Wireless sensing and communication system with matching functionality for improved interoperability

Abstract

The present invention relates to a sensing and communication system for sensing a target (object or person) in an environment, wherein first realistic sensing data of the target collected by a first device is used to generate synthetic data that simulates second realistic sensing data to be generated by a second device of the same target. The synthesized data is then used to determine whether the second realistic sensing data collected by the second device matches the first realistic sensing data collected by the first device, such that it can be confirmed whether both devices are sensing or have sensed the same target, or an object in the field of view of the device (e.g., AR glasses).

Description

Technical Field

[0001] The present invention relates to the field of integrated sensing and communications (ISAC) in wireless networks, such as but not limited to fifth generation (5G) cellular communication systems. Background Art

[0002] As the wavelength of communication systems decreases, the ability to use the same wavelength band for increasingly precise sensing applications improves.

[0003] So-called millimeter-wave radar is a contactless sensing technology used to detect objects and provide their range, velocity, and angle, operating in the spectrum between 30 GHz and 300 GHz. Because the technology uses small wavelengths, it can provide submillimeter accuracy and is able to penetrate certain materials, such as plastics, drywall, and clothing, and is relatively unaffected by environmental conditions such as rain, fog, dust, and snow. The ability to sense the position and movement of surfaces at the submillimeter scale enables such systems to perform vital sign monitoring.

[0004] As an example, the signal bands of 5G communication systems or other suitable wireless communication systems can be used as millimeter wave radars, for example to measure the position and movement of cars and people and even vital signs such as heart rate and breathing rate, but this requires understanding the transmission environment, the approximate target location and appropriate modifications to the signaling system.

[0005] Recently, millimeter-wave frequency Doppler radar systems have been studied for human pose estimation (see Sizhe An et al.: "Fast and Scalable Human Pose Estimation using mmWave Point Cloud", Design Automation Conference (DAC) 2022, arXiv:2205.00097[eess.IV]). Such systems typically utilize frequency-modulated continuous wave (FMCW) chirps, which are emitted by a transmitter, deflected by objects in the scene, and then received by one or more antennas. Both the distance and Doppler shift (velocity) of people moving in the scene can be recovered, mapped in two dimensions (2D), and used as features for a given pose. In addition, human pose estimation has been used to identify individuals in a crowd, primarily for security applications.

[0006] Synthetic data is artificial data generated from raw data and a model trained to reproduce the properties and structure of the raw data. Generating millimeter-wave synthetic data representing 3D human poses from raw video datasets has recently been demonstrated (see Karan Ahuja et al., “Vid2Doppler: Synthesizing Doppler Radar Data from Videos for Training Privacy-Preserving Activity Recognition”, CHI’21, May 8–13, 2021, Yokohama, Japan). The method results in synthetic millimeter-wave Doppler radar measurements that closely match real Doppler radar measurements of both range and Doppler shift over time. It can be decomposed into two key steps: (1) generating a 3D mesh model of the pose individual from video data, and (2) generating synthetic Doppler radar measurements based on the 3D mesh model and a given synthetic viewpoint. Equivalence of step (1) has been demonstrated with other initial datasets, including generation of 3D mesh data from lidar, sonar, and body-worn accelerometers (see Amin Ahmadi et al., “3D Human Gait Reconstruction and Monitoring Using Body-Worn Inertial Sensors and Kinematic Modelling,” DOI 10.1109 / JSEN.2016.2593011, Journal of IEEE Sensors). Step (2) should be compatible with 3D meshes generated from these other data types, indicating that synthetic millimeter-wave Doppler radar data can be generated from many initial base datasets.

[0007] Beyond human pose recognition, research has shown that the radar cross-sections of objects such as drones or different car models may be different enough to perform recognition. The generation of synthetic aperture radar data of cars and other objects is often applied to virtual sensor training, such as in autonomous vehicles.

[0008] ISAC is considered a new service for next-generation telecommunications networks. In such a service, network resources can be intelligently shared between communication and sensing tasks, allowing the network infrastructure to function as a sensor network. Such "aware" networks can be used to improve core communication functions on the network, but they can also enable "sensing as a service," where the output of such sensing functions can be accessed by third parties.

[0009] The term "virtual reality" has recently been used to refer to a shared collection of interactive spaces where users can interact with each other alongside mutually perceived virtual features (i.e., augmented reality (AR)) or where those spaces consist entirely of virtual features (i.e., virtual reality (VR)). This definition has recently been adopted in some 3GPP work items. Throughout this disclosure, VR and AR are generally referred to as "mixed reality" (MR).

