment, the phase detector 1002 may compare the phase of the VCO output waveform with the phase of the input waveform to generate an output voltage proportional to the difference between the two phase inputs. The phase detector 1002 may pass the output voltage to a loop filter 1004. In one embodiment, the loop filter 1004 may 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 may then be applied to VCO 1006 to control the frequency of VCO 1006. In an example, and because the phase is an integral of frequency, the filtered output voltage applied to VCO 1006 may also control the phase of the VCO output waveform. In an example, a higher filtered output voltage generates a higher frequency of VCO 1006.

In an embodiment, the phase detector 1002, loop filter 1004, and VCO 1006 may create a phase negative feedback loop that may pull the phase of the VCO output waveform to track the phase change of the input waveform. In an embodiment, when the phase negative feedback loop is in a locked state (i.e., synchronized), the VCO output waveform may have the same frequency and phase as the input waveform, and thus be synchronized with the input waveform.

In some examples, PLL unit 524 may be in an out-of-lock 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 out-of-lock state, the VCO output waveform provided to down converter 522 may have a phase offset or phase drift (equivalent to a frequency offset), which may be reflected as distortion in the M-CSI. Such distortion in the M-CSI may be interpreted by the sensing algorithm as a disturbance in the OTA channel, resulting in false detection.

In an example, when PLL unit 524 is in a locked state, the output voltage applied to VCO 1006 may remain constant or near a constant value. Conversely, when PLL unit 524 is in an out-of-lock state, the output voltage applied to VCO 1006 may vary more widely. Thus, the output voltage is an indicator of the phase change that may exist in the M-CSI due to VCO 1006. The output voltage may be referred to as a phase change indicator and is provided to the sensing algorithm.

In one example, the phase change indicator may be an analog signal that may be digitized before being provided to the sensing algorithm. For example, an analog phase change indicator may be input to the baseband processor 528. In one embodiment, baseband processor 528 may convert the analog phase change indicator to a digital phase change indicator and may provide the digital phase change indicator to the sensing algorithm. In some embodiments, PLL unit 524 may be a digital PLL, and the phase change indicator may already exist in digital form. Additionally, in some embodiments, the sensing decision unit 504 may include an a/D converter that may convert the analog phase change indicator into a digital signal. Thus, the voltage output from the loop filter 1004 and applied to the VCO 1006 may be provided to the sensing algorithm as a phase change indicator. In an example, the phase change indicator may indicate that PLL unit 524 is out of lock, and in such a case, the sensing algorithm may not consider CSI changes to avoid false motion detection. In some embodiments, the phase change indicator may be further filtered before being used by the sensing algorithm. In one example, the phase change indicator may be low pass filtered to suppress high frequency changes that may be artifacts of other signal impairments.

Signals such as multi-tone OFDM signals, which include a series of frequency components through an ideal system such as an ideal channel or ideal filter, experience the same time delay across all frequency components. Thus, the phase shift of each frequency component may be proportional to the frequency of each frequency component. An example of a group delay 1100 for 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 illustrated in fig. 11, the group delay of a distortion-free channel is a straight line with a negative slope. In the case of non-ideal Wi-Fi channels, the group delay of the M-CSI may not be as described in example 1100. In such cases, the group delay of the M-CSI may be a superposition of the group delays contributed by each signal processing element, including the group delay of the ideal channel.

In an implementation, for M-CSI to be used for motion sensing, it may be desirable to estimate the group delay of the channel with sufficient accuracy. However, the group delay of the M-CSI may comprise the group delay of the filters used in downconverter 522, and the nature or form of the group delay of the filters used in downconverter 522 may depend on the type of downconverter 522 implemented (i.e., whether downconverter 522 is a low-IF downconverter or a zero-IF downconverter).

According to one embodiment, the radio frequency signal may be expressed mathematically using equation (8) provided below.

Where Real x represents the Real part x of the complex number,F _c denotes a carrier frequency, I (t) denotes an in-phase component of the baseband signal, and Q (t) denotes a quadrature component of the baseband signal. In an embodiment, the down-converter 522 may be configured to recover the in-phase component I (t) and the quadrature component Q (t) from the received radio frequency signal.

Fig. 12 depicts a block diagram of a zero IF down converter 1200 with two branches, in accordance with some embodiments.

