Crowd sensing using radio frequency sensing from multiple wireless nodes

Abstract

Techniques are provided for obtaining environmental information by one or more wireless devices using radio frequency sensing. An example method of crowd sensing and / or environmental detection using radio frequency sensing by one or more wireless devices includes providing radio frequency sensing assistance data to the one or more wireless devices, receiving a radio frequency sensing report from the one or more wireless devices, and determining one or more environmental characteristics based on the radio frequency sensing report. The environmental characteristics may include a location or movement of the one or more target objects, or an attribute of the one or more target objects (e.g., one or more persons, vehicles, animals, drones, or other target objects), or any combination thereof. This may help monitor people or road flow and / or identify and track specific people or vehicles.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of U.S. patent application No. 17 / 848,528, filed on June 24, 2022, entitled “CROWD SENSING USING RADIOFREQUENCY SENSING FROM MULTIPLE WIRELESS NODES,” which application is assigned to the assignee of this application, and the entire contents of which are incorporated herein by reference. Background Art

[0003] Wireless communication systems have evolved over many generations, including first generation analog wireless telephone service (1G), second generation (2G) digital wireless telephone service (including transitional 2.5G and 2.75G networks), third generation (3G) high speed data, Internet-enabled wireless services, fourth generation (4G) services (e.g., Long Term Evolution (LTE) or WiMax), fifth generation (5G) services, and the like. There are many different types of wireless communication systems in use today, including cellular and personal communications service (PCS) systems. Examples of known cellular systems include cellular analog Advanced Mobile Phone System (AMPS) and digital cellular systems based on code division multiple access (CDMA), frequency division multiple access (FDMA), time division multiple access (TDMA), global system for mobile communications (GSM) variants of TDMA, and the like.

[0004] The fifth-generation (5G) mobile standard calls for higher data speeds, more connections and better coverage, among other improvements. According to the Next Generation Mobile Networks Alliance, the 5G standard is designed to provide data rates of tens of megabits per second for each of tens of thousands of users and 1 gigabit per second for dozens of workers on an office floor. To support large sensor deployments, hundreds of thousands of simultaneous connections should be supported.

[0005] Various mobile RF standards like 4G, 5G, and WiFi (also known as Wi-Fi) can be used not only for communication, but also for determining characteristics of the local environment or nearby objects via RF sensing. Such non-communication uses can increase the benefits provided by mobile wireless devices, and therefore enhancements to these uses may be required. Summary of the invention

[0006] An example method for crowdsourcing radio frequency sensing data at a wireless device according to the present disclosure includes: receiving radio frequency sensing assistance data from a server; performing a radio frequency sensing operation based at least in part on the radio frequency sensing assistance data; and reporting radio frequency sensing results to the server.

[0007] Implementations of such methods may include one or more of the following features. Radio frequency sensing results may be used to determine one or more environmental characteristics. Radio frequency sensing results may be aggregated with multiple radio frequency sensing results received from multiple wireless devices, and one or more environmental characteristics may be determined based on the aggregation of radio frequency sensing results. One or more environmental characteristics may include movement of a target object, location of a target object, one or more attributes of a target object, or any combination thereof. One or more attributes of a target object may include horizontal position, altitude, speed, bearing, size, height, width, length, weight, type, brand, model, kind, orientation, posture, gait, clothing type, carrying of a bag or parcel, location area, density, quantity, rate of increase in quantity, rate of decrease in quantity, average speed, statistical direction of movement, or any combination thereof. Radio frequency sensing assistance data may include information related to at least one of movement, location, or any combination thereof of a target object. Radio frequency sensing assistance data may include information related to one or more attributes of a target object. Radio frequency sensing assistance data may include geographic information, and performing radio frequency sensing operations may be based at least in part on geographic information. The RF sensing assistance data may include RF signatures or attribute information associated with one or more potential target objects, and performing RF sensing operations is based at least in part on the RF signatures or attribute information. The RF sensing assistance data may be received via one or more radio resource control (RRC) messages or one or more IP messages or TCP / IP messages.

[0008] An example method for performing environmental detection at a server using radio frequency sensing according to the present disclosure includes: providing radio frequency sensing assistance data to one or more wireless devices; receiving one or more radio frequency sensing reports from one or more wireless devices; and determining one or more environmental characteristics based at least in part on the one or more radio frequency sensing reports.

[0009] Implementations of such methods may include one or more of the following features. Determining one or more environmental characteristics may include aggregating one or more radio frequency sensing reports. The one or more environmental characteristics may include movement of a target object, location of a target object, one or more attributes of a target object, or any combination thereof. The one or more attributes of a target object may include horizontal position, altitude, speed, orientation, size, height, width, length, weight, type, brand, model, kind, orientation, posture, gait, clothing type, carrying of a bag or parcel, location area, density, quantity, rate of increase in quantity, rate of decrease in quantity, average speed, statistical direction of movement, or any combination thereof. Radio frequency sensing assistance data may include information related to at least one of the movement, location, one or more attributes, or any combination thereof of a target object. Radio frequency sensing assistance data may include geographic information. Radio frequency sensing assistance data may include RF signature information, attribute information, or both associated with a potential target object. One or more radio frequency sensing reports may include sensor data obtained by one or more wireless devices. Radio frequency sensing assistance data may be provided via one or more radio resource control (RRC) messages or one or more IP or TCP / IP messages.

[0010] An example device according to the present disclosure includes: a memory; at least one transceiver; at least one processor, communicatively coupled to the memory and the at least one transceiver, and configured to: receive radio frequency sensing assistance data from a server; perform a radio frequency sensing operation based at least in part on the radio frequency sensing assistance data; and report radio frequency sensing results to the server.

[0011] An example apparatus according to the present disclosure may include: a memory; at least one transceiver; at least one processor, communicatively coupled to the memory and the at least one transceiver, and configured to: provide RF sensing assistance data to one or more wireless devices; receive one or more RF sensing reports from the one or more wireless devices; and determine one or more environmental characteristics based at least in part on the one or more RF sensing reports.

[0012] The items and / or technologies described herein may provide one or more of the following capabilities, as well as other capabilities not mentioned. Multiple wireless nodes may receive RF sensing assistance data from a network resource. The RF assistance data may enable multiple wireless nodes to jointly perform RF sensing operations. The wireless nodes may provide RF sensing results to a crowdsourcing server. The crowdsourcing server may be configured to construct a synthetic graph based on the RF sensing results. Characteristics (e.g., inferences) about crowds, traffic flow, or other object attributes may be drawn based on the synthetic graph. Crowd sensing may be achieved without dedicated sensors. Other capabilities may be provided, and not every embodiment according to the present disclosure must provide any of the capabilities discussed, let alone all of them. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 is a simplified diagram of an example wireless communication system.

[0014] Figure 2 is a block diagram of components of an example user device.

[0015] Figure 3 is a block diagram of the components of an example send / receive point.

[0016] Figure 4 is a block diagram of the components of a server.

[0017] Figure 5A is a schematic diagram of radio frequency sensing with concurrent transmission and reception by an example wireless device.

[0018] Figure 5B yes Figure 5A A graph of an example received signal in a wireless device.

[0019] Figure 6 is a diagram of an example use case for detecting crowds using radio frequency sensing.

[0020] Fig. 7A is a diagram of an example use case for detecting crowds using multiple wireless nodes configured for radio frequency sensing.

[0021] Figure 7B is a diagram of an example use case for improving detection of target objects using multiple wireless nodes configured for radio frequency sensing.

[0022] Fig. 8A is a diagram of an example use case of utilizing radio frequency sensing to detect stationary objects in a crowd.

[0023] Figure 8B is a diagram of an example use case for tracking a moving object using radio frequency sensing.

[0024] Figure 8C is an example message flow for performing crowd sensing using multiple wireless nodes.

[0025] Fig. 9 is an example directional diagram including the boresight direction of an object detected using radio frequency sensing.

[0026] Fig.10 is a graph of exemplary frequency-based components in radio frequency signal information.

[0027] Fig.11 is a graph of exemplary time-based components of RF signal information.

[0028] Fig.12is a graph of an example time and frequency response of a radio frequency sensing signal.

[0029] Fig.13 is an example data structure for crowdsourced RF sensing reports.

[0030] Fig.14A and Fig. 14B is a schematic diagram of a composite graph based on multiple RF sensing reports.

[0031] Fig.15 is an example flow chart of a method for determining properties of an object using radio frequency sensing.

[0032] Fig.16 is an example flow chart of a method for crowdsourcing radio frequency sensing data.

[0033] Fig.17 is an example flow chart of a method for performing environmental detection at a server using radio frequency sensing.

[0034] According to certain exemplary embodiments, the same reference numerals in the various drawings represent the same elements. In addition, in some cases, multiple instances of an element can be represented by adding letters after the first digit of the element. For example, multiple instances of element 110 can be indicated as 110a, 110b, etc. When only numbers are used to refer to the element, any instance of the element will be understood (for example, element 110 in the previous example will refer to elements 110a and 110b). DETAILED DESCRIPTION

[0035] Techniques for obtaining information related to an environment or one or more objects in an environment through RF sensing performed by multiple wireless-enabled devices are discussed herein. RF sensing performed by multiple wireless-enabled devices is referred to herein as crowd sensing, and may differ from traditional "crowd sourcing" in that information related to a crowd or collection of objects may be provided without requiring any active support from the collection of objects or the crowd itself or from any device associated with the crowd or collection of objects.

[0036] An example of crowd sensing is to obtain information about the crowd, such as the size of the crowd, the movement of the crowd, the rate at which the crowd increases or decreases. Other examples of crowd sensing are to obtain information about the traffic flow on the road or at the scene of the accident, or to identify and possibly track individuals in the crowd or separate vehicles on the road. For example, law enforcement officers, municipal planners, event organizers, retailers, stadium managers, etc. can use crowd information for emergency management, help and regulate pedestrian flow or traffic flow, business processes, and improve customer interfaces. Current crowd monitoring schemes may utilize costly imaging technology, artificial intelligence (AI), human observers, and additional sensors that may be extremely high in cost. The technology provided herein utilizes existing wireless nodes and devices to obtain crowd and environmental information, and therefore can be implemented at a fraction of the cost of existing schemes.

[0037] In one example, multiple wireless nodes (e.g., UEs) can perform radio frequency (RF) sensing operations and provide sensor data to a server. The RF sensing data can be obtained at a single location within a single time period, or over a period of time and / or at different locations. The sensor data can include RF sensor measurements obtained by sending RF signals (e.g., WiFi or 5G NR) and measuring signals reflected and / or scattered from surrounding objects. In one example, the sensor data can also include image data (e.g., images) from a camera and an infrared (IR) camera, which can be combined with the RF measurements. Additional sensors can enable detection of people, animals, and / or vehicles under many conditions, including at night, in the rain, and when there are intermediate objects (e.g., walls, buildings, trees, people).

[0038] In operation, an individual user equipment (UE) may be configured to report (e.g., periodically or when requested) sensor measurements obtained in the neighborhood of the UE. The report may include raw signal measurement data or features / inferences from the signal measurements (e.g., a map of people or vehicles detected near the UE or a 3D map of the area around the UE). The report may also include applicable timestamp and location information, such as the current location of the UE or measurements related to the UE location. Other UEs (e.g., near the UE) may be configured to obtain and report their sensor measurements. A crowdsourcing server may be configured to receive RF sensing reports from the UE and build a composite picture or map based on these reports (as well as the location of the UE and the time of the report). The crowdsourcing server or another network server may be configured to calculate environmental characteristics based on aggregated RF sensor reports. For example, characteristics about crowd size, crowd movement, traffic flow, or buildings may be obtained (e.g., building a floor plan for a building on fire). RF sensor signals may enable the detection of attributes of an object, and aggregated RF sensor reports may enable the network to track objects based on the attributes. For example, individual characteristics of a person or vehicle (e.g., person's height, weight, clothing, vehicle's length, width, height) can be determined in UE reports, and then the aggregated RF sensor reports can be used to track individual people or vehicles over a period of time based on the attributes. Compared to existing tracking schemes, the RF sensing techniques described herein can enable monitoring of target objects without requiring the target objects to send signals or be aware of the monitoring. Crowd sensing does not rely on every individual in the crowd having a UE to report their location. These techniques and configurations are examples, and other techniques and configurations may be used.

[0039] The following description provides examples and does not limit the scope, applicability or examples set forth in the claims. Without departing from the scope of the present disclosure, the functions and arrangements of the elements discussed may be changed. Various examples may appropriately omit, replace or add various processes or components. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted or combined. In addition, the features described with respect to some examples may be combined in other examples.

[0040] The description may relate to a sequence of actions performed, for example, by elements of a computing device. The various actions described herein may be performed by specific circuits (e.g., application specific integrated circuits (ASICs)), by program instructions executed by one or more processors, or by a combination of the two. The sequence of actions described herein may be implemented in a non-transitory computer-readable medium having a corresponding set of computer instructions stored therein, which, when executed, will cause an associated processor to perform the functions described herein. Thus, the various aspects described herein may be implemented in a variety of different forms, all of which are within the scope of the present disclosure including the claimed subject matter.

[0041] Unless otherwise specified, the terms "user equipment" (UE) and "base station" as used herein are not specific or otherwise limited to any specific radio access technology (RAT). Generally, such a UE can be any wireless communication device (e.g., mobile phone, router, tablet, laptop, consumer asset tracking device, Internet of Things (IoT) device, etc.) used by a user to communicate through a wireless communication network. The UE can be mobile or can be fixed (e.g., at certain times) and can communicate with a radio access network (RAN). The term "UE" as used herein can be interchangeably referred to as an "access terminal" or "AT", "client device", "wireless device", "user equipment", "user terminal (subscriber terminal)", "subscriber station", "user terminal (user terminal)" or UT, "mobile terminal", "mobile station", "mobile device" or its variants. Generally, the UE can communicate with the core network via the RAN, and through the core network, the UE can be connected to external networks (such as the Internet) and other UEs. Of course, for the UE, other mechanisms for connecting to the core network and / or the Internet are also possible, such as through a wired access network, a WiFi network (such as, based on IEEE 802.11, etc.), etc.

[0042] Depending on the network in which the base station is deployed, the base station may operate according to one of several RATs for communicating with the UE. Examples of base stations include access points (APs), network nodes, NodeBs, evolved NodeBs (eNBs), or new radio (NR) NodeBs (also known as gNodeBs or gNBs). In addition, in some systems, the base station may provide pure edge node signaling functions, while in other systems, additional control and / or network management functions may be provided.

[0043] The UE may be implemented by any of a variety of types of devices, including but not limited to a printed circuit (PC) card, a compact flash device, an external or internal modem, a wireless or wired phone, a smartphone, a tablet, a consumer asset tracking device, an asset tag, etc. The communication link through which the UE can send signals to the RAN is called an uplink channel (e.g., a reverse traffic channel, a reverse control channel, an access channel, etc.). The communication link through which the RAN can send signals to the UE is called a downlink or forward link channel (e.g., a paging channel, a control channel, a broadcast channel, a forward traffic channel, etc.). The term traffic channel (TCH) as used herein may refer to an uplink / reverse or downlink / forward traffic channel.

[0044] As used herein, the term "cell" or "sector" may correspond to one of a plurality of cells of a base station, or to the base station itself, depending on the context. The term "cell" may refer to a logical communication entity used to communicate with a base station (e.g., via a carrier), and may be associated with an identifier (e.g., a physical cell identifier (PCID), a virtual cell identifier (VCID)) used to distinguish adjacent cells operating via the same or different carriers. In some examples, a carrier may support multiple cells, and different cells may be configured according to different protocol types that may provide access to different types of devices (e.g., machine type communication (MTC), narrowband Internet of Things (NB-IoT), enhanced mobile broadband (eMBB), or other). In some examples, the term "cell" may refer to a portion of a geographic coverage area (e.g., a sector) over which the logical entity operates.

[0045] As used herein, the term "wireless node" includes a device configured to communicate on a wireless network. UE and base station are examples of wireless nodes. Specifically, a wireless node includes at least a radio frequency transmitter and a receiver (or transceiver), and can be configured to perform radio frequency sensing operations as described herein.

[0046] refer to Figure 1, an example of a communication system 100 includes UE 105, UE 106, a radio access network (RAN) 135, here a fifth generation (5G) next generation (NG) RAN (NG-RAN), and a 5G core network (5GC) 140. UE 105 and / or UE 106 may be, for example, an IoT device, a location tracker device, a cellular phone, a vehicle (e.g., a car, truck, bus, boat, etc.), or other device. A 5G network may also be referred to as a new radio (NR) network; NG-RAN 135 may be referred to as a 5G RAN or an NR RAN; and 5GC 140 may be referred to as an NG core network (NGC). RAN 135 may be another type of RAN, such as a 3G RAN, a 4G long term evolution (LTE) RAN, etc. UE 106 may be configured and coupled similarly to UE 105 to send signals to and / or receive signals from similar other entities in the communication system 100, but to simplify the drawings, such signaling is not shown. Figure 1 105. Similarly, for simplicity, the discussion focuses on UE 105. The communication system 100 can utilize information from a constellation 185 of satellite vehicles (SVs) 190, 191, 192, 193 of a satellite positioning system (SPS) (e.g., a global navigation satellite system (GNSS)), such as the Global Positioning System (GPS), the Global Navigation Satellite System (GLONASS), Galileo or BeiDou or some other local or regional SPS, such as the Indian Regional Navigation Satellite System (IRNSS), the European Geostationary Navigation Overlay Service (EGNOS), or the Wide Area Augmentation System (WAAS). Additional components of the communication system 100 are described below. The communication system 100 may include additional or alternative components.

[0047] like Figure 1As shown, the NG-RAN 135 includes NR nodeBs (gNBs) 110a, 110b and a next generation eNodeB (ng-eNB) 114, and the 5GC 140 includes an access and mobility management function (AMF) 115, a session management function (SMF) 117, a user plane function (UPF) 119, a location management function (LMF) 120, and a gateway mobile location center (GMLC) 125. The gNBs 110a, 110b, and ng-eNB 114 are communicatively coupled to each other, each configured for bidirectional wireless communication with the UE 105, and each is communicatively coupled to the AMF 115 and configured for bidirectional communication with the AMF 115. The gNBs 110a, 110b, and ng-eNB 114 may be referred to as base stations (BSs). AMF 115 , SMF 117 , LMF 120 , and GMLC 125 are communicatively coupled to one another, and the GMLC is communicatively coupled to an external client or server 130 .

[0048] UPF 119 may support voice and data bearers for UE 105 and may enable UE 105 to have voice and data access to other networks such as the Internet 121. UPF 119 may be connected to gNB 110 and ng-eNB 114. The functions of UPF 119 may include: external protocol data unit (PDU) session point interconnected with data networks, packet (e.g., Internet Protocol (IP)) routing and forwarding, user plane portion of packet inspection and policy rule enforcement, quality of service (QoS) processing of the user plane, downlink packet buffering, and downlink data notification triggering.

[0049] As shown, SMF 117 is connected to AMF 115 and UPF 119. SMF 117 may have the ability to control local and central UPFs in a PDU session. SMF 117 may manage the establishment, modification, and release of PDU sessions for UE 105, perform IP address allocation and management for UE 105, act as a Dynamic Host Configuration Protocol (DHCP) server for UE 105, and select and control UPF 119 on behalf of UE 105.