[0010] Interoperability of virtual and mixed reality (MR) services has been predicted to be a key issue to address. More specifically, parts of the services, such as digital storefronts and the digital goods and items they sell, are expected to be non-interoperable by default. This means that for a given user interacting in one VR environment, any digital assets they purchase will not be visible to a different user interacting in a second VR environment.

[0011] This interoperability issue leads to user experience problems (since users are more likely to purchase digital assets if they can be viewed by any other user, even outside of their specific VR), so solutions need to be identified that enable limited interoperability (and specific digital asset sharing) between VRs without disrupting the effective monopoly that each VR service provider has on the digital storefront within its own service. Summary of the Invention

[0012] It is an object of the present invention to improve the identification of objects for sensing related services.

[0013] This object is achieved by an apparatus according to claim 1 , a terminal device according to claim 12 , an access device according to claim 13 , a system according to claim 14 , a method according to claim 15 , and a computer program product according to claim 16 .

[0014] According to a first aspect related to a wireless communication device or other network device (e.g., an access device or a terminal device), an apparatus comprises at least one sensor characterized by at least one sensing parameter, in particular at least one of a sensor type and a viewpoint or perspective, wherein the apparatus is configured to:

[0015] obtaining first measurement data of a target object;

[0016] receiving second measurement data related to the target object from a second sensor;

[0017] obtaining synthetic data of the second measurement data and / or the first measurement data based on the at least one sensing parameter of the first sensor and / or at least one sensing parameter related to the second measurement data, in particular at least one of a point or a direction or a field of view and a sensor type; and

[0018] A determination is made based on the obtained synthetic data whether there is a match between the first measurement data and the second measurement data.

[0019] According to a second aspect related to a process performed at a wireless communication device or other network device (e.g., an access device or a terminal device), a method for matching a target object in a wireless network includes:

[0020] obtaining first measurement data of a target object;

[0021] receiving second measurement data related to the target object from a second sensor;

[0022] obtaining synthetic data from the second measurement data and / or the first measurement data based on at least one sensing parameter of the first sensor and / or at least one sensing parameter related to the second measurement data, in particular at least one of sensor type and field of view point or direction, and

[0023] A determination is made based on the obtained synthetic data whether there is a match between the first measurement data and the second measurement data.

[0024] According to a third aspect, a terminal device (eg, UE) comprising the apparatus of the first aspect is provided.

[0025] According to a fourth aspect, an access device (eg, a base station, an access point, etc.) comprising the apparatus of the first aspect is provided.

[0026] According to a fifth aspect, a wireless communication system is provided, comprising at least one of the terminal device according to the third aspect and the access device according to the fourth aspect.

[0027] Finally, according to a sixth aspect, a computer program product is provided, comprising code means for producing the steps of the method of the second aspect when executed on a processor of a network device.

[0028] Thus, the proposed solution enables a matching service where two different devices can confirm or de-confirm having viewed or otherwise sensed the same object by generating synthetic data based on data from the first device that is very similar to the data that would be generated if the second device viewed the same object.

[0029] Thus, a "perception" network with matching services is provided, which can be composed of many terminal devices (e.g., UEs) and access devices (e.g., gNBs) with different capabilities and modalities deployed to sense target objects (e.g., people and objects) in an environment. First (real) sensed data of a target object collected by a first device is used to generate synthetic data suitable for simulating as accurately as possible possible second (real) sensed data generated by a second device for the same target object. The synthetic data can then be used to determine whether the second sensed data collected by the second device matches the first sensed data collected by the first device, so that it can be confirmed whether the two devices are sensing or have sensed the same object.

[0030] Therefore, the specific generation of synthetic data based on the sensed data of the first sensor to match the sensed data of the second sensor helps to determine that the same target object is sensed by different sensors.The synthetic data generation process can take into account factors such as the position, perspective or viewpoint of the different sensors.

[0031] The proposed matching concepts can be applied in various use case specific embodiments (as described later) to provide methods and systems for generating synthetic data by or for one device to achieve matching with real-world data of a second device, wherein the synthetic data is generated based on knowledge of at least one sensing parameter used by the second device (e.g., sensor type, viewpoint, viewing direction, etc.).

[0032] Depending on the specific use case, the following benefits are achieved:

[0033] This can allow the network to arbitrate information transfer between a first device and a second device when the first device does not know the identity of the second device. More specifically, in an MR / virtual reality use case, the network can allow the first device to determine the identity of the user specifically being viewed by the first device so that necessary further information can be retrieved (e.g., the correct digital assets to load for the specific viewing user).