In an embodiment, the zero IF down converter 1200 may be a down converter with a single mixer stage for converting a received radio frequency signal to a baseband signal in a single step. In one example, the radio frequency signal may be received by a receive antenna 516 of the receiving device 502. As illustrated in fig. 12, the zero IF down converter 1200 may include two branches, a first branch 1202 and a second branch 1204. Further, as depicted in fig. 12, the outputs of the first branch 1202 and the second branch 1204 are an in-phase I (t) baseband signal and a quadrature Q (t) baseband signal, respectively. The first branch 1202 may include a first mixer 1206, a first low-pass filter 1208, and a first notch filter 1210. In one embodiment, the first mixer 1206 may be a nonlinear device that multiplies the radio frequency signal with a local carrier f _c, which is synchronized in frequency and phase with the radio frequency signal. In an example, the local carrier f _c is generated by the PLL unit 524. According to one embodiment, the output of the first mixer 1206 may include a baseband signal, a high frequency component, and a Direct Current (DC) component. In one example, of these components, only the baseband signal is useful and is the desired signal. The undesired high frequency components may be suppressed (or attenuated) by the first low pass filter 1208 and the DC components may be suppressed by the first notch filter 1210. In addition, the second branch 1204 may include a second mixer 1212, a second low pass filter 1214, and a second notch filter 1216.

In accordance with aspects of the present disclosure, the description of the first branch 1202, the first mixer 1206, the first low-pass filter 1208, and the first notch filter 1210 applies equally to the second branch 1204, the second mixer 1212, the second low-pass filter 1214, and the second notch filter 1216, respectively.

In one embodiment, the notch filter may be a type of band reject filter that can attenuate frequencies within a particular range while passing all other frequencies without attenuation (or with minimal attenuation). Fig. 13A and 13B depict characteristics of an example of a notch filter according to some embodiments. In fig. 13A, plot 1302 shows the amplitude versus frequency change of the notch filter (clearly demonstrating frequency selective attenuation). In fig. 13B, plot 1304 shows the change in phase shift of the notch filter with respect to frequency (i.e., group delay). Group delay is shown to have a phase discontinuity (i.e., a phase jump) at the notch filter center frequency f _E.

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

Fig. 14 depicts a block diagram of a two-stage low IF down converter 1400 with two branches in accordance with some embodiments.

In one embodiment, the two-stage low-IF down converter 1400 may be a down converter having two-stage mixers (i.e., a first stage and a second stage). The first stage may convert the received radio frequency signal to a low IF signal, wherein the bandpass filter may allow only the desired IF signal to pass. In addition, the bandpass filter may attenuate all other undesirable lower and higher frequency components. The second stage may convert the IF signal to a baseband signal. As illustrated in fig. 14, the low IF down converter 1400 may 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 an in-phase I (t) baseband signal and a quadrature Q (t) baseband signal, respectively. First branch 1402 may include a first mixer 1406, a first band-pass filter 1408, a second mixer 1410, and a first low-pass filter 1412. In addition, the second branch 1404 may include a third mixer 1414, a second bandpass filter 1416, a fourth mixer 1418, and a second lowpass filter 1420.

In an implementation of low-IF down-converter 1400, the resulting baseband signal in each of first finger 1402 and second finger 1404 may not include a DC component. Thus, low IF down converter 1400 may not require a notch filter and thus the group delay of M-CSI may not have discontinuities within its frequency band.

Referring again to fig. 5, in an embodiment, the sensing decision unit 504 may be configured to receive M-CSI representing the sensing measurements from the receiving device 502. In addition, the sensing decision unit 504 may be configured to receive RFE-SI from the receiving device 502. In an example implementation, the sensing decision unit 504 may receive the M-CSI and RFE-SI from the receiving device 502 through the receiving antenna 534. In an embodiment, the sensing decision unit 504 may receive M-CSI through the MLME and the SME.

According to an embodiment, upon receiving the M-CSI and RFE-SI, the sensing decision unit 504 may be configured to cancel or reduce the effect of the disturbance caused by the RFE 518 in the M-CSI on the sensing decision. In an embodiment, the sensing decision unit 504 may determine sensing decision input information according to the M-CSI and RFE-SI. In an example, the sensing decision input information may include processed channel state information (P-CSI).