[0050] The external client or server 130 may be connected to the 5GC 140 via the GMLC 125. The external client or server 130 may also be connected to the 5GC 140 via the Internet 121. The external client or server 130 may directly ( Figure 1 1) or connected to UPF 119 via the Internet 121. The external client or server 130 may be a server, a network server or a user device such as a personal computer, UE, etc.

[0051] Base stations such as gNBs 110a, 110b, and / or ng-eNB 114 may each support a macro cell (e.g., for a high-power cellular base station) or a small cell (e.g., for a low-power cellular base station), or may act as an access point (e.g., for a short-range base station configured to communicate using a short-range technology such as WiFi, WiFi Direct (WiFi-D), Bluetooth, Bluetooth-Low Energy (BLE), Zigbee, etc.). One or more BSs, e.g., one or more of gNBs 110a, 110b, and / or ng-eNB 114, may be configured to communicate with UE 105 via multiple carriers. Each of gNBs 110a, 110b, and ng-eNB 114 may provide communication coverage for a corresponding geographic area (e.g., a cell). Each cell may be divided into a plurality of sectors based on the functionality of the base station antennas.

[0052] Figure 1 A general description of various components is provided, any or all of which may be used as appropriate, and each component may be duplicated or omitted as desired. Specifically, although one UE 105 is shown, many UEs (e.g., hundreds, thousands, millions, etc.) may be used in the communication system 100. Similarly, the communication system 100 may include a greater (or lesser) number of SVs (i.e., more or less than the four SVs 190-193 shown), gNBs 110a, 110b, ng-eNBs 114, AMFs 115, UPFs 119, external clients or servers 130, and / or other components. The connections shown to connect the various components in the communication system 100 include data and signaling connections, which may include additional (intermediate) components, direct or indirect physical and / or wireless connections, and / or additional networks. In addition, components may be rearranged, combined, separated, replaced, and / or omitted, depending on the desired functionality.

[0053] Although Figure 1 A 5G based network is shown, but similar network implementations and configurations may be used for other communication technologies such as 3G, Long Term Evolution (LTE). Gateway Mobile Location Center (GMLC) 125, Location Management Function (LMF) 120, Access and Mobility Management Function (AMF) 115, SMF 117, UPF 119, ng-eNB (eNodeB) 114, and gNB (gNodeB) 110a, 110b are examples and may be replaced or include various other location server functions and / or base station functions, respectively, in various embodiments.

[0054] The communication system 100 is capable of wireless communication because the components of the communication system 100 can communicate with each other (at least sometimes using wireless connections), directly or indirectly, for example, via gNB 110a, gNB 110b, ng-eNB 114, and / or network 140 (and / or one or more other devices not shown, such as one or more other base transceiver stations). For indirect communication, the communication can be changed during transmission from one entity to another, for example, to change header information of a data message, change the format, etc. The UE 105 can include multiple UEs and can be a mobile wireless communication device, but can communicate wirelessly and via a wired connection. The UE 105 can be any of a variety of devices, such as a smartphone, a tablet, a vehicle-based device, etc., but these are examples because the UE 105 need not be any of these configurations and other configurations of the UE can be used. Other UEs can include wearable devices (e.g., smart watches, smart jewelry, smart glasses or headphones, etc.). Other UEs, whether currently existing or developed in the future, can also be used. Further, other wireless devices (whether mobile or not) may be implemented within the communication system 100 and may communicate with each other and / or with the UE 105, gNB 110a, gNB 110b, ng-eNB 114, core network 140, and / or external clients or servers 130. For example, such other devices may include Internet of Things (IoT) devices, medical devices, home entertainment and / or automation devices, etc. The core network 140 may communicate with an external client or server 130 (e.g., a computer system), for example, to allow the external client or server 130 to request and / or receive location information about the UE 105 (e.g., via the GMLC 125).

[0055] UE 105 or other devices may be configured to communicate in various networks and / or for various purposes and / or using various technologies (e.g., 5G, Wi-Fi communication, multiple frequencies of Wi-Fi communication, satellite positioning, one or more types of communication (e.g., GSM, CDMA (code division multiple access), LTE (long term evolution), V2X (vehicle to pedestrian), V2I (vehicle to infrastructure), V2V (vehicle to vehicle), etc.), IEEE 802.11p, etc.). V2X communication may be cellular (cellular-V2X (C-V2X)) and / or WiFi (e.g., DSRC (dedicated short range communication)). The communication system 100 may support operation on multiple carriers (waveform signals of different frequencies). A multi-carrier transmitter may simultaneously transmit modulated signals on multiple carriers. Each modulated signal may be a code division multiple access (CDMA) signal, a time division multiple access (TDMA) signal, an orthogonal frequency division multiple access (OFDMA) signal, a single carrier frequency division multiple access (SC-FDMA) signal, etc. Each modulated signal may be sent on a different carrier and may carry pilot, overhead information, data, etc. The UEs 105, 106 may communicate with each other through UE-to-UE sidelink (SL) communications by transmitting on one or more sidelink channels, such as a physical sidelink synchronization channel (PSSCH), a physical sidelink broadcast channel (PSBCH), or a physical sidelink control channel (PSCCH).

[0056] UE 105 may include and / or may be referred to as a device, a mobile device, a wireless device, a mobile terminal, a terminal, a mobile station (MS), a terminal (SET) supporting secure user plane location (SUPL), or other names. In addition, UE 105 may correspond to a mobile phone, a smart phone, a laptop, a tablet, a PDA, a consumer asset tracking device, a navigation device, an Internet of Things (IoT) device, a health monitor, a security system, a smart city sensor, a smart meter, a wearable tracker, or some other portable or mobile device. Generally, although not necessarily, UE 105 can support wireless communications using one or more radio access technologies (RATs), such as Global System for Mobile Communications (GSM), Code Division Multiple Access (CDMA), Wideband CDMA (WCDMA), LTE, High Rate Packet Data (HRPD), IEEE 802.11 WiFi (also known as Wi-Fi), (BT), Worldwide Interoperability for Microwave Access (WiMAX), 5G New Radio (NR) (e.g., using NG-RAN 135 and 5GC 140), etc. UE 105 can support wireless communication using a wireless local area network (WLAN), which can be connected to other networks (e.g., the Internet) using, for example, a digital subscriber line (DSL) or a packet cable. The use of one or more of these RATs can allow UE 105 to communicate with an external client or server 130 (e.g., via UPF 119 or GMLC 125) and / or allow an external client or server 130 to receive location information about UE 105 (e.g., via GMLC 125) or RF sensing results from UE 105 (e.g., via UPF 119 and Internet 121).

[0057] UE 105 may include a single entity or may include multiple entities, such as in a personal area network, where a user may use audio, video and / or data I / O (input / output) devices, and / or body sensors and separate wired or wireless modems. The estimate of the location of UE 105 may be referred to as location, location estimate, location fix, fix, position, position estimate, or position fix, and may be geodetic, thereby providing location coordinates (e.g., latitude and longitude) of UE 105, which may or may not include an altitude component (e.g., height above sea level, height above ground level, floor level or basement level, or depth below ground level, floor level or basement level). Alternatively, the location of UE 105 may be represented as an urban location (e.g., as a postal address or a designation of a point or small area in a building (such as a specific room or floor)). The location of UE 105 can be expressed as an area or volume (defined geographically or in urban form) in which UE 105 is expected to be located with a certain probability or confidence level (e.g., 67%, 95%, etc.). The location of UE 105 can be expressed as a relative position, including, for example, a distance and direction from a known location. The relative position can be expressed as a relative coordinate (e.g., X, Y (and Z) coordinate) defined relative to a certain origin at a known location, which can be defined, for example, geographically, in urban terms, or by reference to a point, area, or volume indicated on a map, floor plan, or building plan. In the description contained herein, unless otherwise stated, the use of the term "location" may include any of these variants. When calculating the location of a UE, it is usually solved for local x, y, and possibly z coordinates, and then, if necessary, the local coordinates are converted to absolute coordinates (e.g., latitude, longitude, and altitude above or below mean sea level).

[0058] UE 105 may be configured to communicate with other entities using one or more of a variety of technologies. UE 105 may be configured to be indirectly connected to one or more communication networks via one or more device-to-device (D2D) peer-to-peer (P2P) links. D2D P2P links may be supported by any appropriate D2D radio access technology (RAT), such as LTE direct (LTE-D), WiFi direct (WiFi-D), Bluetooth, etc. One or more UEs in a group of UEs utilizing D2D communication may be within a geographic coverage area of ​​a transmit / receive point (TRP) such as one or more of gNB 110a, 110b and / or ng-eNB 114. Other UEs in such a group may be outside such geographic coverage area or may not be able to receive transmissions from the base station. Multiple groups of UEs communicating via D2D communication may utilize a one-to-many (1:M) system, in which each UE may transmit to other UEs in the group. TRPs may facilitate scheduling of resources for D2D communication. In other cases, D2D communication may be conducted between UEs without the involvement of a TRP. One or more UEs in a group of UEs utilizing D2D communications may be within the geographic coverage area of ​​a TRP. Other UEs in such a group may be outside such geographic coverage area or unable to receive transmissions from the base station. Groups of UEs communicating via D2D communications may utilize a one-to-many (1:M) system, where each UE may transmit to other UEs in the group. The TRP may facilitate the scheduling of resources for D2D communications. In other cases, D2D communications may be conducted between UEs without the involvement of a TRP.

[0059] Figure 1 The base stations (BS) in the NG-RAN 135 shown include NR Node Bs, referred to as gNBs 110a and 110b. The gNB 110a, 110b pair in the NG-RAN 135 may be connected to each other directly or via one or more other gNBs. Access to the 5G network is provided to the UE 105 via wireless communications between the UE 105 and one or more of the gNBs 110a, 110b, and one or more of the gNBs 110a, 110b may provide wireless communications access to the 5GC 140 on behalf of the UE 105 using 5G. Figure 1 In the example, it is assumed that the serving gNB for UE 105 is gNB 110a, but if UE 105 moves to another location, another gNB (e.g., gNB 110b) may be used as the serving gNB, or may be used as a secondary gNB to provide additional throughput and bandwidth to UE 105.

[0060] Figure 1The base stations (BSs) in the illustrated NG-RAN 135 may include ng-eNB 114, also referred to as next generation evolved Node B. The ng-eNB 114 may be connected to one or more of the gNBs 110a, 110b in the NG-RAN 135, possibly via one or more other gNBs and / or one or more other ng-eNBs. The ng-eNB 114 may provide LTE radio access and / or evolved LTE (eLTE) to the UE 105.

[0061] The gNBs 110a, 110b, and / or the ng-eNB 114 may each include one or more TRPs. For example, each sector within a cell of a BS may include a TRP, but multiple TRPs may share one or more components (e.g., a shared processor but with separate antennas). The communication system 100 may exclusively include a macro TRP, or the communication system 100 may have different types of TRPs, such as a macro TRP, a pico TRP, and / or a femto TRP, etc. A macro TRP may cover a relatively large geographic area (e.g., a radius of several kilometers) and may allow unrestricted access to terminals with service subscriptions. A pico TRP may cover a relatively small geographic area (e.g., a pico cell) and may allow unrestricted access to terminals subscribed to the service. A femto or home TRP may cover a relatively small geographic area (e.g., a femto cell) and may allow restricted access to terminals associated with a femto cell (e.g., terminals of users in a home).

[0062] As mentioned above, although Figure 1 Nodes configured to communicate according to a 5G communication protocol are shown, but nodes configured to communicate according to other communication protocols (such as an LTE protocol or an IEEE 802.11x protocol) may be used. For example, in an evolved packet system (EPS) that provides LTE wireless access to UE 105, the RAN may include an evolved universal mobile telecommunications system (UMTS) terrestrial radio access network (E-UTRAN), which may include base stations, including evolved Node Bs (eNBs). The core network for the EPS may include an evolved packet core (EPC). The EPS may include the E-UTRAN and the EPC, where the E-UTRAN corresponds to the UE 105. Figure 1 The NG-RAN 135 in the network and the EPC corresponds to the 5GC 140.

[0063] The gNBs 110a, 110b, and ng-eNB 114 may communicate with the AMF 115, which, for positioning functions, communicates with the LMF 120. The AMF 115 may support mobility of the UE 105, including cell changes and handovers, and may participate in supporting signaling connections to the UE 105 and possible data and voice bearers for the UE 105. For example, the LMF 120 may communicate directly with the UE 105, or directly with the gNBs 110a, 110b, and / or ng-eNB 114, via wireless communications. When the UE 105 accesses the NG-RAN 135, the LMF 120 may support positioning of the UE 105 and may support positioning procedures / methods such as Assisted GNSS (A-GNSS), Time Difference of Arrival (TDOA) (e.g., Downlink TDOA (DL-TDOA) or Uplink TDOA (UL-TDOA)), Round Trip Time (RTT), Multi-cell RTT, Real-Time Kinematics (RTK), Precise Point Positioning (PPP), Differential GNSS (DGNSS), Enhanced Cell ID (E-CID), Angle of Arrival (AoA), Angle of Departure (AoD), and / or other positioning methods. The LMF 120 may process location service requests for the UE 105, such as location service requests received from the AMF 115 or the GMLC 125. A node / system implementing the LMF 120 may additionally or alternatively implement other types of location support modules, such as an Enhanced Serving Mobile Location Center (E-SMLC) or a Secure User Plane Location (SUPL) Location Platform (SLP). At least part of the positioning functionality (including deriving the location of UE 105) may be performed at UE 105 (e.g., using signal measurements obtained by UE 105 of signals transmitted by wireless nodes such as gNB 110a, 110b and / or ng-eNB 114, and / or assistance data provided to UE 105, for example, by LMF 120). AMF 115 may serve as a control node for handling signaling between UE 105 and core network 140, and may provide QoS (Quality of Service) flow and session management. AMF 115 may support mobility of UE 105, including cell changes and handovers, and may participate in supporting signaling connections to UE 105.

[0064] The GMLC 125 may support location requests for the UE 105 received from an external client or server 130, and may forward such location requests to the AMF 115 for forwarding by the AMF 115 to the LMF 120, or may forward the location requests directly to the LMF 120. A location response (e.g., containing a location estimate for the UE 105) from the LMF 120 may be returned to the GMLC 125 directly or via the AMF 115, and the GMLC 125 may then return the location response (e.g., containing a location estimate) to the external client or server 130. The GMLC 125 is shown as being connected to the AMF 115 and the LMF 120, but may not be connected to the AMF 115 or the LMF 120 in some embodiments.

[0065] like Figure 1 As further shown in FIG. 1 , LMF 120 may communicate with gNB 110a, 110b, and / or ng-eNB 114 using a New Radio Positioning Protocol A (NRPPa), which may be defined in Technical Specification (TS) 38.455 defined by the Third Generation Partnership Project (3GPP). NRPPa messages may be transmitted between gNB 110a (or gNB 110b) and LMF 120, and / or between ng-eNB 114 and LMF 120 via AMF 115. Figure 1 As further shown in , the LMF 120 and the UE 105 may communicate using the LTE Positioning Protocol (LPP), which may be defined in 3GPP TS 37.355. Here, LPP messages may be transmitted between the UE 105 and the LMF 120 via the AMF 115 and the serving gNB 110a, 110b or the serving ng-eNB 114 for the UE 105. For example, the LPP messages may be transmitted between the LMF 120 and the AMF 115 using the Hypertext Transfer Protocol (HTTP), and may be transmitted between the AMF 115 and the UE 105 using the 5G Non-Access Stratum (NAS) protocol. The LPP protocol may be used to support positioning of the UE 105 using UE-assisted and / or UE-based positioning methods such as A-GNSS, RTK, DL-TDOA, and / or E-CID. The NRPPa protocol can be used to support positioning of UE 105 using network-based positioning methods such as UL-TDOA and E-CID (e.g., when used with measurements obtained by gNB 110a, 110b, or ng-eNB 114), and / or can be used by LMF 120 to obtain location-related information from gNB 110a, 110b, and / or ng-eNB 114, such as parameters defining downlink (DL) signals sent from gNB 110a, 110b, and / or ng-eNB 114.

[0066] Using the UE-assisted positioning method, the UE 105 can obtain location measurements and send the measurements to a location server (e.g., LMF 120) for calculating a location estimate of the UE 105. For example, the location measurements can include one or more of received signal strength indication (RSSI), round-trip signal propagation time (RTT), reference signal time difference (RSTD), reference signal received power (RSRP), and / or reference signal received quality (RSRQ) of the gNB 110a, 110b, ng-eNB 114, and / or WLAN AP. The location measurements can also or alternatively include measurements of GNSS pseudoranges, code phases, and / or carrier phases of the SVs 190-193.

[0067] Using the UE-based positioning method, UE 105 can obtain position measurements (e.g., which can be the same or similar to the position measurements of the UE-assisted positioning method), and the position of UE 105 can be calculated (e.g., with the help of auxiliary data received from a location server such as LMF 120 or broadcast by gNB 110a, 110b, ng-eNB 114 or other base stations or APs).

[0068] Using network-based positioning methods, one or more base stations (e.g., gNB 110a, 110b and / or ng-eNB 114) or APs may obtain location measurements (e.g., measurements of RSSI, RTT, RSRP, RSRQ, or time of arrival (ToA) of signals sent by UE 105) and / or may receive measurements obtained by UE 105. One or more base stations or APs may send the measurements to a location server (e.g., LMF 120) for use in computing a location estimate for UE 105.

[0069] The LPP message sent from the LMF 120 to the UE 105 may instruct the UE 105 to do any of a variety of things depending on the desired functionality. For example, the LPP message may contain instructions for the UE 105 to obtain measurements of GNSS (or A-GNSS), WLAN, E-CID, and / or DL-TDOA (or some other positioning method). In the case of E-CID, the LPP message may instruct the UE 105 to obtain one or more measurements (e.g., beam ID, beam width, average angle, RSRP, RSRQ measurements) of directional signals transmitted within a particular cell supported by one or more of the gNBs 110a, 110b, and / or ng-eNBs 114 (or supported by some other type of base station such as an eNB or WiFi AP). The UE 105 may send the measurements back to the LMF 120 in an LPP message (e.g., within a 5G NAS message) via the serving gNB 110a (or serving ng-eNB 114) and the AMF 115.

[0070] As described above, although the communication system 100 is described with respect to 5G technology, the communication system 100 may be implemented to support other communication technologies, such as GSM, WCDMA, LTE, etc., which are used to support and interact with mobile devices such as UE 105 (e.g., implement voice, data, positioning, and other functions). In some such embodiments, the 5GC 140 may be configured to control different air interfaces. For example, the 5GC 140 may use the non-3GPP interworking function (N3IWF, Figure 1 115). For example, the WLAN may support IEEE 802.11 WiFi access for the UE 105 and may include one or more WiFi APs. Here, the N3IWF may be connected to the WLAN and other elements in the 5GC 140, such as the AMF 115. In some embodiments, both the NG-RAN 135 and the 5GC 140 may be replaced by one or more other RANs and one or more other core networks. For example, in the EPS, the NG-RAN 135 may be replaced by an E-UTRAN including an eNB, and the 5GC 140 may be replaced by an EPC including a mobility management entity (MME) replacing the AMF 115, an E-SMLC replacing the LMF 120, and a GMLC that may be similar to the GMLC 125.