[0034] Furthermore, it is possible to track individual devices between cells via the transfer of data representing their radar cross section, thereby providing service continuity for sensing tasks on the network. More specifically, it is possible to allow the tracking of non-communicating objects as they travel from cell to cell, which can be an important function in areas such as law enforcement (e.g., tracking vehicles).

[0035] Additionally, users may be allowed to provide data using readily accessible sensors (such as a smartphone camera), which may then be used as part of the authentication service provided by the network.

[0036] According to a first option that can be combined with any one of the above first to sixth aspects, the at least one sensing parameter related to the second measurement data may be at least one sensing parameter of the second sensor, wherein the at least one sensing parameter of the second sensor is obtained from another device.

[0037] According to the second option which can be combined with the first option or any one of the first to sixth aspects above, the device can be configured to determine whether there is a match between the synthesized data of the first measurement data obtained and the synthesized data of the second measurement data obtained; or determine whether there is a match between the first measurement data and the synthesized data of the second measurement data obtained; or determine whether there is a match between the second measurement data and the synthesized data of the first measurement data obtained.

[0038] According to the third option which can be combined with the first option or the second option or any one of the first to sixth aspects mentioned above, whether there is a match can be achieved by using at least one of a first algorithm for splitting the first measurement data and the second measurement data into first object-related data and second object-related data, a second algorithm for generating synthetic data from the first object-related data or the second object-related data or one of the previous inputs, a third algorithm for converting the first object-related data or the second object-related data or one of the previous inputs into a first intermediate form or a second intermediate form (specifically a multidimensional representation of the object described by the first object-related data or the second object-related data), a fourth algorithm for converting the first intermediate form or the second intermediate form or one of the previous inputs into synthetic data, and a fifth algorithm for aligning the first intermediate form and the second intermediate form.

[0039] According to the fourth option, which may be combined with any of the first to third options or any of the first to sixth aspects, the identity of the target object may be determined (eg, by the device) based on the obtained synthesized data and the first measurement data.

[0040] According to a fifth option, which may be combined with any of the first to fourth options or any of the above first to sixth aspects, the first measurement data may be retrieved (eg by the device) from a database.

[0041] According to the sixth option, which can be combined with any of the first to fifth options or any of the first to sixth aspects above, additional data related to the target object can be retrieved (for example, by the device) from a virtual reality or mixed reality service provider and provided to a second sensor.

[0042] According to the seventh option, which can be combined with any of the first to fifth options or any of the first to sixth aspects, the apparatus can be configured to perform asset tracking of a target object. This enables intermittent checking of tagged assets to ensure that the tracking tags are still attached to the appropriate assets.

[0043] According to an eighth option which may be combined with any one of the first to fifth options or any one of the first to sixth aspects, the apparatus may be configured to request the target object to accept network-assisted identification.

[0044] According to a ninth option which may be combined with any one of the first to fifth options or any one of the first to sixth aspects, the apparatus may be configured to authorize the target object if a match is determined.

[0045] According to the tenth option, which can be combined with any one of the first to fifth options or any one of the first to sixth aspects above, the apparatus may be configured to provide support for service continuity, particularly when the target object moves out of the coverage area of the remote device.

[0046] According to a seventh aspect, the above object is solved by an apparatus comprising a receiver and a sensing sensor characterized by certain sensing parameters (e.g., sensor type, viewpoint), and configured to:

[0047] - sensing or retrieving first sensing data of a target object,

[0048] - receiving second sensory data from a first device associated with the target object,

[0049] - (optionally) receiving sensing parameters (e.g. sensor type, viewpoint) from said first device,

[0050] - generating synthetic data from the second sensed data (or the first sensed data) based on parameters of the apparatus and parameters of the first device, and

[0051] - determining whether the real-world first sensory data (respectively, the second sensory data) and the generated synthetic data match.

[0052] According to a first option, the apparatus of the seventh aspect may be configured as:

[0053] - generating synthetic data from the first sensed data and the first sensed data based on parameters of the apparatus and parameters of the first device, and

[0054] - determining whether the generated synthetic data from the first sensed data and the generated synthetic data from the second sensed data match.

[0055] According to the second option which can be combined with the first option, the apparatus of the seventh aspect may further include at least one of a segmentation algorithm, a synthetic data algorithm, an X to grid algorithm, a grid to Y algorithm, a synthetic transformation algorithm and a grid alignment algorithm.

[0056] According to the third option, which may be combined with the first option or the second option, the apparatus of the seventh aspect may be further configured to determine the identity of the target object based on the generated synthesized data and the first sensed data.

[0057] According to a fourth option which may be combined with any one of the first to third options, the first sensing data may be stored in a database.