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

According to some embodiments, CSI equalization unit 536 may be configured to determine from the AGC information the AGC gain that AGC 520 applies to the sensed transmission captured in the M-CSI to perform equalization of the M-CSI. In an example, the AGC information may be equivalent to the AGC gain applied by AGC 520 to the sensed transmission. In some embodiments, CSI equalization unit 536 may perform equalization of M-CSI based on both AGC information and strength of the M-CSI. In an example, the strength of all or a portion of the M-CSI may be represented by a root mean square value of the amplitude of all or a portion of the M-CSI tones.

In an embodiment, CSI equalization unit 536 may make a first determination of whether the AGC information exceeds a first threshold. In an embodiment, CSI equalization unit 536 may be configured to make a second determination of whether the strength of the portion of M-CSI exceeds a second threshold. In response to determining that the AGC information does not exceed the first threshold and the strength of the portion of the M-CSI does not exceed the second threshold, CSI equalization unit 536 may perform gain adjustment on the M-CSI. In an embodiment, CSI equalization unit 536 may perform 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, CSI equalization unit 536 may set the sensing decision input information to P-CSI.

In an embodiment, CSI equalization unit 536 may multiply the amplitude of all M-CSI tones by an AGC scaling factor to apply a gain to all or a portion of the M-CSI tones provided by baseband processor 528. In an example, CSI equalization unit 536 may multiply the amplitude of all or a portion of the M-CSI tones provided by baseband processor 528 by an AGC scaling factor proportional to the inverse of the AGC information to create P-CSI. In an embodiment, CSI equalization unit 536 may determine P-CSI using equation (9) provided below.

Where AGC _FcGH" is the AGC scaling factor, a is the multiplier, and b is the offset.

In some embodiments, CSI equalization unit 536 may be configured to filter the AGC information using a low pass filter before making the first determination and the second determination.

According to some embodiments, a determination that the AGC information does not exceed the first threshold may indicate that the RFE 518 is largely saturated by the interferer, thereby significantly reducing the AGC gain, and the likelihood of signal disturbance resolution (the a/D converter 804 passed to the baseband processor 528) may be very low because the interferer dominates the available a/D resolution. In such cases, the accuracy of the resulting measurement may not be sufficient to perform Wi-Fi sensing even if subsequently multiplied by CSI equalization unit 536. In one example, CSI equalization unit 536 may set the sensing decision input information to a null input in response to a determination that the AGC information does not exceed the first threshold, or in another example, it may discard the M-CSI and not pass the M-CSI further to, for example, sensing algorithm manager 508.

According to some embodiments, CSI equalization unit 536 may 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 the root mean square of the portion of M-CSI exceeds a second threshold.

In one embodiment, CSI equalization unit 536 may calculate the strength of the relevant tones of the M-CSI. In an example, the relevant tones of the M-CSI may be tones of the M-CSI corresponding to the sensing transmissions received by the receiving device 502 from the sensing transmitter 506- (1-M). In an example, the associated tones of the M-CSI may be a subset or portion of all tones of the M-CSI. If the strength of the associated tone of the M-CSI is below the second threshold, the CSI equalization unit 536 may create the P-CSI by multiplying the amplitude of the associated tone of the M-CSI tone by the AGC scaling factor determined according to equation (9). In some implementations, if the AGC information is below a first threshold, however, the strength of the associated tones of the M-CSI is greater than a second threshold, the M-CSI may not be strong enough to detect object movement. Thus, CSI equalizing unit 536 may set P-CSI equal to M-CSI, and P-CSI may be considered to be equal to M-CSI. In an embodiment, setting the P-CSI to M-CSI corresponding to a low AGC gain may facilitate improving the detectability of movement of the object.

According to an embodiment, the group delay estimation and correction unit 538 may calculate the group delay of the M-CSI based on the down-converter type information. In an embodiment, the group delay estimation and correction unit 538 may process all tones of the M-CSI together as a single piece of information. In an embodiment, the group delay estimation and correction unit 538 may generate the P-CSI by adjusting the M-CSI according to the down-converter type information. In addition, the group delay estimation and correction unit 538 may set the sensing decision input information to P-CSI.