[0071] Also refer to Figure 2UE 200 is an example of one of UEs 105, 106, and includes a computing platform including a processor 210, a memory 211 including software (SW) 212, one or more sensors 213, a transceiver interface 214 for a transceiver 215 (including a wireless transceiver 240 and a wired transceiver 250), a user interface 216, a satellite positioning system (SPS) receiver 217, a camera 218, and a positioning device (PD) 219. The processor 210, the memory 211, the (multiple) sensors 213, the transceiver interface 214, the user interface 216, the SPS receiver 217, the camera 218, and the positioning device 219 may be communicatively coupled to each other via a bus 220 (which may be configured, for example, for optical and / or electrical communication). One or more of the illustrated devices (e.g., one or more of the camera 218, the positioning device 219, and / or the sensor 213, etc.) may be omitted from UE 200. The processor 210 may include one or more intelligent hardware devices, such as a central processing unit (CPU), a microcontroller, an application specific integrated circuit (ASIC), etc. The processor 210 may include multiple processors, including a general / application processor 230, a digital signal processor (DSP) 231, a modem processor 232, a video processor 233, and / or a sensor processor 234. One or more of the processors 230-234 may include multiple devices (e.g., multiple processors). For example, the sensor processor 234 may include, for example, a processor for RF (radio frequency) sensing (using one or more transmitted (cellular) wireless signals and (multiple) reflections for identifying, mapping and / or tracking objects) and / or ultrasound, etc. The radio modem processor 232 may support dual SIM / dual connections (or even more SIMs). For example, a SIM (subscriber identity module or subscriber identification module) may be used by an original equipment manufacturer (OEM), and another SIM may be used by an end user of the UE 200 for connection. The memory 211 is a non-transitory storage medium, which may include a random access memory (RAM), a flash memory, a disk memory, and / or a read-only memory (ROM), etc. The memory 211 stores software 212, which may be processor-readable, processor-executable software code containing instructions that are configured to, when executed, cause the processor 210 to perform various functions described herein. Alternatively, the software 212 may not be directly executed by the processor 210, but may be configured to, for example, cause the processor 210 to perform these functions when compiled and executed. The description may refer to the processor 210 performing functions, but this includes other embodiments, such as the processor 210 executing software and / or firmware. The description may refer to the processor 210 performing a function as a shorthand for one or more of the processors 230 to 234 that perform the function.The description may refer to the UE 200 performing a function as shorthand for one or more appropriate components of the UE 200 performing the function. The processor 210 may include a memory having stored instructions in addition to and / or in lieu of the memory 211. The functionality of the processor 210 will be discussed more fully below.

[0072] Figure 2 The configuration of UE 200 shown in the is an example and does not limit the present disclosure including the claims, and other configurations may be used. For example, an example configuration of the UE includes one or more of the processors 230-234 of the processor 210, the memory 211, and the wireless transceiver 240. Other example configurations include one or more of the processors 230-234 of the processor 210, the memory 211, the wireless transceiver, and one or more of the sensor 213, the user interface 216, the SPS receiver 217, the camera 218, the PD 219, and / or the wired transceiver.

[0073] The UE 200 may include a modem processor 232 capable of performing baseband processing on signals received and down-converted by the transceiver 215 and / or the SPS receiver 217. The modem processor 232 may perform baseband processing on signals to be up-converted for transmission by the transceiver 215. Additionally or alternatively, the baseband processing may be performed by the general processor 230 and / or the DSP 231. However, other configurations may be used to perform baseband processing.

[0074] UE 200 may include sensor(s) 213, which may include, for example, one or more sensors of various types, such as one or more inertial sensors, one or more magnetometers, one or more environmental sensors, one or more optical sensors, one or more weight sensors, and / or one or more radio frequency (RF) sensors, etc. An inertial measurement unit (IMU) may include, for example, one or more accelerometers (e.g., collectively responsive to acceleration of UE 200 in three dimensions) and / or one or more gyroscopes (e.g., (multiple) three-dimensional gyroscopes). Sensor 213 may include one or more magnetometers (e.g., (multiple) three-dimensional magnetometers) to determine orientation (e.g., relative to magnetic north and / or true north), which may be used for any of a variety of purposes, such as supporting one or more compass applications. Environmental sensor(s) may include, for example, one or more temperature sensors, one or more atmospheric pressure sensors, one or more ambient light sensors, one or more camera imagers, an IR camera, and / or one or more microphones, etc. Sensor(s) 213 may generate analog and / or digital signals indicative thereof, which may be stored in memory 211 and processed by DSP 231 and / or general purpose processor 230 to support one or more applications, such as applications for positioning and / or navigation operations.

[0075] The (multiple) sensors 213 may be used for relative position measurement, relative position determination, motion determination, etc. The information detected by the (multiple) sensors 213 may be used for motion detection, relative displacement, dead reckoning, sensor-based position determination, and / or sensor-assisted position determination. The (multiple) sensors 213 may be used to determine whether the UE 200 is fixed (stationary) or moving, and / or whether to report certain useful information about the mobility of the UE 200 to the LMF 120. For example, based on the information obtained / measured by the (multiple) sensors 213, the UE 200 may notify / report to the LMF 120 that the UE 200 has detected movement or that the UE 200 has moved, and report the relative displacement / distance (e.g., via dead reckoning, sensor-based position determination, sensor-assisted position determination implemented by the (multiple) sensors 213). In another example, for relative positioning information, the sensor / IMU may be used to determine the angle and / or orientation of other devices relative to the UE 200, etc.

[0076] The IMU may be configured to provide measurements of the direction of motion and / or speed of motion of the UE 200, which may be used for relative position determination. For example, one or more accelerometers and / or one or more gyroscopes of the IMU may detect the linear acceleration and rotational speed of the UE 200, respectively. The linear acceleration and rotational speed measurements of the UE 200 may be integrated over time to determine the instantaneous direction of motion and displacement of the UE 200. The instantaneous direction and displacement of motion may be integrated to track the position of the UE 200. For example, a reference position of the UE 200 may be determined at a time, for example, using the SPS receiver 217 (and / or by some other means), and the measurements of the (multiple) accelerometers and (multiple) gyroscopes obtained after that time may be used in dead reckoning to determine the current position of the UE 200 based on the movement (direction and distance) of the UE 200 relative to the reference position.

[0077] The magnetometer(s) may determine the magnetic field strength in different directions, which may be used to determine the orientation of the UE 200. For example, the orientation may be used to provide a digital compass for the UE 200. The magnetometer(s) may include a two-dimensional magnetometer configured to detect and provide an indication of the magnetic field strength in two orthogonal dimensions. The magnetometer(s) may include a three-dimensional magnetometer configured to detect and provide an indication of the magnetic field strength in three orthogonal dimensions. The magnetometer(s) may provide a component for sensing a magnetic field and providing an indication of the magnetic field to, for example, the processor 210.

[0078] The transceiver 215 may include a wireless transceiver 240 and a wired transceiver 250, which are configured to communicate with other devices via wireless connections and wired connections, respectively. For example, the wireless transceiver 240 may include a wireless transmitter 242 and a wireless receiver 244 coupled to one or more antennas 246 for transmitting (e.g., on one or more uplink channels and / or one or more sidelink channels) and / or receiving (e.g., on one or more downlink channels and / or one or more sidelink channels) wireless signals 248, and converting signals from the wireless signals 248 to wired (e.g., electrical and / or optical) signals, and from wired (e.g., electrical and / or optical) signals to the wireless signals 248. For example, the one or more antennas 246 may include two (dual) antennas, four (quad) antennas, or an antenna array to achieve directional transmission and / or directional reception of RF sensing signals. Thus, the wireless transmitter 242 may include multiple transmitters, which may be discrete components or combined / integrated components, and / or the wireless receiver 244 may include multiple receivers, which may be discrete components or combined / integrated components. The wireless transceiver 240 may be configured to communicate signals (e.g., with the TRP and / or one or more other devices) according to various radio access technologies (RATs), such as 5G New Radio (NR), GSM (Global System for Mobile Communications), UMTS (Universal Mobile Telecommunications System), AMPS (Advanced Mobile Phone System), CDMA (Code Division Multiple Access), WCDMA (Wideband CDMA), LTE (Long Term Evolution), LTE Direct (LTE-D), 3GPP LTE-V2X (PC5), IEEE 802.11 (including IEEE 802.11p), WiFi, WiFi Direct (WiFi-D), Zigbee, etc. The new radio may use millimeter wave frequencies and / or sub-6 GHz frequencies. The wired transceiver 250 may include a wired transmitter 252 and a wired receiver 254 configured for wired communication, for example, a network interface that may be used to communicate with the NG-RAN 135 to send communications to and receive communications from the NG-RAN 135. The wired transmitter 252 may include multiple transmitters that may be discrete components or combined / integrated components, and / or the wired receiver 254 may include multiple receivers that may be discrete components or combined / integrated components. The wired transceiver 250 may be configured for, for example, optical communication and / or electrical communication. The transceiver 215 may be communicatively coupled to the transceiver interface 214, for example, via an optical and / or electrical connection. The transceiver interface 214 may be at least partially integrated with the transceiver 215.

[0079] The transceiver 215 may be configured to send and receive other types of signals. For example, the transceiver 215 may be configured to send and receive radar, sonar, ultrasound, and / or lidar signals under the control of the sensor processor 234. The wireless transmitter 242, the wireless receiver 244, and / or the antenna 246 may include multiple transmitters, multiple receivers, and / or multiple antennas, respectively, for sending and / or receiving appropriate signals, respectively.

[0080] The user interface 216 may include one or more of several devices, such as a speaker, a microphone, a display device, a vibration device, a keyboard, a touch screen, etc. The user interface 216 may include more than one of these devices. The user interface 216 may be configured to enable a user to interact with one or more applications hosted by the UE 200. For example, the user interface 216 may store indications of analog and / or digital signals in the memory 211 to be processed by the DSP 231 and / or the general processor 230 in response to actions from the user. Similarly, the application hosted on the UE 200 may store indications of analog and / or digital signals in the memory 211 to present output signals to the user. The user interface 216 may include an audio input / output (I / O) device, including, for example, a speaker, a microphone, a digital-to-analog circuit, an analog-to-digital circuit, an amplifier, and / or a gain control circuit (including more than one of these devices). Other configurations of the audio I / O device may be used. In addition or alternatively, the user interface 216 may include one or more touch sensors, which respond to, for example, touch and / or pressure on a keyboard and / or a touch screen of the user interface 216.

[0081] The SPS receiver 217 (e.g., a global positioning system (GPS) receiver) is capable of receiving and capturing SPS signals 260 via an SPS antenna 262. The antenna 262 is configured to convert the wireless SPS signal 260 into a wired signal, such as an electrical signal or an optical signal, and may be integrated with the antenna 246. The SPS receiver 217 may be configured to process the captured SPS signal 260 in whole or in part to estimate the position of the UE 200. For example, the SPS receiver 217 may be configured to determine the position of the UE 200 by trilateration using the SPS signal 260. The general processor 230, the memory 211, the DSP 231, and / or one or more dedicated processors (not shown) may be used in conjunction with the SPS receiver 217 to process the captured SPS signal in whole or in part, and / or calculate an estimated position of the UE 200. The memory 211 may store indications (e.g., measurements) of the SPS signal 260 and / or other signals (e.g., signals captured from the wireless transceiver 240) for performing positioning operations. The general purpose processor 230 , the DSP 231 , and / or one or more dedicated processors and / or the memory 211 may provide or support a location engine for processing measurements to estimate the location of the UE 200 .

[0082] UE 200 may include a camera 218 for capturing still or moving images. Camera 218 may include, for example, an imaging sensor (e.g., a charge coupled device or CMOS imager), a lens, an analog-to-digital conversion circuit, a frame buffer, etc. General processor 230 and / or DSP 231 may perform additional processing, conditioning, encoding, and / or compression on a signal representing a captured image. In addition or alternatively, video processor 233 may perform conditioning, encoding, compression, and / or manipulation on a signal representing a captured image. Video processor 233 may decode / decompress stored image data for presentation on a display device (not shown) such as user interface 216.

[0083] The positioning device (PD) 219 may be configured to determine the location of the UE 200, the movement of the UE 200, and / or the relative location and / or time of the UE 200. For example, the PD 219 may communicate with the SPS receiver 217, and / or include some or all of the SPS receiver 217. The PD 219 may work appropriately in conjunction with the processor 210 and the memory 211 to perform at least a portion of one or more positioning methods, but the description herein may involve the PD 219 being configured to perform or being performed according to (multiple) positioning methods. In addition or alternatively, the PD 219 may be configured to determine the position of the UE 200 using ground-based signals (e.g., at least some of the signals 248) for trilateration, for assisting in obtaining and using the SPS signals 260, or for both. The PD 219 may be configured to determine the location of the UE 200 using one or more other techniques (e.g., relying on the UE's self-reported location (e.g., part of the UE's location beacon)), and may use a combination of techniques (e.g., SPS and ground positioning signals) to determine the location of the UE 200. The PD 219 may include one or more of the sensors 213 (e.g., (multiple) gyroscopes, (multiple) accelerometers, (multiple) magnetometers, etc.), which may sense the orientation and / or motion of the UE 200 and provide an indication thereof, and the processor 210 (e.g., the general processor 230 and / or the DSP 231) may be configured to determine the motion of the UE 200 (e.g., velocity vector and / or acceleration vector). The PD 219 may be configured to provide an indication of uncertainty and / or error in the determined positioning and / or motion. The functionality of PD 219 may be provided in various ways and / or configurations, for example, by general / application processor 230, transceiver 215, SPS receiver 217, and / or another component of UE 200, and may be provided by hardware, software, firmware, or various combinations thereof.

[0084] Also refer to Figure 3, an example of a TRP 300 for gNB 110a, 110b, and / or ng-eNB 114 includes a computing platform including a processor 310, a memory 311 including software (SW) 312, and a transceiver 315. The processor 310, the memory 311, and the transceiver 315 may be communicatively coupled to each other via a bus 320 (which may be configured for, for example, optical and / or electrical communication). One or more of the illustrated devices (e.g., wireless interfaces) may be omitted from the TRP 300. The processor 310 may include one or more intelligent hardware devices, such as a central processing unit (CPU), a microcontroller, an application specific integrated circuit (ASIC), etc. The processor 310 may include a plurality of processors (e.g., including a general / application processor, a DSP, a modem processor, a video processor, and / or a sensor processor, such as Figure 2 ). The memory 311 is a non-transitory storage medium, which may include a random access memory (RAM), a flash memory, a disk memory, and / or a read-only memory (ROM), etc. The memory 311 stores software 312, which may be a processor-readable, processor-executable software code, which contains instructions, which are configured to, when executed, cause the processor 310 to perform the various functions described herein. Alternatively, the software 312 may not be directly executed by the processor 310, but may be configured to, for example, cause the processor 310 to perform these functions when compiled and executed.

[0085] The description may refer to the processor 310 performing functions, but this includes other embodiments, such as the processor 310 executing software and / or firmware. The description may refer to the processor 310 performing functions as shorthand for one or more of the processors included in the processor 310 that perform the functions. The description may refer to the TRP 300 performing functions as shorthand for one or more appropriate components (e.g., processor 310 and memory 311) of the TRP 300 (and therefore one of the gNBs 110a, 110b and / or ng-eNB 114) that perform the functions. The processor 310 may include a memory having stored instructions in addition to and / or in lieu of the memory 311. The functionality of the processor 310 will be discussed more fully below.

[0086] The transceiver 315 may include a wireless transceiver 340 and a wired transceiver 350, which are configured to communicate with other devices via wireless connections and wired connections, respectively. For example, the wireless transceiver 340 may include a wireless transmitter 342 and a wireless receiver 344 coupled to one or more antennas 346 for transmitting (e.g., on one or more uplink channels and / or one or more downlink channels) and / or receiving (e.g., on one or more downlink channels and / or one or more uplink channels) wireless signals 348, and converting signals from the wireless signals 348 to wired (e.g., electrical and / or optical) signals, and converting signals from the wired (e.g., electrical and / or optical) signals to the wireless signals 348. Thus, the wireless transmitter 342 may include multiple transmitters that may be discrete components or combined / integrated components, and / or the wireless receiver 344 may include multiple receivers that may be discrete components or combined / integrated components. The wireless transceiver 340 may be configured to communicate signals (e.g., with the UE 200, one or more other UEs, and / or one or more other devices) in accordance with various radio access technologies (RATs), such as 5G New Radio (NR), GSM (Global System for Mobile Communications), UMTS (Universal Mobile Telecommunications System), AMPS (Advanced Mobile Phone System), CDMA (Code Division Multiple Access), WCDMA (Wideband CDMA), LTE (Long Term Evolution), LTE Direct (LTE-D), 3GPP LTE-V2X (PC5), IEEE 802.11 (including IEEE 802.11p), WiFi, WiFi Direct (WiFi-D), Zigbee, etc. The wired transceiver 350 may include a wired transmitter 352 and a wired receiver 354 configured for wired communication, for example, a network interface that can be used to communicate with the NG-RAN 135 to send and receive communications to, for example, the LMF 120 and / or one or more other network entities. The wired transmitter 352 may include multiple transmitters that may be discrete components or combined / integrated components, and / or the wired receiver 354 may include multiple receivers that may be discrete components or combined / integrated components. The wired transceiver 350 may be configured for, for example, optical communication and / or electrical communication.

[0087] Figure 3 The configuration of the TRP 300 shown in the is an example and does not limit the present disclosure, including the claims, and other configurations may be used. For example, the description herein discusses that the TRP 300 is configured to perform several functions, but one or more of these functions may be performed by the LMF 120 and / or the UE 200 (i.e., the LMF 120 and / or the UE 200 may be configured to perform one or more of these functions).

[0088] Also refer to Figure 4 , the server 400 (LMF 120 is an example thereof) includes a computing platform including a processor 410, a memory 411 including software (SW) 412, and a transceiver 415. The processor 410, the memory 411, and the transceiver 415 may be communicatively coupled to each other via a bus 420 (which may be configured for, for example, optical and / or electrical communication). One or more of the devices shown (e.g., wireless interfaces) may be omitted from the server 400. The processor 410 may include one or more intelligent hardware devices, such as a central processing unit (CPU), a microcontroller, an application specific integrated circuit (ASIC), etc. The processor 410 may include a plurality of processors (e.g., including a general / application processor, a DSP, a modem processor, a video processor, and / or a sensor processor, such as Figure 2 410). The memory 411 is a non-temporary storage medium, which may include random access memory (RAM), flash memory, disk memory and / or read-only memory (ROM), etc. The memory 411 stores software 412, which may be a processor-readable, processor-executable software code, which contains instructions, which are configured to, when executed, cause the processor 410 to perform the various functions described herein. Alternatively, the software 412 may not be directly executed by the processor 410, but may be configured to, for example, cause the processor 410 to perform these functions when compiled and executed. The description may involve the processor 410 performing functions, but this includes other embodiments, such as the processor 410 executing software and / or firmware. The description may refer to the processor 410 performing a function as a shorthand for one or more of the processors included in the processor 410 performing the function. The description may refer to the server 400 performing a function as a shorthand for one or more appropriate components of the server 400 performing the function. In addition to and / or in place of the memory 411, the processor 410 may include a memory having stored instructions. The functions of the processor 410 will be discussed more fully below.