In one embodiment, the group delay estimation and correction unit 538 may determine whether the down converter 522 is a zero IF down converter or a low IF down converter. In response to determining that down-converter 522 is a zero-IF down-converter, group delay estimation and correction unit 538 may independently calculate group delays over the lower and upper portions of the signal bandwidth and combine the individual calculations of the group delays. In addition, the group delay estimation and correction unit 538 may generate the P-CSI from a single calculation of a combination of group delays. In addition, in response to determining that the down-converter 522 is a low IF down-converter, the group delay estimation and correction unit 538 may calculate a group delay over the entire signal bandwidth. In addition, the group delay estimation and correction unit 538 may generate P-CSI from the calculated group delay. In an example, in response to determining that down-converter 522 is a low IF down-converter, group delay estimation and correction unit 538 may not perform any processing on the signal and generate P-CSI without any estimation of group delay.

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

FIG. 15 depicts a flowchart 1500 for determining sensing decision input information, according to some embodiments.

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

Step 1502 includes receiving M-CSI representing sensed measurements. According to an embodiment, the sensing decision unit 504 may be configured to receive M-CSI representing sensed measurements from the receiving device 502.

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

Step 1506 includes determining sensing decision input information from the RFE-SI. According to an embodiment, the sensing decision unit 504 may be configured to determine sensing decision input information according to RFE-SI.

Fig. 16 depicts a flowchart 1600 for sending M-CSI to a sensing decision unit 504, according to some embodiments.

In a brief overview of one embodiment of the flowchart 1600, at step 1602, a sensing transmission is received from a plurality of sensing transmitters 506- (1-M). At step 1604, M-CSI is generated based on the sensed transmission. At step 1606, the M-CSI is sent to sensing decision unit 504.

Step 1602 includes receiving a sensing transmission from a plurality of sensing transmitters 506- (1-M). According to an embodiment, the receiving device 502 may be configured to receive the sensing transmissions from the plurality of sensing transmitters 506- (1-M).

Step 1604 includes generating M-CSI based on the sensed transmission. According to an embodiment, the receiving device 502 may be configured to generate M-CSI based on the sensed transmission.

Step 1606 includes sending the M-CSI to sensing decision unit 504. According to an embodiment, the receiving device 502 may be configured to send the M-CSI to the sensing decision unit 504.

FIG. 17 depicts a flowchart 1700 for determining sense decision input information from RFE-SI, which includes a phase change indicator, in accordance with some embodiments.

In a brief overview of one embodiment of the flowchart 1700, at step 1702, M-CSI representing sensed measurements is received. At step 1704, an RFE-SI is received, wherein the RFE-SI includes a phase change indicator. At step 1706, sensing decision input information is determined from RFE-SI, 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 M-CSI.

Step 1702 includes receiving M-CSI representing sensed measurements. According to an embodiment, the sensing decision unit 504 may be configured to receive M-CSI representing sensed measurements from the receiving device 502.

Step 1704 includes receiving an RFE-SI, wherein the RFE-SI includes a phase change indicator. According to an embodiment, the sensing decision unit 504 may be configured to receive RFE-SI from the receiving device 502. In an example, the RFE-SI may include a phase change indicator.

Step 1706 includes determining sense decision input information from the RFE-SI, wherein determining sense decision input information includes setting sense 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. According to an embodiment, the sensing decision unit 504 may be configured to determine whether the phase change indicator indicates a phase change in the M-CSI. In response to a determination that the phase change indicator indicates a phase change in the M-CSI, the sensing decision unit 504 may set the sensing decision input information to a null input.

Fig. 18 depicts a flow diagram 1800 for determining sensing decision input information from RFE-SI, where RFE-SI contains downconverter type information, in accordance with some embodiments.

In a brief overview of one implementation of flowchart 1800, at step 1802, M-CSI representing sensed measurements is received. At step 1804, an RFE-SI is received, wherein the RFE-SI contains downconverter type information. At step 1806, sensing decision input information is determined from the RFE-SI, wherein determining the sensing decision input information includes: calculating group delay of the M-CSI according to the down converter type information; generating P-CSI by adjusting M-CSI according to group delay; and setting the sensing decision input information to P-CSI. At step 1808, the sensing decision input information is sent to the sensing algorithm manager 508.

Step 1802 includes receiving M-CSI representing sensed measurements. According to an embodiment, the sensing decision unit 504 may be configured to receive M-CSI representing sensed measurements from the receiving device 502.

Step 1804 includes receiving an RFE-SI, wherein the RFE-SI includes downconverter type information. According to an embodiment, the sensing decision unit 504 may be configured to receive RFE-SI from the receiving device 502. In an example, the RFE-SI may contain down-converter type information.