[0089] The transceiver 415 may include a wireless transceiver 440 and a wired transceiver 450, which are configured to communicate with other devices via wireless connections and wired connections, respectively. For example, the wireless transceiver 440 may include a wireless transmitter 442 and a wireless receiver 444 coupled to one or more antennas 446 for transmitting (e.g., on one or more uplink channels) and / or receiving (e.g., on one or more uplink channels) wireless signals 448, and converting signals from the wireless signals 448 to wired (e.g., electrical and / or optical) signals, and from wired (e.g., electrical and / or optical) signals to the wireless signals 448. Thus, the wireless transmitter 442 may include multiple transmitters that may be discrete components or combined / integrated components, and / or the wireless receiver 444 may include multiple receivers that may be discrete components or combined / integrated components. The wireless transceiver 440 may be configured to transmit signals (e.g., with the UE 200, one or more other UEs, and / or one or more other devices) in accordance with various radio access technologies (RATs), such as 5G New Radio (NR), GSM (Global System for Mobile Communications), UMTS (Universal Mobile Telecommunications System), AMPS (Advanced Mobile Phone System), CDMA (Code Division Multiple Access), WCDMA (Wideband CDMA), LTE (Long Term Evolution), LTE Direct (LTE-D), 3GPP LTE-V2X (PC5), IEEE 802.11 (including IEEE 802.11p), WiFi, WiFi Direct (WiFi-D), Zigbee, etc. The wired transceiver 450 may include a wired transmitter 452 and a wired receiver 454 configured for wired communication, for example, a network interface that can be used to communicate with the NG-RAN 135 to send and receive communications to, for example, the TRP 300 and / or one or more other network entities. The wired transmitter 452 may include multiple transmitters that may be discrete components or combined / integrated components, and / or the wired receiver 454 may include multiple receivers that may be discrete components or combined / integrated components. The wired transceiver 450 may be configured for, for example, optical communication and / or electrical communication.

[0090] The description herein may refer to the processor 410 performing a function, but this includes other implementations, such as the processor 410 executing software (stored in the memory 411) and / or firmware. The description herein may refer to the server 400 performing a function as a shorthand for one or more appropriate components (e.g., the processor 410 and the memory 411) of the server 400 performing the function.

[0091] Figure 4The configuration of the server 400 shown is an example and does not limit the present disclosure including the claims, and other configurations may be used. For example, the wireless transceiver 440 may be omitted. In addition or alternatively, the description herein discusses that the server 400 is configured to perform several functions, but one or more of these functions may be performed by the TRP 300 and / or the UE 200 (i.e., the TRP 300 and / or the UE 200 may be configured to perform one or more of these functions).

[0092] refer to Figure 5A , shows an example diagram 500 of radio frequency sensing for simultaneous transmission and reception of a wireless device. A wireless device such as UE 200, UE 105, UE 106, or TRP 300 includes a transceiver 240 or transceiver 340 having multiple transmit and receive chains configured to simultaneously transmit and receive RF signals. Figure 5A The number of transmit and receive chains in is an example and not a limitation, because other transceivers and antenna configurations can be used. For example, the transceiver 240 can be configured for multiple input multiple output (MIMO) with two transmit chains and two receive chains. Other array sizes and configurations can be used. In one example, the transceiver 240 may include a transmit chain, which includes a transmit antenna 502 operably coupled to a transmit RF module 508. The transmit RF module 508 is configured to receive a signal from a digital-to-analog converter (DAC) 506 and transmit a corresponding RF signal via the transmit antenna 502. The signal can be generated by a processor such as a modem processor 232 and / or a general processor 230. The transceiver 240 may include one or more receive chains, and the one or more receive chains include a receive antenna 504, a receive RF module 516, and an analog-to-digital converter (ADC) 514. Additional receive modules such as a second receive chain 520 and a third receive chain 522 may also be used.

[0093] Typically, RF sensing uses one or more RF signals (e.g., WiFi signals or NR signals) including one or more waveforms, sequences, or packets to determine the presence and / or movement of an object. This can be accomplished by using the RF signal for channel acquisition, performing channel estimation to obtain a channel impulse response (CIR), a channel frequency response (CFR), and / or other forms of channel state information (CSI) indicating the presence and / or movement of an object. CSI indicates various aspects of the RF signal, such as multipath, reflection, and signal strength of each path. More broadly, CSI can represent, for example, the combined effects of one or more of reflection, scattering, fading, refraction, attenuation, and / or power attenuation with distance on the RF signal. According to some embodiments, channel estimation used in the form of a wireless communication system can be used to obtain CSI. (In wireless communications, CSI is used to correctly demodulate and decode received packets). Therefore, embodiments can utilize existing channel estimation techniques to obtain CSI for RF sensing purposes.

[0094] In operation, the wireless device may transmit a radio frequency signal 512a to a target 518. The reflected signal 512b is the portion of the RF signal 512a that is reflected (and / or diffracted or scattered) by the target 518 and received by one or more receiving antennas (such as the receiving antenna 504). As used herein, the terms target, target object, and object refer to a physical entity that can be detected using RF sensing. Additional receive chains may implement beamforming / direction detection so that the wireless device can calculate the angle of arrival (AoA) of the received signal. The receive chain may also receive transmission leakage 510 while transmitting the RF signal 512a. Depending on the configuration of the wireless device, the transmission leakage 510 may be conducted and / or radiated interference. For example, physical shielding may be used to reduce radiated interference between a transmitting antenna and a receiving antenna. In one embodiment, the radio frequency signal 512a may be a predefined sequence (also referred to as a "sequence") of length "L". The predefined sequence may be designed to have a cyclic autocorrelation property, such as a single-carrier Zadoff-Chu sequence, or an orthogonal frequency division multiplexing (OFDM)-like symbol.

[0095] The predefined sequence may be different from another predefined sequence used by another (e.g., nearby) wireless device to avoid receiving a transmission from another wireless device and mistaking it for a reflection of a predefined sequence sent by the wireless device. In an embodiment, the predefined sequence may be defined or encoded based on a unique characteristic of the wireless device, such as a global identification of the wireless device or a temporary identification of the wireless device provided by a service network such as 5GC 140. In other embodiments, some or all of the predefined sequences may be defined and provided to the wireless device by a service network (such as 5GC 140) or a server (such as an external client or server 130), which may provide or define different predefined sequences for each of multiple wireless devices that are close to each other. The predefined sequence may be repeated and sent "n" times in succession, so that the (multiple) receiving chains of the wireless device may start listening for a length "L" at a later time to receive the predefined sequence without losing signal information. This relaxed timing requirement on the receiving chains means that they do not have to start at the same time as the transmitter.

[0096] The receive RF module 516 (and the additional receive chains 520, 522) can monitor and receive "m" sequences instead of 1 sequence. For example, the receive RF module 516 can monitor a length of m*L, where "m" is the number of sequences captured by the receive RF module 516, and m<=n. The wireless device (e.g., UE 200) can combine the received "m" sequences to improve the signal-to-noise ratio (SNR). The received sequence can be used for RF sensing. For example, a known transmit sequence can be used to obtain a channel estimate based on a signal correlation technique. The channel estimate can be processed via an iterative elimination algorithm to detect leakage and reflections. The time difference between leakage and reflection can be used to estimate the distance to the target 518.

[0097] In one example, multiple Rx antennas such as additional receive chains 520, 522 can be used to receive (multiple) sequences in the reflected signal 512b, determine channel estimates, and obtain angle estimates of the reflected signal 512b. The UE typically has 2 to 4 antennas. The CSI received via different Rx antennas can be used to determine angle information (e.g., by using Rx beamforming, determining angle information phase difference, etc.). In some embodiments, an embodiment with two antennas can achieve an angle granularity of, for example, 10 degrees (10°) to 15°, and an embodiment with four antennas can achieve a granularity of 2° to 3°. In addition, in some other embodiments, the RF sensing system can have multiple Tx antennas (e.g., 2 to 4 antennas). The phase of the Tx antenna can be configured to send an RF signal with a beam pointing in a certain direction. In some embodiments, for example, an embodiment with two Tx antennas can achieve an angle granularity of 10° to 15°, and an embodiment with four Tx antennas can achieve a granularity of 2° to 3°. Changes in CSI over time (e.g., from one scan to the next) indicate motion of target 518. The changes may include changes in the amplitude or phase of the CSI. Additionally or alternatively, the changes may include changes in metrics extracted and / or estimated from the CSI, such as time of flight and the angle of each reflection path, etc. Thus, the RF signal can be used to determine properties of the target object, such as position, volume, and movement. In one example, classification algorithms and / or machine learning of the channel estimation results can be used to identify the type and / or size of motion of target 518. In one example, channel estimation can be used to detect changes in the orientation, size, shape, and / or posture of target 518.

[0098] Figure 5A The number of transmit and receive chains on a wireless device is an example and not a limitation. Other wireless devices may have multiple arrays, and each array may include a different number and pattern of antenna elements. For example, the antenna array may include a matrix of elements of 1×2, 1×4, 1×5, 1×8, 2×2, 2×4, 2×5, 2×8, 3×4, 3×5, 3×8, etc. Other antenna array matrix sizes may also be used.

[0099] In one embodiment, a wireless device having one or more multi-element antenna arrays may be configured to beamform the transmitted and received RF signals. For example, the transceiver 240 may include a radio frequency integrated circuit (RFIC) including a phase shifter to modify the transmit and receive beam gains. The wireless device may be configured to change the angle of departure (AoD) of the RF signal 512a. In one example, the RF signal 512a may be swept across different AoDs, and the gain of the corresponding reflected signal may be determined. Changing the AoD of the RF signal 512a may be used to determine the direct path to the target 518 (e.g., based on the highest reflected gain). In one example, beam scanning may be used to determine the changing orientation, size, shape, and / or pose of an object (e.g., based on a series of reflected signals over time). In one embodiment, the transmitted RF signal 512a may be a polarized signal, and the polarization of the received signal 512b may be detected. The polarization change between the transmitted signal and the received signal may be used to determine the characteristics of the target 518 and / or classify it.

[0100] In one example, the general processor 230 and / or the DSP 231 may be configured to determine the distance, speed, and / or size of the target object. The distance may be measured based on the pulse delay associated with the transmission of the RF signal 512a and the reception of the received signal 512b. The speed of the target object may be obtained based on the Doppler shift of the RF signal 512a when the reflection is received. The angular direction may be based on the AoD of the changing RF signal. Signature analysis and backscattering techniques known in the art may be used to detect other properties of the target object. For example, the size of the target object may be based on the amplitude of the received signal 512b, and the presence of a moving part on the target object may be based on the modulation of the received signal 512b.

[0101] refer to Figure 5B , and further reference Figure 5A, a graph 550 of an example received signal is shown. The graph 550 includes a relative power axis 552, a time axis 554, and a signal response function 556. The signal response function 556 represents the signal detected by the receiving antenna 504. The first peak 558 is based on the transmission leakage 510, and the second peak 560 is based on the reflected signal 512b. The RF module 516 (and other receiving chains 520, 522) can be configured to reduce the receiving gain during the transmission of the RF signal 512a. For example, one or more amplifier components (e.g., a low noise amplifier (LNA)) in the receiver can be configured with an adjustable gain function. The receiving gain can be reduced to mitigate the leakage effect on the receiving chain. Other iterative elimination algorithms can be used to reduce the effect of the first peak 558 and improve the detection of the second peak 560. The transmit gain of the RF transmit module 508 can be increased to improve the detection of the reflected signal 512b. For example, the transmit gain can be increased for each iteration in the sequence based on the value of one or more peaks associated with the reflected signal 512b.

[0102] In operation, the signal response function 556 includes the transmitted sequence, and the corresponding ADC capture in the ADC module 514 is equivalent to a channel capture, which can be used to implement channel capture based on the RF sensing use case. The time difference between the first peak 558 (i.e., the transmission time) and the second peak 560 (i.e., the reflected signal 512b) can be used to estimate the distance from the target 518. The AoA of the reflected signal 512b can be obtained based on ADC capture from multiple antennas (e.g., additional receiving chains 520, 522). The measured distance and direction information from the target 518 can be used for indoor mapping applications. The bandwidth of the transmitted RF signal 512a can vary and is not limited to the Wi-Fi packet bandwidth. For example, the wide bandwidth can be based on the DAC and ADC rates and the analog filter bandwidth, and the analog filter bandwidth can be greater than the Wi-Fi packet bandwidth. The transmission and reception of the RF signal 512a can be performed in hundreds of microseconds, so the impact on Wi-Fi communication can be minimal. Therefore, the RF sensing technology described herein can be used simultaneously with the Wi-Fi data exchange function.

[0103] The properties of the transmitted RF signal 512a may vary depending on the technology used. The RF sensing technology provided herein may be applied to WLAN technology, which typically operates at 2.4, 5, and 6 GHz, but may include frequencies ranging from 900 MHz to 60 GHz. Other frequency ranges may also be used. For example, the frequency used by the 802.11ad Wi-Fi standard (operating at 60 GHz). Because WLAN sensing can be performed in the same frequency band as communication, hardware may be used for communication and WLAN sensing. For example, one or more of the components of UE 200 may be included in a wireless modem (e.g., Wi-Fi or 5G modem) of a TV. Other RF communication technologies and signals may also be used, such as ultra-wideband (UWB) transceivers, and symbols similar to orthogonal frequency division multiplexing (OFDM) long training fields (LTFs) for channel capture to determine the presence and / or movement of a target object. In one example, known channel estimation techniques may be used, such as traditional long training fields (L-LTFs) and high throughput (HT) / very high throughput (VHT) / high efficiency long training fields (HE-LTFs) in communication packet preambles. Embodiments may use similar methods, for example, by using the known transmitted signal for channel estimation.

[0104] refer to Figure 6 , a diagram 600 illustrating an example use case of detecting a crowd using radio frequency sensing. Diagram 600 includes a first wireless node, such as a first UE 602, configured to perform RF sensing. The first UE 602 may be a smartphone or other mobile device owned by a first user 602a (e.g., UE 200, 105, or 106). The first user 602a may be close to a crowd including at least a first pedestrian 606 and a second pedestrian 608. The pedestrians 606, 608 may or may not have mobile devices, but in either case, the pedestrians 606, 608 do not need to have mobile devices to implement the crowd sensing techniques described herein. The first UE 602 may send an RF sensing signal 604a (e.g., Figure 5A and Figure 5B) and receives a reflected signal 604b returned from pedestrians 606, 608. In one example, the first UE 602 may be configured to determine range and orientation information based on the reflected signal 604b. For example, AoA technology may be used to determine the orientation of the pedestrian, and time-of-flight technology may be used to calculate the range. A first polar coordinate graph 610 shows the results of the RF scan, wherein a first target indication 612 corresponds to the relative position of the first pedestrian 606, and a second target indication 614 corresponds to the relative position of the second pedestrian 608. The first UE 602 may be configured to report target indications 612, 614 (e.g., range and orientation parameters) and status information of UE 602 to a network server for the crowdsourced RF sensing results. The status information may include the current position of UE 602 (e.g., based on satellite or other terrestrial technology), as well as other orientation information, such as direction of motion, speed, magnetic heading, and other sensor information, so that network resources can convert the local coordinate system (e.g., relative orientation) of UE 602 to a global coordinate system.

[0105] refer to Fig. 7A , and further reference Figure 6, a diagram 700 is shown of an example use case of detecting a crowd using multiple wireless nodes configured for radio frequency. In addition to including a second user 702a with a second wireless node (such as a second UE 702 (e.g., which can be UE 200, 105, or 106)), the diagram 700 also includes a first user 602a with a first UE 602 and pedestrians 606, 608. The second UE 702 is configured to perform RF sensing operations and can send an RF sensing signal 704a and receive a reflected signal 704b based on the location of the pedestrians 606, 608 and the first user 602a. Similarly, the first UE 602 can receive the reflected signal 604b based on the location of the second user 702a, and can determine a third target indication 706 based on the range and orientation to the second user 702a. In one example, the network server 400 can be configured as an RF sensing crowdsourcing server and can provide RF sensing assistance data to the first UE 602 and the second UE 702 to configure the RF sensing signals 604a, 704a. For example, the RF sensing assistance data may include beam configuration information, such as frequency, bandwidth, and timing information, so that the RF sensing signals 604a, 704a do not interfere with each other. In one example, the RF sensing signals 604a, 704a can be based on orthogonal components in an OFDM scheme. The second UE 702 can determine a first target indication 712 based on the relative position of the first pedestrian 606, a second target indication 714 based on the relative position of the second pedestrian 608, and a third target indication 708 based on the relative position of the first user 602a. The target indications 708, 712, 714 are shown on the second example polar coordinate diagram 710. The first UE 602 and the second UE 702 can provide UE status information and their corresponding target indications to the RF sensing crowdsourcing server to enable aggregation of RF sensing reports and analysis of sensor data. In one example, the UE 602, 702 may be configured to perform RF sensing and provide sensing reports periodically and / or as directed by a network or RF sensing crowdsourcing server.

[0106] In one example, UE 602, 702 may be configured to determine attributes associated with a target object. Attributes may be based on characteristics of reflected RF signals 604b, 704b. For example, Doppler shift, ranging change, and / or AoA drift may be used to estimate a motion vector associated with a target object. For example, a first pedestrian 606 may be associated with a first motion 606a, and a second pedestrian 608 may be associated with a second motion 608a. UE 602, 702 may be configured to determine other attributes associated with a target object, such as size, pose / orientation, and composition, based on RF signal characteristics. In one example, UE 602, 702 may be configured to determine attributes of a target object and provide attribute information and target indication information to server 400. Attributes of a target object may be used to identify and / or track an object. Attributes of a target object as a person may include height, width, pose (e.g., sitting, standing, walking, running), orientation (e.g., facing sideways, facing forward, or facing backward), clothing type, whether to carry a bag or other (multiple) objects. Attributes of a target object that is a vehicle may include length, width, height, speed, and / or a pattern or signature of reflected RF signals that indicates a specific type, make, and / or model of a vehicle (e.g., truck, SUV, compact car, midsize car, Ford, Chevrolet, Buick, Lexus, Dodge Ram, Toyota Highlander, Audi A4, etc.). Attributes of a target object that is a drone may include length, width, height, cross-sectional area, horizontal position, altitude, speed, direction of motion, and / or a pattern or signature of reflected RF signals that indicates a specific type, make, or model of a drone (e.g., multi-rotor, fixed wing, single rotor, number of rotors, DJI Matrix 300RTK, Skydio 2+, Autel Robotics EvoLite+, etc.).

[0107] In these examples, each of the UEs 602, 702 may analyze the reflected RF signals 604b, 704b, respectively, to determine properties and may provide the properties to the server instead of providing the original signal information of the reflected RF signals 604b, 704b to the server.

[0108] In another example, the UE 602, 702 may be configured to provide the server 400 with RF sensing signal information (e.g., RF signal characteristics that the UE 602, 702 may not analyze and interpret). The server 400 may then be configured to detect the target object and determine the properties of the target object. For example, the UE 602, 702 may provide state information (e.g., UE position, UE transmit power, UE orientation, etc.) and time domain and / or frequency domain components of the reflected signal. In one example, the UE 602, 702 may be configured to perform analog-to-digital conversion on the received RF sensing signal and provide a digital representation of the RF sensing signal to the server 400. For example, the server 400 may be configured to analyze the frequency of the reflected RF sensing signal 604b, 704b to detect a frequency shift (e.g., Doppler) associated with the pedestrians 606, 608, and estimate the movement of the pedestrians 606, 608 based on the corresponding frequency shift and state / position of the UE 602, 702. The server 400 may also be configured to determine other properties associated with the target object.

[0109] The server 400 may aggregate the attribute and / or RF sensing signal information provided by and received from the UEs 602 and 702. In the example diagram 700, both the UEs 602 and 702 may provide attribute and / or RF sensing signal information for pedestrians 606 and 608. By aggregating (i.e., combining) the information, the server 400 may obtain or infer more information about the pedestrians 606 and 608 than may be obtained or inferred from the attribute and / or RF sensing signal information provided by only one UE (e.g., only UE 602 or UE 702). For example, by aggregating the information, the server may obtain or infer a more accurate position, speed and / or direction of movement, size, weight, posture, gait, clothing type, bag or package carried by one or both of the pedestrians 606 and 608. This may be partly because UE 602 and 702 are located at different locations and transmit RF sensing signals 604a and 704a, respectively, and receive reflected signals 604b and 704b, respectively, which reach pedestrians 606 and 608 and are reflected or scattered at different angles and directions by pedestrians 606 and 608, respectively. The different ranging, different AOA, and / or different Doppler shifts of each pedestrian 606 and 608 obtained (e.g., by UE 602, UE 702, and / or server 400) can then be used to triangulate or trilaterate a more accurate position, speed, and / or direction of motion of each pedestrian 606 and 608. Similarly, the signal characteristics of reflected signals 604b and 704b can both indicate a certain type of clothing (e.g., based on a certain type of clothing reflecting the signal more strongly than other clothing), or can both indicate the carrying of a package or bag (e.g., based on the greater intensity of the reflected signal).

[0110] refer to Figure 7B , and further reference Fig. 7A , a diagram 750 is shown of an example use case of improving detection of a single target object using multiple wireless nodes configured for radio frequency sensing. The diagram 750 includes a first user 602a having a first UE 602, a second user 702a having a second UE 702, and a pedestrian 608. Also shown are a first polar plot 610 showing a target indication 614 result of an RF scan of the pedestrian 608 by the UE 602 and a second polar plot 710 showing a target indication 714 result of an RF scan of the pedestrian 608 by the UE 702. The target indication 614 result may include an orientation 652 (e.g., an orientation relative to true north), a range 654, and a velocity component 656 (which may be obtained from a Doppler shift) of the pedestrian 608 sensed at the location of the first UE 602. Similarly, the target indication 714 result may include an orientation 752, a range 754, and a velocity component 756 (which may be obtained from a Doppler shift) of the pedestrian 608 sensed at the location of the second UE 702. If the positions of the two UEs 602 and 702 are known, the position of the pedestrian 608 can be uniquely obtained from any of the following: bearing 652 and ranging 654; bearing 752 and ranging 754 or bearing 652 and bearing 752. That is, only two of the four variables are needed to locate the pedestrian 608. The additional two variables can then be used to improve the accuracy of the position of the pedestrian 608. For example, if there is a measurement error in any one or all of the bearing 652, ranging 654, bearing 752, and ranging 754, all four variables can be combined to calculate a position with an expected error that is smaller than the expected error of the position calculated using only two (or three) of the four variables, for example, using a least squares method. If the bearing and ranging results of the pedestrian 608 are obtained from an additional UE ( Figure 7B 608a (e.g., the speed and direction of walking or running) can be calculated based on the speed components 656 and 756 determined by the two UEs 602 and 702 based on simple vector algebra. For position calculation, if the speed component of the pedestrian 608 is provided by the RF sensing results from the additional UEs, the accuracy of the speed calculation can be further improved.

[0111] As discussed with respect to Figures 700 and 750, one problem of aggregating RF sensing results of multiple UEs from a common target object may be to ensure that the RF sensing results from multiple UEs are applied to the same target object rather than different target objects. One way to achieve this may be to obtain RF sensing results of multiple target objects from each UE at approximately the same time, wherein the multiple target objects may include stationary and mobile target objects. The RF sensing results of stationary target objects can be used to compare RF sensing results between different UEs. For example, if two UEs obtain RF sensing results indicating the number of stationary target objects (e.g., buildings, walls, trees, lamp posts, traffic lights) at approximately the same location, the indication of the mobile target object may become easier to associate. For example, if two UEs sense a first mobile target object in the middle of two stationary target objects (the location of each stationary target object is indicated as being approximately the same according to the RF sensing results from the two UEs), and if neither UE senses another mobile target object near the first mobile target object, it can be assumed that the two UEs sense the same first mobile target object.

[0112] This observation can be generalized to RF sensing results provided by multiple UEs, where the RF sensing results from each UE indicate the number of stationary and mobile target objects. For example, the server can combine the indications of stationary and mobile target objects by calculating a geographical map of the stationary and mobile target objects indicated by the RF sensing results provided by each UE. If the stationary target objects sensed by each UE are generally aligned with the stationary target objects sensed by other UEs, the server can use the position of the stationary target objects as a reference point to define and evaluate the position of the mobile target objects. If the position of the mobile target objects relative to the stationary target objects is approximately the same for each UE, the server can assume that the mobile target objects sensed by different UEs are the same mobile target object. Sensing results from a small number of misaligned UEs can be ignored because the errors, positions, and movements inferred from the RF sensing results from other UEs can be further statistically averaged to further improve accuracy.

[0113] Although the example diagrams 700 and 750 only show two sensing UEs 602 and 702, there may be many other UEs ( Fig. 7A and Figure 7B), which can send attributes and / or RF sensing signal information of pedestrians 606 and 608 to server 400 based on the transmission of RF sensing signals and the reception of reflected or scattered signals, similar to what is described for UE 602 and 702. In this case, server 400 can access information related to attributes, such as the position, speed and / or moving direction, size, weight, posture, gait, clothing type, and carrying of bags or parcels of one or both of pedestrians 606 and 608 obtained by UE at many different directions and distances from pedestrians 606 and 608, which can greatly improve the accuracy and reliability of server 400 in determining these attributes.

[0114] refer to Fig. 8A , a diagram 800 of an example use case of using radio frequency sensing to detect stationary objects in a crowd is shown. Diagram 800 includes multiple wireless nodes (also referred to as wireless devices) (e.g., UEs 200, 105, 106) configured for RF sensing, such as a first UE 802, a second UE 804, a third UE 806, and a fourth UE 808. UEs 802, 804, 806, 808 are oriented so that the RF sensing operation of each UE covers a limited area, such as a first area 802a of the first UE 802, a second area 804a of the second UE 804, a third area 806a of the third UE 806, and a fourth area 808a of the fourth UE 808. The locations of the UEs and the corresponding coverage areas are examples and not limitations, as the UEs may be in other locations and may have different coverage areas. Diagram 800 includes a group of moving pedestrians 830a-i, as well as examples of stationary inanimate objects, such as a first lamp post 820, a tree 822, and a second lamp post 824. UE 802, 804, 806, 808 or RF sensing crowdsourcing server can be configured to detect stationary inanimate objects to improve crowd estimation (e.g., exclude inanimate objects from crowd counting). In one embodiment, UE 802, 804, 806, 808 can be configured to calculate relative ranging, orientation, and motion information based on RF sensing operations, such as shown in corresponding polar coordinate plots 812, 814, 816, 818. For example, UE 802, 804, 806, 808 can be configured to detect motion using Doppler shift and / or changes in ranging and / or AoA in RF signal reflections. Multiple measurements obtained over a time period can also be used to detect whether a target object is moving or stationary. Other RF signal parameters can also be used to classify the target object.

[0115] Diagram 800 shows how a server (e.g., server 400) can obtain RF sensing results from many wireless devices (in this case, UEs 802, 804, 806, 808), which can enable RF sensing of a larger area or volume than any one wireless device can sense by itself. In this example, UEs 802, 804, 806, 808 can provide RF sensing results for an area including a first area 802a, a second area 804a, a third area 806a, and a fourth area 808a. When some of the first area 802a, the second area 804a, the third area 806a, and the fourth area 808a overlap partially (or even completely), RF sensing results can be provided by two or more of the UEs 802, 804, 806, 808 for the same target object (e.g., a person, a vehicle, an animal, a drone, or some other object), which can improve the accuracy and reliability of inferring the attributes of the target object, as discussed above with respect to diagrams 700 and 750. Therefore, by using multiple sensing wireless devices, the server can obtain or infer the properties of the target object with higher accuracy and reliability over a larger area or volume.

[0116] refer to Figure 8B , diagram 840 showing an example use case of tracking a mobile object using radio frequency sensing. Diagram 840 shows some of the UEs and a moving pedestrian 830 previously shown and described with respect to diagram 800. In an embodiment of tracking a mobile target object, the LMF 120 or the server 400 may determine the presence of a mobile target object that may be sensed by a first set of UEs in a first area, and may obtain or infer attributes of the target object (e.g., position, velocity, direction of movement) that suggest that the target object will enter a second area at some nearby future time. The LMF 120 or the server 400 may then send sensing assistance data to a second set of UEs that may perform RF sensing in the second area, and may include information in the sensing assistance data so that the second set of UEs may obtain RF sensing results for the target object. In this manner, tracking of the target object may be switched from the first set of UEs to the second set of UEs without losing the RF sensing results for the target object for any significant time (e.g., more than 3 seconds). In Figure 8BIn the example shown, the first area may be area 802a, the second area may be area 806a, the first UE set may be UE 802, the second UE set may be UE 806, and the moving target object is pedestrian 830c. At time T1, pedestrian 830c is in area 802a and is being tracked by UE 802. At time T2, pedestrian 830c has moved into area 806a and is being tracked by UE 806. At time T1 or shortly after time T1, LMF 120 or server 400, which has received the RF sensing result from UE 802, may send auxiliary data to UE 806, indicating that pedestrian 830c will soon be visible in area 806a, and may provide the expected location, expected time (e.g., time T2), and expected speed or velocity of pedestrian 830c, as well as other attributes of pedestrian 830c, such as approximate height, size, clothing type, etc. This may enable the UE 806 to detect the pedestrian 830 c based on the RF sensing results obtained by the UE 806 , and in particular to track the pedestrian 830 c , and provide the associated RF sensing results to the LMF 120 or the server 400 .

[0117] In operation, refer to Figure 8C , an example message flow 850 for performing crowd sensing operations is shown. Message flow 850 is an example and not a limitation, as other messages may be used in the communication system 100 to obtain RF sensing information from network nodes. Flow 850 includes an RF sensing crowdsourcing perception server (such as LMF 120 or another server 400), a base station (such as gNB110a), and multiple wireless nodes (such as UE 852 (for example, which may be an instance of UE 105 or UE 106)). UE 852 may include some or all of the components of UE 200, and UE 200 is an example of one of UE 852. In Figure 8CIn the illustrated use case, the UE 852 may include UEs 802, 804, 806, 808. In one example, the LMF 120 (or other crowdsourcing server) may be configured to send an RF sensing request message 854 to one or more of the UEs 852, for example, via an LPP or TCP / IP message. The UEs 852 may respond with an RF sensing capability message 856 to indicate their respective capabilities to participate in RF sensing operations. For example, a UE actively engaged in a communication application (e.g., voice, video, data, etc.) or other processor and / or bandwidth intensive operations may not be able to participate in the requested RF sensing operation. The RF sensing capability message 856 may also include parameter information (e.g., location, orientation, bandwidth, power, frequency range, beam width, etc.) about the ability of the UE 852 to perform RF sensing operations. The LMF 120 may generate and provide an RF sensing assistance data message 858 including RF sensing configuration information to enable the UE 852 to jointly perform RF sensing operations. The RF sensing assistance data message 858 may be provided via an LPP message, an IP message, or a TCP / IP message. In one example, the RF sensing assistance data message 858 may include sector information (eg, Fig. 8A 802a, 804a, 806a, 808a in the regions 802a, 804a, 806a, 808a), and transmitter configuration information for reducing cross-interference of RF sensing signals (e.g., parameters such as frequency range, timing, guard band, beam width, predefined transmission sequence, etc.). In one example, the RF sensing operation can utilize OFDM technology, and the RF sensing assistance data message 858 may include resource portion information (e.g., timing and frequency) for the RF sensing operation. In one example, the assistance data may include RF signature and / or attribute information associated with the expected target object. The information may include expected location (e.g., ranging / azimuth), expected movement (e.g., speed / direction), size and / or other frequency domain characteristics to assist the UE 852 in identifying the target object (e.g., Figure 8B Other information elements may also be included in the auxiliary data.

[0118] At stage 860, UE 852 may perform RF sensing operations based at least in part on the assistance data. For example, UE 802, 804, 806, 808 may be configured to jointly perform monostatic RF sensing operations based on an assigned geographic area (e.g., area 802a, 804a, 806a, 808a), time division, frequency division, and / or a combination of area, time, and frequency. In one example, UE 802, 804, 806, 808 may be configured for bistatic RF sensing, such that an RF signal transmitted by one UE that is reflected, scattered, diffracted, and / or absorbed by a target object may be received and utilized by other UEs to detect the target object.

[0119] The UE 852 may be configured to provide an RF sensing report message 862 to the LMF 120 based on the RF sensing operation of stage 860. In one example, each of the UEs 852 may be configured to determine attributes associated with the target object, such as size, motion, ranging, orientation (e.g., direction of the visual axis), elevation (e.g., in a 3D implementation), or other attributes, based on the received RF signal. The RF sensing report message 862 may include attribute information. In one example, the UE 852 may provide raw RF signal information in the RF sensing report message 862, and a network server such as the LMF 120 or other server 400 may be configured to determine the attribute based on the RF signal information. In stage 864, the crowdsourcing server may be configured to analyze and aggregate the content of the RF sensing report message 862 across multiple UEs 852, and provide crowd sensing information back to the UE 852, or provide the crowd sensing information to another entity such as an external client or server 130.

[0120] At stage 864, the crowdsourcing server may determine one or more environmental characteristics based at least in part on the analysis and aggregation of the RF sensing report message 862. The one or more environmental characteristics (e.g., inferences) may include at least one of the following: tracking the movement or position of a person, vehicle, animal, drone, or other object, or both; determining one or more attributes of a person, vehicle, animal, drone, or other object; and determining one or more attributes of a crowd, multiple vehicles, animal swarm, drone swarm, or other collection of objects. The one or more attributes of a person, vehicle, animal, drone, or other object may include horizontal position, altitude, speed, orientation, size, height, width, length, weight, type, brand, model, kind, orientation, posture, gait, clothing type, carrying of a bag or parcel, or some combination of these. The one or more attributes of a crowd, multiple vehicles, animal swarm, drone swarm, or other collection of objects may include location, location area, density, number, rate of increase in number, rate of decrease in number, average speed, statistical direction of movement, or some combination of these. The crowdsourcing server may include information related to at least one of the movement, position, or one or more attributes of a person, vehicle, animal, drone, or other object in the RF sensing assistance data message 858. The crowdsourcing server may also or alternatively include in the RF sensing assistance data message 858 information related to at least one of one or more attributes of a crowd, a plurality of vehicles, a swarm of animals, a swarm of drones, or other collection of objects.

[0121] Although the messages in message flow 850 may utilize the described LPP, other messaging and control techniques may also be used. For example, RF sensing assistance data and reports may utilize radio resource control (RRC) techniques, or may employ messages (e.g., HTTP messages) transmitted over a user plane (e.g., using the TCP / IP protocol). Other techniques such as a media access control (MAC) control element (CE) may be used to trigger RF sensing operations. For example, the gNB 110a may be configured to provide a MAC-CE message to activate RF sensing in the UE, and the UE may be configured to provide an RF sensing report in response to receiving the MAC-CE message. Other signaling techniques may also be used.

[0122] refer to Fig. 9, shows an example directional diagram 900 including the boresight direction of an object detected using radio frequency sensing. Diagram 900 is an example of RF sensing information that can be determined by a UE (e.g., UE 852) and included in an RF sensing report message 862, and used by an RF sensing crowdsourcing server (e.g., LMF 120 or server 400) to aggregate the RF sensing information. In one example, the RF sensing information can include an array of boresight angles and gain information, such as shown in diagram 900. Diagram 900 includes a coordinate plane 902 (e.g., polar angles from 0 degrees to 360 degrees, which can be related to or aligned with a global coordinate plane such as having a north-south or east-west polar axis) and a signal gain value 904, so that the relative strength of the received RF signal (e.g., the gain of the reflected signal 512b) can be plotted from a center position 906. The set of measurements extending at various angles from the center position 906 indicates the strength of the RF signal received at the corresponding boresight angle. For example, the first measurement 908a has a relatively higher gain (e.g., signal strength) than the surrounding measurements, and can indicate that the object is located at the boresight angle. The gain value (e.g., the length of the measurement) can also be used to indicate the size of the object. In contrast, the second measurement 908b has a relatively small gain (e.g., at the noise level) and can therefore indicate that the target object is not present. The boresight angle and gain value are examples and can vary based on the capabilities of the UE. In one example, the angular resolution can be in the range of 2 degrees to 5 degrees.

[0123] refer to Fig.10 , a graph 1000 of exemplary frequency-based components in radio frequency signal information is shown. Graph 1000 represents a generalized frequency domain analysis of a reflected RF signal. In general, an RF signal can be represented as an array of variables and can be plotted in the frequency domain with a gain axis 1002 and a frequency axis 1004. A frequency response 1006 can include an array of frequencies and gain values ​​that can be used to characterize a target. For example, a target signal region 1008 can be based on an RF pulse and used to distinguish and / or identify a specific target. Signal region 1008 is an example of signal information (e.g., frequency-based components) that can be included in one or more RF sensing report messages 862 and used by a crowdsourcing server to identify a target. In operation, frequency response 1006 can represent other spectral functions, such as Doppler frequency or other spectral processing, such as power spectral density (PSD). In one example, a machine learning application can be trained with the frequency response and used to characterize signal region 1008. Frequency response 1006 may apply to a particular boresight direction in a pattern such as pattern 900, and thus each of the measurements in the pattern (e.g., Fig. 9 The measurements 908a, 908b in FIG. 1004 may have their own unique frequency response, such as the frequency response 1006 shown in the graph 1000.

[0124] refer to Fig.11 , a graph 1100 of an exemplary time-based component of radio frequency signal information is shown. Graph 1100 represents a generalized time domain analysis of a reflected RF signal. In general, an RF signal can be represented as an array of variables and can be plotted in the time domain with a gain axis 1102 and a time axis 1104. A time response 1106 may include an array of time and gain values ​​that can be used to characterize a target. For example, a target signal region 1110 may be based on an RF pulse 1108 and used to distinguish and / or identify a specific target. Signal region 1110 is an example of signal information (e.g., a time-based component) that may be included in one or more RF sensing report messages 862 and used by a crowdsourcing server to identify a target. In operation, time response 1106 may represent other time domain functions, such as scattering characteristics, pulse curves, and time-frequency characteristics. In one example, a machine learning application may be trained with the time domain response and used to characterize signal region 1110. The time response 1106 may apply to a particular boresight direction in a pattern, such as the pattern 900 , and / or to a particular frequency response, such as the frequency response 1006 shown in the graph 1000 .