Step 1806 includes determining sensing decision input information according to RFE-SI, wherein determining sensing decision input information includes: calculating group delay of the M-CSI according to the down converter type information; generating P-CSI by adjusting M-CSI according to group delay; and setting the sensing decision input information to P-CSI. According to an embodiment, the sensing decision unit 504 may be configured to determine the sensing decision input information based on: calculating group delay of the M-CSI according to the down converter type information; generating P-CSI by adjusting M-CSI according to group delay; and setting the sensing decision input information to P-CSI.

Step 1808 includes sending the sensing decision input information to the sensing algorithm manager 508. According to an embodiment, the sensing decision unit 504 may be configured to send the sensing decision input information to the sensing algorithm manager 508.

Fig. 19A and 19B depict a flow chart 1900 for determining sensing decision input information from RFE-SI, where RFE-SI contains AGC information, in accordance with some embodiments.

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

Step 1902 includes receiving M-CSI representing sensed measurements. According to an embodiment, the sensing decision unit 504 may be configured to receive M-CSI representing sensed measurements from the receiving device 502.

Step 1904 includes receiving RFE-SI, where the RFE-SI includes AGC information. According to an embodiment, the sensing decision unit 504 may be configured to receive RFE-SI from the receiving device 502. In one example, the RFE-SI may contain AGC information.

Step 1906 includes determining whether the AGC information exceeds a first threshold. According to an embodiment, the sensing decision unit 504 may be configured to determine whether the AGC information exceeds a first threshold. If it is determined that the AGC information exceeds the first threshold, the flow chart 1900 proceeds to step 1910 ("yes" branch), and if it is determined that the AGC information does not exceed the first threshold, the flow chart 1900 proceeds to step 1912 ("no" branch).

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

Step 1910 includes setting the sensing decision input information to an M-CSI input. According to an embodiment, the sensing decision unit 504 may be configured to set the sensing decision input information to M-CSI.

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

Step 1914 includes setting the sensing decision input information to P-CSI. According to an embodiment, the sensing decision unit 504 may be configured to set the sensing decision input information to P-CSI.

Step 1916 includes sending the sensing decision input information to the sensing algorithm manager 508. According to an embodiment, the sensing decision unit 504 may be configured to send the sensing decision input information to the sensing algorithm manager 508.

Embodiment 1 is a method for Wi-Fi sensing performed by a sensing decision unit operating on at least one processor. The method comprises the following steps: receiving, by the sensing decision unit, measured channel state information (M-CSI) representing sensed 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.

Embodiment 2 is the method of embodiment 1, further comprising: receiving, by a receiving device comprising a Receiver Front End (RFE) with a receiving antenna, a sensing transmission from a plurality of sensing transmitters; and generating, by the receiving device, the M-CSI based on the sensing transmission.

Embodiment 3 is the method of embodiment 2, wherein the receiving device further comprises the at least one processor.

Embodiment 4 is the method of embodiment 2 or 3, wherein the RFE-SI is provided as a message to the sensing decision unit by a baseband processor of the receiving device.

Embodiment 5 is the method of any one of embodiments 2-4, wherein the RFE-SI is provided as one or more digital signals to the sensing decision unit by at least one of a baseband processor of the receiving device and the RFE.

Embodiment 6 is the method of any one of embodiments 2-5, wherein the RFE-SI is provided as one or more digital signals and one or more analog signals to the sensing decision unit by at least one of a baseband processor of the receiving device and the RFE.

Embodiment 7 is the method of any one of embodiments 1-6, wherein the RFE-SI comprises a phase change indicator.

Embodiment 8 is the method of embodiment 7, wherein determining the sense decision input information includes setting the sense decision input information to a null input in response to the phase change indicator indicating a determination of a phase change in the M-CSI.

Embodiment 9 is the method of any one of embodiments 1-8, wherein the RFE-SI includes Automatic Gain Controller (AGC) information.

Embodiment 10 is the method of embodiment 9, 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 AGC information does not exceed a first threshold.

Embodiment 11 is the method of embodiment 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 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.

Embodiment 12 is the method of any one of embodiments 9-11, wherein determining the sensing decision input information comprises: generating processed channel state information (P-CSI) by multiplying the 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 setting the sensing decision output information to the P-CSI.