[0125] refer to Fig.12 , an example time and frequency response graph 1200 of a radio frequency sensing signal is shown. Graph 1200 represents a generalized time and frequency response of a reflected RF signal. In one example, UE 1202 can be configured to perform RF sensing operations including transmitting an RF signal 1204a and receiving a reflected RF signal 1204b based on a neighboring object 1206. UE 1202 can be configured to determine the time and frequency response of the reflected signal 1204b as a multivariate array, such as a response function 1216. The multivariate array can include gain, frequency, and time parameters, which can be plotted on a gain axis 1210, a frequency axis 1212, and a time axis 1214, such as Fig.12 As shown. A multivariate array (e.g., response function 1216) is an example of signal information that may be included in one or more RF sensing report messages 862 and used by a crowdsourcing server to identify a target. In operation, a machine learning application may be trained with the response function 1216 of an associated target and used to characterize the reflected signal 1204b. The multivariate response function 1216 may be applied to a specific boresight direction in a pattern (such as pattern 900), in which case a multivariate array in four dimensions may be plotted to include gain, frequency, time, and boresight direction parameters. The information in such a four-dimensional graph may be an example of signal information that may be included in one or more RF sensing report messages 862 and used by a crowdsourcing server to identify a target or set of targets.

[0126] refer to Fig.13 , an example data structure 1300 for crowdsourcing RF sensing signal information is shown. The data structure 1300 may be stored (e.g., may be saved) in an external client or server 130 such as a crowdsourcing server, or in another networked server 400 such as LMF 120. In one embodiment, the data structure 1300 may be stored (e.g., may be saved) in the UE 200. The data structure 1300 may be provided on a storage device 1302 such as a solid state or mechanical hard drive, and may include a plurality of data records stored in a relational database application (e.g., Amazon Aurora, Oracle Database, Microsoft SQL Server, MySQL, DB2, etc.) or in one or more flat files (e.g., JSON, XML, CSV, etc.). The table structures and fields in the data structure 1300 are examples and not limitations, as other data fields, tables, stored procedures, and index patterns may be used to construct the data structure 1300. In one example, a report table 1304 may be configured to capture parameters associated with an instance of an RF sensing operation. One or more datetime fields (e.g., start / stop time, duration, etc.) may be used to record when the RF sensing operation occurred, and the location information field may indicate the location where the RF sensing operation occurred (e.g., latitude / longitude / altitude, grid coordinates, etc.). The UEID field may uniquely identify the wireless node that obtained the RF sensing measurement (e.g., using a global identifier of the wireless node or some other unique identifier assigned to or by the wireless node that hides the global identifier and provides privacy for the wireless node). One or more UEstateparams fields may capture UE state information during the RF sensing operation. For example, the state information may include orientation and inertial measurement values ​​(e.g., based on IMU 270), user presence detection, battery charge, software state / version, and other UE-specific parameters used to characterize the state of the wireless node during the RF sensing operation. The ChannelParams field may be used to capture channel information such as channel state (e.g., CIR, CFR, CSI) and channel gain (e.g., SNR) during the RF sensing operation.

[0127] Records in report table 1304 may be related to other tables, such as signal table 1306 and object table 1308. Signal table 1306 may include fields associated with RF sensing signals measured by the wireless node. In one example, these fields may include time, date, and location information associated with the signal measurement (e.g., based on the location of the wireless node during the RF sensing operation). The signal information may include one or more boresight fields indicating the angle of arrival (AoA) of the RF signal and the corresponding signal strength. For example, the boresight fields may be based on the information shown in diagram 900. Parameters associated with time domain and frequency domain measurements may also be stored in arrays associated with signal table 1306. For example, the frequency domain array may include Fig.10 The frequency components described in , and the time domain array can include Fig.11 Other fields and data structures may be used to store other signal parameters, such as Fig.12 The time and frequency response information described in, as well as other signal identification parameters (e.g., applicable to radar and known in the art).

[0128] The object table 1308 may include parameters associated with target objects detected by the wireless node and reported to the crowdsourcing server. In one example, these fields may include time, date, and location information associated with the signal measurement (e.g., based on the location of the wireless node during the RF sensing operation). Object ranging and orientation information determined by the wireless node may be included in one or more fields in the object table 1308. Other attribute fields may be included to record the attributes of the target object determined by the wireless node, such as size, pose / orientation, speed, and direction of motion. Other fields may be used for additional attributes. One or more classification fields may be used to store classification information provided by the reporting wireless node. For example, the reporting wireless node may be configured to classify the target object based on the RF signals sent and received. The classification may be based on local processing of the RF signal to provide a general description of the target (e.g., a person, dog, car, truck, tree, wall, building, etc.). In one example, the wireless node may be configured to classify the target object using other sensors (e.g., camera, microphone, lidar, ultrasound, etc.) and provide an RF sensing report to the classification. In one example, the wireless node may be configured to include sensor information (e.g., images, audio recordings) in an RF sensing report message (e.g., RF sensing report message 862). Similar fields and data structures may be used to store object-based parameters to enable a crowdsourcing server to store and aggregate the results of RF sensing operations obtained by multiple wireless nodes.

[0129] refer to Fig.14A and Fig. 14B, shows a schematic diagram of a composite graph based on multiple radio frequency sensing reports. The first graph 1400 includes an RF sensing data structure 1402, which is operably coupled to a communication network 1401 including a base station 1404. The communication network 1401 is an example of the communication system 100, and the RF sensing data structure 1402 can be included in a crowdsourcing server, such as an external client or server 130, LMF 120, or another server 400. The RF sensing data structure 1402 may include Fig.13 The table described in, for example, may include a table of each of a plurality of wireless nodes (e.g., UEs 105 and 106) that provide RF sensing report messages (e.g., RF sensing report messages 862) to a crowdsourcing server. Base station 1404 may include components of TRP 300, and TRP 300 may be an example of base station 1404. Although in Fig.14A and Fig. 14B 1402. One base station is shown in FIG. 1401, but additional base stations may be used to send and receive RF sensing information to UEs within the communication network 1401. The communication network 1401 may utilize message flow 850 to send and receive RF sensing information to multiple wireless nodes (e.g., UEs, such as UEs 105 and 106) in the network. For example, a first UE 1406 may be configured to obtain RF sensing measurements within a first area 1406a, a second UE 1408 may be configured to obtain RF sensing measurements within a second area 1408a, and a third UE 1410 may be configured to obtain RF sensing measurements within a third area 1410a. The first UE 1408 may detect a first object 1412a and a second object 1412b, and provide one or more RF sensing measurement report messages to be stored in the RF sensing data structure 1402. The second UE 1408 may detect a third object 1412c, and the third UE 1410 may detect the second object 1412b and the fourth object 1412d. The second UE 1408 and the third UE 1410 may also provide corresponding RF sensing report messages to the crowdsourcing server. The RF sensing report message may include a boresight angle, time, frequency and / or gain component (such as in Figures 9 to 12 ), and / or object information (such as Figures 6 to 8A 1402). For example, the RF sensing report message may include the current location of each of the corresponding UEs and the detected range and orientation to the object. The server 400 may be configured to store the RF sensing information in the RF sensing report message in one or more tables in the RF sensing data structure 1402.

[0130] refer to Fig. 14B, a second figure 1450 shows a composite graph 1454 based on RF sensing reports provided by UEs 1406, 1408, 1410. In one example, the server 400 within the communication network 1401 or an external server 1452 can access the RF sensing data structure 1402 to calculate the composite graph 1454 and determine one or more environmental characteristics based on the RF signals and / or attributes associated with each of the target objects. In one example, the external server 1452 can access the RF sensing data structure 1402 via a wired connection 1452a or via a wireless connection 1452b. The environmental characteristics can be based on the location of the object, the density of the object, the movement of the object, or other properties of the individual objects when viewed as a group. For example, in a crowd sensing use case, objects 1412a-d can be associated with people moving in a building or other pedestrian area, and the environmental characteristics can be based on the density of objects 1412a, 1412b, 1412d near the first user 1406 and the third user 1408. Crowd density can infer higher pedestrian traffic (e.g., if the object is moving), or a preferred location for viewing an event, or any other inference associated with an increased (or decreased) crowd size. In one example, the external server 1452 can be configured to track the object over a period of time. For example, the close location of the object (e.g., based on ranging and orientation from the UE) and the movement of the object (e.g., based on multiple measurements from the UE) can be used to identify and track the object passing through different coverage areas. In one example, the server 400 can be configured to provide RF sensing assistance data with an estimated location of the object to enable the UE to capture and track the object.

[0131] refer to Fig.15 , and further reference Figures 1 to 14A , method 1500 for determining object attributes using radio frequency sensing includes the stages shown. However, method 1500 is an example and not a limitation. For example, method 1500 can be changed by adding, removing, rearranging, combining, performing stages simultaneously, and / or dividing a single stage into multiple stages. Method 1500 can be performed by a server (e.g., LMF 120, server 400 or external client or server 130), a network node (e.g., AMF 115), or a wireless device (e.g., UE 105).

[0132] At stage 1502, the method includes receiving radio frequency sensing signal information. The server 400 including the processor 410 and the transceiver 415 is a component for receiving the RF sensing signal information. In one example, one or more wireless nodes (also referred to herein as one or more wireless devices), such as Figure 8C852 in the UE 852, can provide the server 400 with an RF sensing report message 862 including RF sensing signal information. In one example, the RF sensing signal information can include one or more boresight fields indicating the angle of arrival (AoA) of the RF signal and the corresponding signal strength, such as shown in Figure 900. The RF sensing signal information can include other parameter values ​​associated with time and frequency and / or time domain measurements, which can be stored in an array associated with the signal table 1306. The RF sensing signal information can include other values ​​and / or data structures, such as Fig.12 The RF sensing signal information may include time and frequency response information described in, and other parameter values ​​associated with radar signal identification techniques known in the art. The RF sensing signal information may also include status information based on the configuration of the wireless node and the RF sensing operation. For example, the RF sensing signal information may include identification, time, date, and / or location information associated with the wireless node performing the RF sensing operation.

[0133] At stage 1504, the method includes detecting one or more time-based components and one or more frequency-based components in the RF sensing signal information. The server 400 including the processor 410 is a means for detecting one or more time-based components and one or more frequency-based components in the RF sensing signal information. In one example, the time-based component may include a delay time associated with the transmitted RF signal and the detected reflected signal. The time-based component may also include AoA and gain information associated with the reflected RF signal (e.g., such as Fig. 9 One or more frequency components may include a Doppler shift in the reflected RF signal. Figures 10 to 12 Other time and / or frequency components as shown may be included in the RF sensing signal information, and the server 400 may be configured to store the time and frequency components in the signal table 1306. Other data structures may also be used.

[0134] At stage 1506, the method includes determining a range to the object based at least in part on one or more time-based components. The server 400 including the processor 410 is a component for determining the range. In one example, referring to Figure 5A and Figure 5B , the time difference between the first peak 558 (ie, the transmission time) and the second peak 560 (ie, the reflected signal 512b) can be used to estimate the distance to the object. The AoA of the reflected signal 512b can also be obtained based on ADC capture from multiple antennas (e.g., additional receive chains 520, 522).

[0135] At stage 1508, the method includes determining one or more attributes of the object based at least in part on one or more time-based components or one or more frequency-based components. The server 400 including the processor 410 is a component for determining the one or more attributes. Generally, the time-based and frequency-based components include Figures 9 to 12 Parameters described in and stored in data structure 1300. In one example, server 400 can be configured to determine the speed, direction and / or size of the object. The speed of the target object can be obtained based on an indication of the Doppler shift in the RF sensing signal information. The angular direction can be based on different AoD and AoA information in the RF sensing signal information. Other techniques, such as feature analysis and backscattering techniques known in the art, can be used to detect other properties of the object. For example, the size of the target object can be based on the amplitude of the received signal, and the presence of a moving part on the target object can be based on detecting different Doppler shifts in time and frequency components. Server 400 can be configured to perform other spectral functions, such as Doppler frequency or PSD processing. In one example, a machine learning algorithm can be used to determine one or more properties of an object. For example, a supervised learning method can use training data such as time and frequency responses (e.g., response function 1216) of a known object to establish a relationship between an input and a corresponding output. For example, a supervised learning method can be used to determine the properties of an object based on a response function obtained during an RF sensing operation. Unsupervised learning techniques such as clustering, dimensionality reduction, anomaly detection, and association mining may also be used to classify the response function 1216 and determine the properties of the detected objects.

[0136] refer to Fig.16 , and further reference Figures 1 to 15 , a method 1600 for crowdsourcing radio frequency sensing data includes the stages shown. However, the method 1600 is an example and not a limitation. For example, the method 1600 can be changed by adding, removing, rearranging, combining, performing stages simultaneously, and / or dividing a single stage into multiple stages. The method 1600 can be performed by a wireless device such as UE 105, UE 106, UE 200, or TRP 300.

[0137] At stage 1602, the method includes receiving radio frequency sensing assistance data from a server. A wireless node such as UE 200 including a general purpose processor 230 and a transceiver 215 is a component for receiving RF sensing assistance data. The server may be an external client or server 130, LMF 120, server 400, or another edge server configured to communicate with one or more wireless nodes in a network. In one example, the server may be configured to provide RF sensing assistance data messages 858 to one or more wireless nodes, such as any UE 852.

[0138] At stage 1604, the method includes performing a radio frequency sensing operation based at least in part on the radio frequency sensing assistance data. The UE 200 including the general processor 230 and the transceiver 215 is a component for performing the RF sensing operation. In one example, the wireless device receiving the RF sensing assistance data at stage 1602 may configure the transmitter and / or receiver settings based on the RF sensing assistance data. The server may configure the wireless device to perform a single-station RF sensing operation based on an assigned geographic area, time division, frequency division, and / or a combination of area, time, and frequency. Other information elements in the RF sensing data may also be used to configure the RF sensing operation. In one example, the wireless device may be configured for dual-station RF sensing so that an RF signal transmitted by another nearby wireless device may be received by the wireless device to detect one or more target objects. The radio frequency sensing operation may include transmitting one or more radio frequency (RF) signals (e.g., RF signals for IEEE 802.11 WiFi or 5G NR). The radio frequency sensing operation may include detecting one or more stationary objects. The radio frequency sensing assistance data may include location information associated with one or more stationary objects. Reference Fig. 8A In crowd sensing use cases, target objects may include people (e.g., crowds) as well as stationary objects. In one example, the RF sensing assistance data may include location and / or signal information associated with stationary objects (e.g., lamp posts, street signs, etc.) to enable the wireless device to detect the stationary objects and establish a coordinate reference.

[0139] The RF sensing assistance data may include RF sensing configuration information to enable the wireless device to perform an RF sensing operation. For example, the RF sensing assistance data may include geographic information, for example, for defining where the wireless device is located and / or where the target of RF sensing is located, and the wireless device may perform the RF sensing operation based at least in part on the geographic information. The RF sensing assistance data may include transmitter configuration information, for example, for reducing cross-interference of RF sensing signals, and the wireless device may perform the RF sensing operation based at least in part on the transmitter configuration information. The RF sensing assistance data may include timing information, for example, to implement time division multiplexing (TDM) of RF sensing operations with multiple other wireless devices, and the wireless device may perform the RF sensing operation based at least in part on the timing information. The RF sensing operation may utilize OFDM, UWB, LTF, L-LTF and / or HT technology, and the RF sensing assistance data may include orthogonal frequency division multiplexing configuration information, such as communication packet preamble information, and the wireless device may perform the RF sensing operation based at least in part on the orthogonal frequency division multiplexing configuration information. In one example, the RF sensing assistance data may include RF signatures and / or attribute information associated with one or more potential targets, and the wireless device may perform RF sensing operations based at least in part on the RF signatures or attribute information. The attribute information may include expected location (e.g., range / orientation), movement (e.g., speed / direction), size, and / or other frequency domain characteristics to assist in identifying and tracking target objects.

[0140] At stage 1606, the method includes reporting the RF sensing results to the server. The UE 200 including the general processor 230 and the transceiver 215 is a component for reporting the RF sensing results. In one example, the wireless device can be configured to provide data such as the RF sensing report message 862 based on the RF sensing operation of stage 1604. In one example, the wireless device can be configured to determine attributes associated with one or more target objects based on the RF sensing operation. Based on the received RF signal, the attribute may include size, motion, ranging, azimuth (e.g., line of sight direction), elevation (e.g., in a 3D implementation), speed, direction of motion, or a combination thereof. The RF sensing results include data such as attribute information. Reporting the RF sensing results may include reporting one or more attributes associated with one or more target objects. In one example, reporting the RF sensing results may include reporting RF signal information based on the RF sensing operation, such as a time-based component, a frequency-based component, or both. The server may be configured to determine additional attributes based on the RF signal information. In one example, the server may be configured to aggregate RF sensing results received from multiple wireless devices (including the wireless device) to calculate a composite map and / or determine additional attributes and / or one or more environmental characteristics, such as Figure 8CIn one example, the RF sensing results may also include sensor data obtained from other sensors on the wireless device (such as images from a visible light-based camera and / or infrared camera, lidar), or other sensor information based on the capabilities of the wireless device. In one embodiment, method 1600 may iterate back to stage 1602, and the wireless device may receive additional assistance data from the server. The server may be configured to update the additional assistance data based on the RF results, so that the wireless device may receive updated signal and object tracking information with each iteration of the assistance data.

[0141] In one embodiment, the server may receive multiple RF sensing results from multiple wireless devices including the wireless device. The server may then aggregate the multiple RF sensing results and determine one or more environmental characteristics based on the aggregated multiple RF sensing results, such as for Figure 8C Phase 864 and for Fig. 7A , Figure 7B , Fig. 9 and Fig.13 Described. One or more environmental characteristics may include at least one of the following: tracking the movement or position of a person, vehicle, animal, drone, or other object, or both; determining one or more attributes of a person, vehicle, animal, drone, or other object; and determining one or more attributes of a crowd, multiple vehicles, animal swarms, drone swarms, or other collections of objects. One or more attributes of a person, vehicle, animal, drone, or other object may include horizontal position, altitude, speed, orientation, size, height, width, length, weight, type, brand, model, kind, orientation, posture, gait, clothing type, carrying of a bag or parcel, or some combination of these. One or more attributes of a crowd, multiple vehicles, animal swarms, drone swarms, or other collections of objects may include location, location area, density, number, rate of increase in number, rate of decrease in number, average speed, statistical direction of movement, or some combination of these. The radio frequency sensing assistance data may include information related to at least one of the movement, position, or one or more attributes of a person, vehicle, animal, drone, or other object. The radio frequency sensing assistance data may include information related to at least one of the one or more attributes of a crowd, multiple vehicles, animal swarms, drone swarms, or other collections of objects.

[0142] In one embodiment, the radio frequency sensing assistance data is received via one or more LTE positioning protocol (LPP) messages, one or more radio resource control (RRC) messages, or one or more IP messages or TCP / IP messages. In one embodiment, the radio frequency sensing results are reported to the server in one or more LTE positioning protocol (LPP) messages, one or more radio resource control (RRC) messages, or one or more IP messages or TCP / IP messages.

[0143] refer to Fig.17 , and further reference Figures 1 to 15 , a method 1700 for performing environmental detection at a server using radio frequency sensing includes the stages shown. In one example, RF sensing can be performed using multiple wireless devices (e.g., UE 105, 106, 200 and / or TRP 300). However, method 1700 is an example and not a limitation. For example, method 1700 can be changed by adding, removing, rearranging, combining, performing stages simultaneously, and / or dividing a single stage into multiple stages. Method 1700 can be performed by a server such as LMF 120, server 400, or an external client or server 130.

[0144] At stage 1702, the method includes providing radio frequency sensing assistance data to one or more wireless devices. The server 400 including the processor 410 and the transceiver 415 is a component for providing RF sensing assistance data. In one example, the server 400 can be configured to provide RF sensing assistance data messages 858 to multiple wireless devices (such as UE 852). The RF sensing assistance data may include RF sensing configuration information to enable the wireless devices to jointly perform RF sensing operations. For example, the RF sensing assistance data may include geographic information (such as sector information for defining where the wireless device will perform RF sensing), and transmitter configuration information (such as beam configuration information for reducing cross-interference of RF sensing signals). The RF sensing operation may utilize OFDM, UWB, LTF, L-LTF, and HT technologies, and the RF sensing assistance data may include orthogonal frequency division multiplexing configuration information, such as communication packet preamble information. In one example, the RF sensing assistance data may include timing information, RF signature information, and / or attribute information associated with a potential target object to assist the wireless device in performing a radio frequency sensing operation (e.g., a radio frequency sensing operation of a potential target object). Attribute information may include expected location (e.g., range / azimuth), movement (e.g., speed / direction), size, and / or other frequency domain characteristics to assist in identifying and tracking potential target objects. The RF sensing assistance data may include information associated with stationary objects whose locations are known and that are proximate to the location of the wireless device. Other information elements may also be included in the RF sensing assistance data. In stage 1702, the RF sensing assistance data may be provided via one or more LTE Positioning Protocol (LPP) messages, one or more Radio Resource Control (RRC) messages, or one or more IP or TCP / IP messages.

[0145] At stage 1704, the method includes receiving one or more radio frequency sensing reports from one or more wireless devices. For example, the server may provide an indication (e.g., as part of radio frequency sensing assistance data) to each of the plurality of wireless devices to perform a radio frequency sensing operation, after which the plurality of wireless devices may send radio frequency sensing reports back to the server. The server 400, including the processor 410 and the transceiver 415, is a component for receiving the RF sensing report. The plurality of wireless devices may be configured to provide an RF sensing report message 862 based on performing the RF sensing operation. In one example, the plurality of wireless devices may be configured to determine an attribute associated with the target object based on the received RF signal, such as size, direction of motion, range, orientation (e.g., direction of boresight), elevation (e.g., in a 3D implementation), speed, or a combination thereof. The RF sensing report may include attributes, such as one or more attributes associated with the object. In one example, the plurality of wireless devices may provide RF signal information in the RF sensing report, such as a time-based component and a frequency-based component, and the server 400 may be configured to determine additional attributes based on the RF signal information. The RF sensing report may include sensor data obtained by multiple wireless devices, where the sensor data may include images from a visible light based camera or an infrared camera. The information in the RF sensing report may be stored by the server in one or more data structures (such as data structure 1300).

[0146] At stage 1706, the method includes determining one or more environmental characteristics based at least in part on the one or more RF sensing reports, e.g., Figure 8C The server 400 including the processor 410 is a component for determining one or more environmental characteristics. The environmental characteristics may include or be based on the density of objects in the synthesized results, the direction of movement of objects in the synthesized results, or one or more other attributes of objects in the synthesized results. For example, characteristics regarding crowd size, crowd movement, traffic flow, or building exits (e.g., to build an evacuation plan for a building on fire) may be obtained based on the synthesized results. Fig. 14B , the environmental characteristics can be based on the density of objects 1412a, 1412b, 1412d near the first user 1406 and the third user 1408. The crowd density can be inferred based on the movement of the objects 1412a, 1412b, 1412d to indicate a higher pedestrian flow (e.g., if the objects are moving), or the crowd size of the event, traffic flow. Based on the RF signal, other environmental characteristics can be inferred, such as the number of adults (e.g., large people) and the number of children (e.g., small people) in the crowd. Other environmental characteristics can also be determined based on the object classification results.

[0147] In one example, determining one or more environmental characteristics at stage 1706 may include aggregating radio frequency sensing reports (e.g., Fig. 7A , Figure 7B , Figure 8C , Fig. 9 and Fig.13 4 ). The server 400 including the processor 410 and the transceiver 415 is a component for aggregating the radio frequency sensing reports. Aggregating the radio frequency sensing reports may include determining a composite result based on the radio frequency sensing reports. In an example, the server 400 may be configured to query the data structure 1300 based on the location, location area, UEID, time, time period, and / or other fields to aggregate the radio frequency sensing reports and / or determine the composite result. For example, referring to Fig. 14B , the server 400 may query the data structure 1300 based on the location area associated with the composite map 1454 to determine the location of the UEs 1406, 1408, 1410 and the corresponding target objects 1412a-d. The server 400 may query the data structure 1300 based on a time period to determine the location of the UEs 1406, 1408, 1410 and the corresponding target objects 1412a-d during the time period. The server 400 may determine the location of the target object using relevant fields in the object table 1308 (e.g., ranging, orientation, attributes, etc.) and / or the signal table 1306 (e.g., line of sight, time and / or frequency components). The target object may be drawn on a global coordinate system based on the location of the UEs 1406, 1408, 1410 (e.g., latitude / longitude / altitude). The server 400 may also use the associated fields in the data structure 1300 to further classify the target object. For example, a machine learning method may be used to classify the target object based on the attributes of the reflected RF signal.

[0148] In one embodiment, the one or more environmental characteristics determined in stage 1708 include at least one of the following: tracking the movement or position of a person, vehicle, animal, drone, or other object, or both; determining one or more attributes of a person, vehicle, animal, drone, or other object; and determining one or more attributes of a crowd, multiple vehicles, animal swarm, drone swarm, or other collection of objects. The one or more attributes of a person, vehicle, animal, drone, or other object may include horizontal position, altitude, speed, orientation, size, height, width, length, weight, type, brand, model, type, orientation, posture, gait, clothing type, carrying of a bag or parcel, or some combination of these. The one or more attributes of a crowd, multiple vehicles, animal swarm, drone swarm, or other collection of objects may include location, location area, density, number, rate of increase in number, rate of decrease in number, average speed, statistical direction of movement, or some combination of these. The server may also include information related to at least one of the movement, position, or one or more attributes of a person, vehicle, animal, drone, or other object in the radio frequency sensing assistance data provided in stage 1702. The server may also or alternatively include information related to at least one of one or more attributes of a crowd, a plurality of vehicles, a swarm of animals, a swarm of drones, or other collection of objects in the radio frequency sensing assistance data provided at stage 1702 .

[0149] Other examples and implementations are within the scope of this disclosure and the appended claims. For example, due to the nature of software and computers, the functions described above can be implemented using software, hardware, firmware, hard wiring, or any combination thereof executed by a processor. Features that implement the functions can also be physically located in different locations, including being distributed so that parts of the functions are implemented in different physical locations. Unless otherwise stated, functional or other components shown in the drawings and / or discussed herein that are connected or communicated with each other are communicatively coupled. That is, they can be connected directly or indirectly to enable communication between them.

[0150] Unless the context clearly indicates otherwise, as used herein, the singular forms "a", "an", and "the" also include the plural forms. For example, "a processor" may include one processor or a plurality of processors. As used herein, the terms "comprises" and / or "comprising" specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or combinations thereof.

[0151] Unless otherwise stated, as used herein, a statement that a function or operation is "based on" an item or condition means that the function or operation is based on the stated item or condition, and may be based on one or more items and / or conditions other than the stated item or condition.

[0152] In addition, as used herein, "or" used in a list of items (which may begin with "at least one" or begin with "one or more") indicates a separate list, so that, for example, a list of "at least one of A, B, or C" or a list of "one or more of A, B, or C" or a list of "A, B, or C" means A, B, C, AB (A and B), AC (A and C), BC (B and C), ABC (i.e., A and B and C), or a combination having more than one feature (e.g., AA, AAB, ABBC, etc.). Therefore, a statement that an item (e.g., a processor) is configured to perform a function with respect to at least one of A or B, or a statement that an item is configured to perform function A or function B, means that the item can be configured to perform the function with respect to A, or can be configured to perform the function with respect to B, or can be configured to perform the functions with respect to both A and B. For example, the phrase "a processor configured to measure at least one of A or B" or "a processor configured to measure A or measure B" means that the processor can be configured to measure A (and can be configured to measure B or not measure B), or can be configured to measure B (and can be configured to measure A or not measure A), or can be configured to measure A and B (and can be configured to select which one or both of A and B to measure). Similarly, a description of a component for measuring at least one of A or B includes a component for measuring A (which can measure B or not measure B), or a component for measuring B (and can be configured to measure A or not measure A), or a component for measuring A and B (which can select which one or both of A and B to measure). As another example, a description of an item (e.g., a processor) being configured to perform at least one of function X or perform function Y means that the item can be configured to perform function X, or can be configured to perform function Y, or can be configured to perform function X and perform function Y. For example, the phrase "a processor configured to measure at least one of X or Y" means that the processor can be configured to measure X (and can be configured to measure Y or not measure Y), or can be configured to measure Y (and can be configured to measure X or not measure X), or can be configured to measure X and measure Y (and can be configured to select which one or both of X and Y to measure). Substantial changes can be made based on specific requirements. For example, customized hardware can also be used, and / or specific elements can be implemented in hardware, software executed by the processor (including portable software, such as applets, etc.), or both. Further, connections to other computing devices such as network input / output devices can be used.

[0153] The systems and devices discussed above are examples. Various operations may be appropriately omitted, replaced, or added to various processes or components. For example, features described with respect to certain configurations may be combined in various other configurations. Different aspects and elements of a configuration may be combined in a similar manner. In addition, technology is developing, so many elements are examples, and these elements do not limit the scope of this disclosure or the claims.

[0154] A wireless communication system is a system that transmits communications wirelessly, i.e., by propagation of electromagnetic waves and / or sound waves in air space, rather than through wires or other physical connections. A wireless communication network may not send all communications wirelessly, but is configured to send at least some communications wirelessly. Further, the term "wireless communication device" or similar terms does not require that the function of the device is exclusively or even primarily for communication, or that the device is a mobile device, but rather indicates that the device includes wireless communication capabilities (unidirectional or bidirectional), for example, including at least one radio component for wireless communication (each radio component is part of a transmitter, receiver or transceiver).

[0155] Specific details are given in the description to provide a comprehensive understanding of example configurations (including implementations). However, the configuration can be implemented without these specific details. For example, in order to avoid confusing these configurations, well-known circuits, processes, algorithms, structures and techniques have been shown without unnecessary details. This description provides example configurations and does not limit the scope, applicability or configuration of the claims. On the contrary, the above description of the configuration provides a description of the technology described in the implementation. Various changes can be made to the functions and arrangements of the elements without departing from the spirit or scope of the present disclosure.

[0156] As used herein, the terms "processor-readable medium," "machine-readable medium," and "computer-readable medium" refer to any medium that participates in providing data that causes a machine to operate in a particular manner. Using a computing platform, various processor-readable media may involve providing instructions / codes to a processor for execution, and / or may be used to store and / or carry such instructions / codes (e.g., as signals). In many embodiments, processor-readable media are physical and / or tangible storage media. Such media may take many forms, including, but not limited to, non-volatile media and volatile media. For example, non-volatile media include optical disks and / or magnetic disks. Volatile media include, but are not limited to, dynamic memory.

[0157] A statement that a value exceeds (or is greater than or above) a first threshold is equivalent to a statement that the value meets or exceeds a second threshold that is slightly greater than the first threshold, e.g., at the resolution of the computing system, the second threshold is a value higher than the first threshold. A statement that a value is less than (or within or below the first threshold) a first threshold is equivalent to a statement that the value is less than or equal to a second threshold that is slightly less than the first threshold, e.g., at the resolution of the computing system, the second threshold is a value lower than the first threshold.

[0158] The following numbered clauses describe examples of implementation:

[0159] Clause 1. A method at a wireless device for crowdsourcing radio frequency sensing data, comprising: receiving radio frequency sensing assistance data from a server; performing a radio frequency sensing operation based at least in part on the radio frequency sensing assistance data; and reporting radio frequency sensing results to the server.

[0160] Clause 2. The method of clause 1, wherein the radio frequency sensing results are used to determine one or more environmental characteristics.

[0161] Clause 3. The method of clause 2, wherein the radio frequency sensing results are aggregated with a plurality of radio frequency sensing results received from a plurality of wireless devices, and the one or more environmental characteristics are determined based on the aggregation of the radio frequency sensing results.

[0162] Clause 4. The method of clause 2, wherein the one or more environmental characteristics include movement of the target object, location of the target object, one or more attributes of the target object, or any combination thereof.

[0163] Clause 5. A method according to clause 4, wherein one or more attributes of the target object include horizontal position, altitude, speed, orientation, size, height, width, length, weight, type, brand, model, type, orientation, posture, gait, type of clothing, carrying of bags or packages, location area, density, number, rate of increase in number, rate of decrease in number, average speed, statistical direction of movement, or any combination thereof.

[0164] Clause 6. The method of clause 1, wherein the radio frequency sensing assistance data comprises information related to at least one of movement and position of the target object.

[0165] Clause 7. The method of clause 1, wherein the radio frequency sensing assistance data comprises information related to one or more attributes of the target object.

[0166] Clause 8. The method of clause 1, wherein the radio frequency sensing assistance data includes geographic information, and performing the radio frequency sensing operation is based at least in part on the geographic information.

[0167] Clause 9. The method of clause 1, wherein the radio frequency sensing assistance data comprises transmitter configuration information, and performing the radio frequency sensing operation is based at least in part on the transmitter configuration information.

[0168] Clause 10. The method of clause 1, wherein the radio frequency sensing assistance data comprises orthogonal frequency division multiplexing configuration information, and performing the radio frequency sensing operation is based at least in part on the orthogonal frequency division multiplexing configuration information.

[0169] Clause 11. The method of clause 1, wherein the radio frequency sensing assistance data comprises RF signature or attribute information associated with one or more potential target objects, and performing the radio frequency sensing operation is based at least in part on the RF signature or attribute information.

[0170] Clause 12. The method of clause 1, wherein the radio frequency sensing assistance data includes timing information, and performing the radio frequency sensing operation is based at least in part on the timing information.

[0171] Clause 13. The method of clause 1, wherein performing a radio frequency sensing operation comprises transmitting one or more radio frequency signals.

[0172] Clause 14. The method of clause 1, wherein performing radio frequency sensing operations comprises receiving one or more radio frequency signals transmitted by neighboring wireless nodes.

[0173] Clause 15. The method of clause 1, wherein performing the radio frequency sensing operation comprises detecting one or more stationary target objects.

[0174] Clause 16. The method of clause 15, wherein the radio frequency sensing assistance data comprises location information associated with one or more stationary target objects.

[0175] Clause 17. The method of clause 1, further comprising determining one or more attributes associated with the target object based on the radio frequency sensing operation.

[0176] Clause 18. The method of clause 17, wherein the one or more attributes associated with the target object include range, orientation, elevation, size, speed, direction of motion, or any combination thereof.

[0177] Clause 19. The method of clause 17, wherein reporting the radio frequency sensing results comprises reporting one or more attributes associated with the target object.

[0178] Clause 20. The method of clause 1, wherein reporting the RF sensing result comprises reporting RF signal information based on the RF sensing operation.

[0179] Clause 21. The method of clause 20, wherein the radio frequency signal information comprises a time-based component, a frequency-based component, or both.

[0180] Clause 22. The method of clause 1 further comprising obtaining sensor data, and reporting the radio frequency sensing results comprises reporting the sensor data.

[0181] Clause 23. The method of clause 22, wherein the sensor data comprises images from a visible light based camera or an infrared camera.

[0182] Clause 24. The method of clause 1, wherein the radio frequency sensing assistance data is received via one or more LTE Positioning Protocol (LPP) messages.

[0183] Clause 25. The method of clause 1, wherein the radio frequency sensing assistance data is received via one or more radio resource control (RRC) messages or one or more IP messages or TCP / IP messages.

[0184] Clause 26. A method for performing environmental detection at a server using radio frequency sensing, comprising: providing radio frequency sensing assistance data to one or more wireless devices; receiving one or more radio frequency sensing reports from one or more wireless devices; and determining one or more environmental characteristics based at least in part on the one or more radio frequency sensing reports.

[0185] Clause 27. The method of clause 26, wherein determining one or more environmental characteristics comprises aggregating one or more radio frequency sensing reports.

[0186] Clause 28. A method according to clause 27, wherein one or more environmental characteristics include the movement or position or both of a person, vehicle, animal, drone or other target object, one or more attributes of a person, vehicle, animal, drone or other target object, one or more attributes of a crowd, multiple vehicles, a group of animals, a group of drones or other collection of target objects.

[0187] Clause 29. A method according to clause 28, wherein one or more attributes of the person, vehicle, animal, drone, or other target object include horizontal position, altitude, speed, orientation, size, height, width, length, weight, type, brand, model, type, orientation, posture, gait, clothing type, bag or package carried, or any combination thereof.

[0188] Clause 30. A method according to clause 28, wherein one or more attributes of a crowd, multiple vehicles, a group of animals, a group of drones, or other collection of target objects include location area, density, number, rate of increase in number, rate of decrease in number, average speed, statistical direction of movement, or any combination thereof.

[0189] Clause 31. The method of clause 28, wherein the radio frequency sensing assistance data comprises information related to at least one of movement, location, or one or more attributes of a person, vehicle, animal, drone, or other target object.

[0190] Clause 32. The method of clause 28 further includes including information related to at least one of one or more attributes of a crowd, a plurality of vehicles, a swarm of animals, a swarm of drones, or other collection of target objects in the radio frequency sensing assistance data.

[0191] Clause 33. The method of clause 26, wherein the radio frequency sensing assistance data includes geographic information.

[0192] Clause 34. The method of clause 26, wherein the radio frequency sensing assistance data comprises transmitter configuration information.

[0193] Clause 35. The method of clause 26, wherein the radio frequency sensing assistance data comprises orthogonal frequency division multiplexing configuration information.

[0194] Clause 36. The method of clause 26, wherein the radio frequency sensing assistance data comprises RF signature information, attribute information, or both associated with the potential target object.

[0195] Clause 37. The method of clause 26, wherein the radio frequency sensing assistance data comprises timing information for performing radio frequency sensing operations.

[0196] Clause 38. The method of clause 26, further comprising storing information contained in the one or more radio frequency sensing reports in a data structure.

[0197] Clause 39. The method of clause 38, wherein aggregating the one or more radio frequency sensing reports comprises querying a data structure based on a location area.

[0198] Clause 40. The method of clause 38, wherein aggregating the one or more radio frequency sensing reports comprises querying a data structure based on a time period.