Embodiment 13 is the method of any one of embodiments 9-12, wherein determining the sensing decision input information comprises: the sensing decision input information is set 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.

Embodiment 14 is the method of any one of embodiments 1-13, wherein the RFE-SI includes downconverter type information.

Embodiment 15 is the method of embodiment 14, wherein determining the sensing decision input information includes: calculating the group delay of the M-CSI according to the down converter 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.

Embodiment 16 is the method of any one of embodiments 11-15, further comprising sending the sensing decision input information to a sensing algorithm manager.

Embodiment 17 is the method of any one of embodiments 12-16, further comprising sending the sensing decision input information to a sensing algorithm manager.

Embodiment 18 is the method of any one of embodiments 15-17, further comprising sending the sensing decision input information to a sensing algorithm manager.

Embodiment 19 is a system for Wi-Fi sensing. The system includes at least one processor configured to execute instructions to operate a sensing decision unit, the instructions configured to: receiving measured channel state information (M-CSI) representing sensing measurements; receiving receiver front-end status information (RFE-SI); and determining sensing decision input information according to the RFE-SI.

Embodiment 20 is the system of embodiment 19, further comprising a receiving device including a Receiver Front End (RFE) having a receiving antenna, and configured to: receiving a sensing transmission from a plurality of sensing transmitters; and generating the M-CSI based on the sensing transmission.

Embodiment 21 is the system of embodiment 20, wherein the at least one processor is included in the receiving device.

Embodiment 22 is the system of embodiment 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.

Embodiment 23 is the system of any one of embodiments 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.

Embodiment 24 is the system of any one of embodiments 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.

Embodiment 25 is the system of any one of embodiments 19-24, wherein the RFE-SI comprises a phase change indicator.

Embodiment 26 is the system of embodiment 25, wherein the instructions for determining the sense decision input information include instructions for setting the sense decision input information to a null input in response to the phase change indicator indicating a determination of a phase change in the M-CSI.

Embodiment 27 is the system of any one of embodiments 19-26, wherein the RFE-SI includes Automatic Gain Controller (AGC) information.

Embodiment 28 is the system of embodiment 27, wherein the instructions for determining the sensing decision input information include instructions for 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.

Embodiment 29 is the system of embodiment 27 or 28, wherein the instructions for determining the sensing decision input information include instructions for: 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.

Embodiment 30 is the system of any one of embodiments 27-29, wherein the instructions for determining the sensing decision input information include instructions for: generating processed channel state information (P-CSI) by multiplying the 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 setting the sensing decision output information to the P-CSI.

Embodiment 31 is the system of any one of embodiments 27-30, wherein the instructions for determining the sensing decision input information include instructions for: the sensing decision input information is set 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.

Embodiment 32 is the system of any one of embodiments 19-31, wherein the RFE-SI includes downconverter type information.

Embodiment 33 is the system of embodiment 32, wherein the instructions for determining the sensing decision input information include instructions for: calculating the group delay of the M-CSI according to the down converter 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.

Embodiment 34 is the system of any one of embodiments 29-33, wherein the at least one processor is further configured with instructions to send the sensing decision input information to a sensing algorithm manager.

Embodiment 35 is the system of any one of embodiments 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.

Embodiment 36 is the system of any one of embodiments 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.

While various embodiments of methods and systems have been described, these embodiments are illustrative and in no way limit the scope of the described methods or systems. Changes in form and detail of the described methods and systems may be made by those skilled in the relevant art without departing from the broadest scope of the described methods and systems. Thus, the scope of the methods and systems described herein should not be limited by any of the illustrative embodiments, and should be defined according to the following claims and their equivalents.

Claims

1. A method for Wi-Fi sensing, the method being performed by a sensing decision unit operating on at least one processor, the method comprising:

Receiving, by the sensing decision unit, measured channel state information (M-CSI) representing a sensing measurement result;

Receiving, by the sensing decision unit, receiver front-end status information (RFE-SI); and

Sensing decision input information is determined by the sensing decision unit and based on the RFE-SI.

2. The method according to claim 1, further comprising:

receiving, by a receiving device including a receiver front end (RFE) having a receiving antenna, sensing transmissions from a plurality of sensing transmitters; and

The M-CSI is generated by the receiving device based on the sensing transmission.

The method of claim 2 , wherein the receiving device further comprises the at least one processor.

4 . The method according to claim 2 , wherein the RFE-SI is provided as a message by a baseband processor of the receiving device to the sensing decision unit.

5. The method of claim 2, wherein the RFE-SI is provided to the sensing decision unit by at least one of a baseband processor of the receiving device and the RFE as one or more digital signals.

6. The method of claim 2, wherein the RFE-SI is provided to the sensing decision unit by at least one of a baseband processor of the receiving device and the RFE as one or more digital signals and one or more analog signals.

The method of claim 1 , wherein the RFE-SI comprises a phase change indicator.

8. The method of claim 7, wherein determining the sensing decision input information comprises 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.

9. The method of claim 1, wherein the RFE-SI includes automatic gain controller (AGC) information.

10. The method of claim 9, wherein determining the sensing decision input information comprises 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.

11. The method of claim 9, wherein determining the sensory decision input information comprises:

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

The sensing decision input information is set as the P-CSI.

12. The method of claim 9, wherein determining the sensory decision input information comprises:

generating processed channel state information (P-CSI) by multiplying the 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 strength of the portion of the M-CSI does not exceed a second threshold; and

The sensing decision output information is set as the P-CSI.

13. The method of claim 9, wherein determining the sensory decision input information comprises:

The sensing decision input information is set to the M-CSI in response to a first determination that the AGC information exceeds a first threshold and a second determination that a strength of a portion of the M-CSI exceeds a second threshold.

14. The method of claim 1, wherein the RFE-SI includes downconverter type information.

15. The method of claim 14, wherein determining the sensory decision input information comprises:

Calculate the group delay of the M-CSI according to the down converter type information;

generating processed channel state information (P-CSI) by adjusting the M-CSI according to the group delay; and

The sensing decision input information is set as the P-CSI.

16. The method of claim 11, further comprising sending the sensing decision input information to a sensing algorithm manager.

17. The method of claim 12, further comprising sending the sensing decision input information to a sensing algorithm manager.

18. The method of claim 15, further comprising sending the sensing decision input information to a sensing algorithm manager.

19. A system for Wi-Fi sensing, the system comprising:

at least one processor configured to execute instructions to operate a sensing decision unit, the instructions configured to:

receiving measured channel state information (M-CSI) representing sensing measurement results;

receiving receiver front-end status information (RFE-SI); and

Sensing decision input information is determined according to the RFE-SI.

20. The system of claim 19, further comprising

A receiving device, the receiving device comprising a receiver front end (RFE) having a receiving antenna and configured to:

receiving sensing transmissions from a plurality of sensing transmitters; and

The M-CSI is generated based on the sensing transmission.

21. The system of claim 20, wherein the at least one processor is included in the receiving device.

22. The system of claim 20, wherein the receiving device further comprises a baseband processor configured to provide the RFE-SI as a message to the sensing decision unit.

23. The system of claim 20, wherein the receiving device is further configured to provide the RFE-SI to the sensing decision unit as one or more digital signals.

24. The system of claim 20, wherein the receiving device is further configured to provide the RFE-SI to the sensing decision unit as one or more digital signals and one or more analog signals.

25. The system of claim 19, wherein the RFE-SI includes a phase change indicator.

26. The system of claim 25, wherein the instructions for determining the sensing decision input information include instructions for 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.

27. The system of claim 19, wherein the RFE-SI includes automatic gain controller (AGC) information.

28. The system of claim 27, wherein the instructions for determining the sensing decision input information include instructions for 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.

29. The system of claim 27, wherein the instructions for determining the sensory decision input information include instructions for:

The sensing decision input information is set as the P-CSI.

30. The system of claim 27, wherein the instructions for determining the sensory decision input information include instructions for:

The sensing decision output information is set as the P-CSI.

31. The system of claim 27, wherein the instructions for determining the sensory decision input information include instructions for:

32. The system of claim 19, wherein the RFE-SI includes downconverter type information.

33. The system of claim 32, wherein the instructions for determining the sensory decision input information include instructions for:

The sensing decision input information is set as the P-CSI.

34. The system of claim 29, wherein the at least one processor is further configured with instructions for sending the sensing decision input information to a sensing algorithm manager.

35. The system of claim 30, wherein the at least one processor is further configured with instructions for sending the sensing decision input information to a sensing algorithm manager.

36. The system of claim 33, wherein the at least one processor is further configured with instructions for sending the sensing decision input information to a sensing algorithm manager.