[0199] Clause 41. The method of Clause 26, wherein the one or more radio frequency sensing reports include one or more attributes associated with the target object.

[0200] Clause 42. The method of clause 41, wherein the one or more attributes associated with the target object include range, orientation, elevation, size, speed, direction of motion, or any combination thereof.

[0201] Clause 43. The method of clause 26, wherein the one or more RF sensing reports include RF signal information based on RF sensing operations performed by the one or more wireless devices.

[0202] Clause 44. The method of clause 43, wherein the radio frequency signal information comprises a time-based component, a frequency-based component, or both.

[0203] Clause 45. The method of clause 26, wherein the one or more radio frequency sensing reports include sensor data obtained by one or more wireless devices.

[0204] Clause 46. The method of clause 45, wherein the sensor data comprises images from a visible light based camera or an infrared camera.

[0205] Clause 47. The method of clause 26, wherein the radio frequency sensing assistance data is provided via one or more LTE Positioning Protocol (LPP) messages.

[0206] Clause 48. The method of clause 26, wherein the radio frequency sensing assistance data is provided via one or more radio resource control (RRC) messages or one or more IP or TCP / IP messages.

[0207] Clause 49. The method of clause 26, wherein determining one or more environmental characteristics comprises determining a density of target objects.

[0208] Clause 50. The method of clause 26, wherein determining one or more environmental characteristics comprises determining a direction of motion of the target object.

[0209] Clause 51. The method of clause 26, wherein determining one or more environmental characteristics comprises determining one or more attributes of the target object.

[0210] Clause 52. An apparatus comprising: a memory; at least one transceiver; at least one processor, communicatively coupled to the memory and the at least one transceiver, and configured to: receive radio frequency sensing assistance data from a server; perform radio frequency sensing operations based at least in part on the radio frequency sensing assistance data; and report radio frequency sensing results to the server.

[0211] Clause 53. The apparatus of clause 52, wherein the radio frequency sensing results are used to determine one or more environmental characteristics.

[0212] Clause 54. The apparatus of clause 53, wherein the radio frequency sensing result is aggregated with a plurality of radio frequency sensing results received from a plurality of wireless devices, and the one or more environmental characteristics are determined based on the aggregation of the radio frequency sensing results.

[0213] Clause 55. The apparatus of clause 53, wherein the one or more environmental characteristics include movement of the target object, location of the target object, one or more attributes of the target object, or any combination thereof.

[0214] Clause 56. An apparatus according to clause 55, wherein one or more attributes of the target object include horizontal position, altitude, speed, orientation, size, height, width, length, weight, type, brand, model, type, orientation, posture, gait, type of clothing, carrying of bags or packages, location area, density, number, rate of increase in number, rate of decrease in number, average speed, statistical direction of movement, or any combination thereof.

[0215] Clause 57. The apparatus of clause 52, wherein the radio frequency sensing assistance data comprises information related to at least one of movement, position, or any combination thereof of the target object.

[0216] Clause 58. The apparatus of clause 52, wherein the radio frequency sensing assistance data comprises information related to one or more attributes of the target object.

[0217] Clause 59. The apparatus of clause 52, wherein the radio frequency sensing assistance data comprises geographic information, and the at least one processor is further configured to perform radio frequency sensing operations based at least in part on the geographic information.

[0218] Clause 60. The apparatus of clause 52, wherein the radio frequency sensing assistance data comprises transmitter configuration information, and the at least one processor is further configured to perform radio frequency sensing operations based at least in part on the transmitter configuration information.

[0219] Clause 61. The apparatus of clause 52, wherein the radio frequency sensing assistance data comprises orthogonal frequency division multiplexing configuration information, and the at least one processor is further configured to perform a radio frequency sensing operation based at least in part on the orthogonal frequency division multiplexing configuration information.

[0220] Clause 62. The apparatus of clause 52, wherein the radio frequency sensing assistance data comprises RF signature or attribute information associated with one or more potential target objects, and the at least one processor is further configured to perform radio frequency sensing operations based at least in part on the RF signature or attribute information.

[0221] Clause 63. The apparatus of clause 52, wherein the radio frequency sensing assistance data comprises timing information, and the at least one processor is further configured to perform a radio frequency sensing operation based at least in part on the timing information.

[0222] Clause 64. The apparatus of clause 52, wherein the at least one processor is further configured to transmit one or more radio frequency signals to perform a radio frequency sensing operation.

[0223] Clause 65. The apparatus of clause 52, wherein the at least one processor is further configured to receive one or more radio frequency signals transmitted by neighboring wireless nodes to perform radio frequency sensing operations.

[0224] Clause 66. The apparatus of clause 52, wherein the at least one processor is further configured to detect one or more stationary objects based at least in part on the radio frequency sensing operation.

[0225] Clause 67. The apparatus of clause 66, wherein the radio frequency sensing assistance data comprises location information associated with one or more stationary objects.

[0226] Clause 68. The apparatus of clause 52, wherein the at least one processor is further configured to determine one or more attributes associated with the target object based on the radio frequency sensing operation.

[0227] Clause 69. The apparatus of clause 68, wherein the one or more attributes associated with the target object include range, position, elevation, size, speed, direction of motion, or any combination thereof.

[0228] Clause 70. The apparatus of clause 68, wherein the at least one processor is further configured to report one or more attributes associated with the target object.

[0229] Clause 71. The apparatus of clause 52, wherein the at least one processor is further configured to report radio frequency signal information based on the radio frequency sensing operation.

[0230] Clause 72. The apparatus of clause 71, wherein the radio frequency signal information comprises a time-based component, a frequency-based component, or both.

[0231] Clause 73. The apparatus of clause 72, wherein the at least one processor is further configured to obtain sensor data and report the sensor data.

[0232] Clause 74. The apparatus of clause 73, wherein the sensor data comprises images from a visible light based camera or an infrared camera.

[0233] Clause 75. The apparatus of clause 52, wherein the radio frequency sensing assistance data is received via one or more LTE Positioning Protocol (LPP) messages.

[0234] Clause 76. The apparatus of clause 52, wherein the radio frequency sensing assistance data is received via one or more radio resource control (RRC) messages or one or more IP messages or TCP / IP messages.

[0235] Clause 77. An apparatus comprising: a memory; at least one transceiver; at least one processor, communicatively coupled to the memory and the at least one transceiver, and configured to: provide RF sensing assistance data to one or more wireless devices; receive one or more RF sensing reports from one or more wireless devices; and determine one or more environmental characteristics based at least in part on the one or more RF sensing reports.

[0236] Clause 78. The apparatus of clause 77, wherein the at least one processor is further configured to aggregate the one or more radio frequency sensing reports to determine one or more environmental characteristics.

[0237] Clause 79. An apparatus according to clause 77, wherein, in order to determine one or more environmental characteristics, at least one processor is further configured to perform one or more of the following: tracking the movement or location or both of a person, vehicle, animal, drone, or other target object; determining one or more attributes of a person, vehicle, animal, drone, or other target object; and determining one or more attributes of a crowd, multiple vehicles, a group of animals, a group of drones, or a collection of other target objects.

[0238] Clause 80. A device according to clause 79, wherein one or more attributes of the person, vehicle, animal, drone, or other target object include horizontal position, altitude, speed, orientation, size, height, width, length, weight, type, brand, model, kind, orientation, posture, gait, type of clothing, carrying of a bag or package, or any combination thereof.

[0239] Clause 81. An apparatus according to clause 79, wherein one or more attributes of a crowd, a plurality of vehicles, a swarm of animals, a swarm of drones, or other collection of target objects include location area, density, number, rate of increase in number, rate of decrease in number, average speed, statistical direction of movement, or any combination thereof.

[0240] Clause 82. An apparatus according to clause 79, wherein at least one processor is further configured to provide information related to at least one of the movement, location, or one or more attributes of a person, vehicle, animal, drone, or other target object in the radio frequency sensing assistance data.

[0241] Clause 83. An apparatus according to clause 79, wherein at least one processor is further configured to provide in the radio frequency sensing assistance data information related to at least one of one or more attributes of a crowd, a plurality of vehicles, a herd of animals, a swarm of drones, or other collection of target objects.

[0242] Clause 84. The apparatus of clause 77, wherein the radio frequency sensing assistance data comprises geographic information.

[0243] Clause 85. The apparatus of clause 77, wherein the radio frequency sensing assistance data comprises transmitter configuration information.

[0244] Clause 86. The apparatus of clause 77, wherein the radio frequency sensing assistance data comprises orthogonal frequency division multiplexing configuration information.

[0245] Clause 87. The apparatus of clause 77, wherein the radio frequency sensing assistance data comprises RF signature information, attribute information, or both associated with the potential target object.

[0246] Clause 88. The apparatus of clause 77, wherein the radio frequency sensing assistance data comprises timing information for performing radio frequency sensing operations.

[0247] Clause 89. The apparatus of clause 77, further comprising storing information contained in one or more radio frequency sensing reports in a data structure.

[0248] Clause 90. The apparatus of clause 89, wherein the at least one processor is further configured to query the data structure based on the location area.

[0249] Clause 91. The apparatus of clause 89, wherein the at least one processor is further configured to query the data structure based on a time period.

[0250] Clause 92. The apparatus of clause 77, wherein the one or more radio frequency sensing reports include one or more attributes associated with the target object.

[0251] Clause 93. The apparatus of clause 92, wherein the one or more attributes associated with the target object include range, position, elevation, size, speed, direction of motion, or a combination thereof.

[0252] Clause 94. The apparatus of clause 77, wherein the one or more RF sensing reports include RF signal information based on RF sensing operations performed by the one or more wireless devices.

[0253] Clause 95. The apparatus of clause 94, wherein the radio frequency signal information comprises a time-based component, a frequency-based component, or both.

[0254] Clause 96. The apparatus of clause 77, wherein the one or more radio frequency sensing reports include sensor data obtained by one or more wireless devices.

[0255] Clause 97. The apparatus of clause 96, wherein the sensor data comprises images from a visible light based camera or an infrared camera.

[0256] Clause 98. The apparatus of clause 77, wherein the radio frequency sensing assistance data is provided via one or more LTE Positioning Protocol (LPP) messages.

[0257] Clause 99. The apparatus of clause 77, wherein the radio frequency sensing assistance data is provided via one or more radio resource control (RRC) messages or one or more IP or TCP / IP messages.

[0258] Clause 100. The apparatus of clause 77, wherein the at least one processor is further configured to determine a density of the target object.

[0259] Clause 101. The apparatus of clause 77, wherein the at least one processor is further configured to determine a direction of motion of the target object.

[0260] Clause 102. The apparatus of clause 77, wherein the at least one processor is further configured to determine one or more attributes of the target object.

[0261] Clause 103. The apparatus of clause 77, wherein the at least one processor is further configured to provide instructions to one or more wireless devices to perform radio frequency sensing operations.

[0262] Clause 104. An apparatus for crowdsourcing radio frequency sensing, comprising: means for receiving radio frequency sensing assistance data from a server; means for performing radio frequency sensing operations based at least in part on the radio frequency sensing assistance data; and means for reporting radio frequency sensing results to the server.

[0263] Clause 105. An apparatus for performing environmental detection at a server using radio frequency sensing, comprising: a component for providing radio frequency sensing assistance data to one or more wireless devices; a component for receiving one or more radio frequency sensing reports from one or more wireless devices; and a component for determining one or more environmental characteristics based at least in part on the one or more radio frequency sensing reports.

[0264] Item 106. A non-transitory processor-readable storage medium comprising processor-readable instructions configured to cause one or more processors to crowdsource radio frequency sensing, including code for: receiving radio frequency sensing assistance data from a server; performing radio frequency sensing operations based at least in part on the radio frequency sensing assistance data; and reporting radio frequency sensing results to the server.

[0265] Clause 107. A non-transitory processor-readable storage medium comprising processor-readable instructions, the processor-readable instructions being configured to cause one or more processors to detect environmental characteristics using radio frequency sensing, including code for performing the following operations: providing radio frequency sensing assistance data to one or more wireless devices; receiving one or more radio frequency sensing reports from one or more wireless devices; and determining one or more environmental characteristics based at least in part on the one or more radio frequency sensing reports.

Claims

1. A method for crowdsourcing radio frequency sensing data at a wireless device, comprising: receiving radio frequency sensing assistance data from a server; performing a radio frequency sensing operation based at least in part on the radio frequency sensing assistance data; as well as The radio frequency sensing result is reported to the server.

2. The method according to claim 1, wherein: The radio frequency sensing results are used to determine one or more environmental characteristics.

3. The method according to claim 2, wherein: The radio frequency sensing result is aggregated with a plurality of radio frequency sensing results received from a plurality of wireless devices, and the one or more environmental characteristics are determined based on the aggregation of the radio frequency sensing results.

4. The method according to claim 2, wherein: The one or more environmental characteristics include movement of a target object, a position of the target object, one or more attributes of the target object, or any combination thereof.

5. The method according to claim 4, wherein: The one or more attributes of the target object include horizontal position, altitude, speed, orientation, size, height, width, length, weight, type, brand, model, kind, orientation, posture, gait, clothing type, bags or packages carried, location area, density, number, rate of increase in number, rate of decrease in number, average speed, statistical direction of movement, or any combination thereof.

6. The method according to claim 1, wherein: The radio frequency sensing assistance data includes information related to at least one of movement, position, or any combination thereof of the target object.

7. The method according to claim 1, wherein: The radio frequency sensing assistance data includes information related to one or more attributes of the target object.

8. The method according to claim 1, wherein: The radio frequency sensing assistance data includes geographic information, and performing the radio frequency sensing operation is based at least in part on the geographic information.

9. The method according to claim 1, wherein: The radio frequency sensing assistance data includes RF signatures or attribute information associated with one or more potential target objects, and performing the radio frequency sensing operation is based at least in part on the RF signatures or attribute information.

10. The method according to claim 1, wherein: The radio frequency sensing assistance data is received via one or more radio resource control (RRC) messages or one or more IP messages or TCP / IP messages.

11. A method for performing environmental detection at a server using radio frequency sensing, comprising: providing radio frequency sensing assistance data to one or more wireless devices; receiving one or more radio frequency sensing reports from the one or more wireless devices; as well as One or more environmental characteristics are determined based at least in part on the one or more radio frequency sensing reports.

12. The method according to claim 11, wherein: Determining the one or more environmental characteristics includes aggregating the one or more radio frequency sensing reports.

13. The method according to claim 11, wherein: The one or more environmental characteristics include movement of a target object, a position of the target object, one or more attributes of the target object, or any combination thereof.

14. The method according to claim 13, wherein: The one or more attributes of the target object include horizontal position, altitude, speed, orientation, size, height, width, length, weight, type, brand, model, kind, orientation, posture, gait, clothing type, bags or packages carried, location area, density, number, rate of increase in number, rate of decrease in number, average speed, statistical direction of movement, or any combination thereof.

15. The method according to claim 11, wherein: The radio frequency sensing assistance data includes information related to at least one of movement, location, one or more attributes of the target object, or any combination thereof.

16. The method according to claim 11, wherein: The radio frequency sensing assistance data includes geographic information.

17. The method according to claim 11, wherein: The radio frequency sensing assistance data includes RF signature information, attribute information, or both associated with the potential target object.

18. The method according to claim 11, wherein: The one or more radio frequency sensing reports include sensor data obtained by the one or more wireless devices.

19. The method according to claim 11, wherein: The radio frequency sensing assistance data is provided via one or more radio resource control (RRC) messages or one or more IP or TCP / IP messages.

20. An apparatus comprising: Memory; at least one transceiver; at least one processor, communicatively coupled to the memory and the at least one transceiver, and configured to: receiving radio frequency sensing assistance data from a server; performing a radio frequency sensing operation based at least in part on the radio frequency sensing assistance data; as well as The radio frequency sensing result is reported to the server.

21. The device according to claim 20, wherein: The radio frequency sensing results are used to determine one or more environmental characteristics.

22. The device according to claim 21, wherein The radio frequency sensing result is aggregated with a plurality of radio frequency sensing results received from a plurality of wireless devices, and the one or more environmental characteristics are determined based on the aggregation of the radio frequency sensing results.

23. The device according to claim 21, wherein The one or more environmental characteristics include movement of a target object, a position of the target object, one or more attributes of the target object, or any combination thereof.

24. The device according to claim 23, wherein: The one or more attributes of the target object include horizontal position, altitude, speed, orientation, size, height, width, length, weight, type, brand, model, kind, orientation, posture, gait, clothing type, bags or packages carried, location area, density, number, rate of increase in number, rate of decrease in number, average speed, statistical direction of movement, or any combination thereof.

25. The device according to claim 20, wherein: The radio frequency sensing assistance data includes information related to at least one of movement, position, or any combination thereof of the target object.

26. The device according to claim 20, wherein: The radio frequency sensing assistance data includes information related to one or more attributes of the target object.

27. The device according to claim 20, wherein: The radio frequency sensing assistance data includes geographic information, and the at least one processor is further configured to perform the radio frequency sensing operation based at least in part on the geographic information.

28. The device according to claim 20, wherein: The radio frequency sensing assistance data includes transmitter configuration information, and the at least one processor is further configured to perform the radio frequency sensing operation based at least in part on the transmitter configuration information.

29. The device according to claim 20, wherein: The radio frequency sensing assistance data includes RF signatures or attribute information associated with one or more potential target objects, and the at least one processor is further configured to perform the radio frequency sensing operation based at least in part on the RF signatures or attribute information.

30. The device according to claim 20, wherein: The radio frequency sensing assistance data is received via one or more radio resource control (RRC) messages or one or more IP messages or TCP / IP messages.

31. An apparatus comprising: Memory; at least one transceiver; at least one processor, communicatively coupled to the memory and the at least one transceiver, and configured to: providing radio frequency sensing assistance data to one or more wireless devices; receiving one or more radio frequency sensing reports from the one or more wireless devices; as well as One or more environmental characteristics are determined based at least in part on the one or more radio frequency sensing reports.

32. The device according to claim 31, wherein The at least one processor is further configured to aggregate the one or more radio frequency sensing reports to determine the one or more environmental characteristics.

33. The device according to claim 31, wherein The one or more environmental characteristics include movement of a target object, a position of the target object, one or more attributes of the target object, or any combination thereof.

34. The device according to claim 33, wherein: The one or more attributes of the target object include horizontal position, altitude, speed, orientation, size, height, width, length, weight, type, brand, model, kind, orientation, posture, gait, clothing type, bags or packages carried, location area, density, number, rate of increase in number, rate of decrease in number, average speed, statistical direction of movement, or any combination thereof.

35. The device according to claim 31, wherein The radio frequency sensing assistance data includes geographic information.

36. The device according to claim 31, wherein The radio frequency sensing assistance data includes RF signature information, attribute information, or both associated with the potential target object.

37. The device according to claim 31, wherein The radio frequency sensing assistance data includes timing information for performing a radio frequency sensing operation.

38. The apparatus of claim 31, wherein: The one or more radio frequency sensing reports include radio frequency signal information based on radio frequency sensing operations performed by the one or more wireless devices.

39. The device according to claim 38, wherein The radio frequency signal information includes a time-based component, a frequency-based component, or both.

40. The device according to claim 31, wherein The radio frequency sensing assistance data is provided via one or more radio resource control (RRC) messages or one or more IP or TCP / IP messages.

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