[0058] According to the fifth option, which can be combined with any one of the first to fourth options, the apparatus of the seventh aspect may be configured to retrieve additional data related to the target object from a virtual reality / MR service provider and provide the additional data to the first device.

[0059] According to the sixth option which can be combined with any one of the first to fifth options, the apparatus of the seventh aspect may be configured to perform asset tracking of the target object.

[0060] According to the seventh option which may be combined with any one of the first to sixth options, the apparatus of the seventh aspect may be configured to request the target object to opt in to network-assisted identification.

[0061] According to an eighth option which may be combined with the seventh option, the apparatus of the seventh aspect may be configured to authorize the target object if there is a match.

[0062] According to a ninth option which may be combined with any one of the first to eighth options, the apparatus of the seventh aspect may be configured to support service continuity when the target object moves out of a coverage area of the first device.

[0063] According to an eighth aspect, the above object is solved by a UE comprising the apparatus of the seventh aspect and the first to fourth, sixth and seventh options.

[0064] According to a ninth aspect, the above object is solved by a base station comprising the apparatus of the seventh aspect and the first to ninth options.

[0065] According to a tenth aspect, the above object is solved by a method for matching features:

[0066] - first sensing data of sensing the target object,

[0067] - receiving second sensory data from a first device associated with the target object,

[0068] - (optionally) receiving sensing parameters (e.g. sensor type, viewpoint) from the first device,

[0069] generating synthetic data from the second sensed data (or the first sensed data) based on parameters of the apparatus and parameters of the first device, and

[0070] It is determined whether the first sensed data (respectively, the second sensed data) and the generated synthetic data match.

[0071] According to an eleventh aspect, the above object is solved by a computer program product comprising code means for producing the steps of the method of the tenth aspect when run on a computer device.

[0072] According to a twelfth aspect, the above-mentioned purpose is solved by a system for generating synthetic data by one device to achieve a match with real-world data of a second device, wherein the synthetic data is generated knowing the parameters used by the second device in its sensing (for example, sensor type or viewpoint).

[0073] It should be noted that the above-mentioned devices can be implemented based on discrete hardware circuits with discrete hardware components, integrated chips or chip module arrangements, or based on signal processing devices or chips controlled by software routines or programs stored in memory, written to computer-readable media or downloaded from a network (such as the Internet).

[0074] It should be understood that the apparatus according to claim 1, the terminal device according to claim 12, the access device according to claim 13, the system according to claim 14, the method according to claim 15, and the computer program product according to claim 16 may have similar and / or identical preferred embodiments, in particular, as defined in the dependent claims.

[0075] It shall be understood that a preferred embodiment of the invention can also be any combination of the dependent claims or the above-described embodiments with the respective independent claim.

[0076] These and other aspects of the invention will be apparent from and elucidated with reference to the embodiments described hereinafter. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] In the following figures:

[0078] Figure 1 Schematically illustrates the distributed sensing functionality created via a 5G communication system link;

[0079] Figure 2 schematically illustrates embodiments of transmitter and receiver architectures that may be used in embodiments of the present invention;

[0080] Figure 3 schematically illustrates a sensing and communication system with data processing and matching algorithms according to a first embodiment;

[0081] Figure 4 Schematically shows a process flow chart according to a first embodiment;

[0082] Figure 5 Schematically shows a flow chart of a matching process according to a second embodiment;

[0083] Figure 6 schematically shows a system configuration according to a modification of the third embodiment;

[0084] Figure 7 Schematically shows a flow chart of a matching process according to a fourth embodiment;

[0085] Figure 8 Schematically illustrates a target authorization process according to various embodiments of the present invention;

[0086] Figure 9 Schematically illustrates an embodiment of a flow chart of a sensing operation according to an embodiment of the present invention;

[0087] Figure 10 schematically illustrates an embodiment of a flow chart of a position and movement detection process that may be used in embodiments of the present invention;

[0088] Figure 11 schematically illustrates an embodiment of a flow chart of a heart rate and respiratory rate detection process that may be used in embodiments of the present invention;

[0089] Figure 12 Schematically illustrates a sensing system according to an embodiment of the present invention;

[0090] Figure 13 The following schematically illustrates the architecture of a wireless network with an overlapping sensing structure in which the present invention can be implemented;

[0091] Figure 14 Schematically shows a block diagram indicating how to perform handover according to a first embodiment of the present invention;

[0092] Figure 15 Schematically shows a block diagram indicating how to perform handover according to a second embodiment of the present invention;

[0093] Figure 16 schematically illustrates a collaborative sensing process according to another embodiment of the present invention; and

[0094] Figure 17Schematically illustrates a block diagram and exchange of signals for a cooperative sensing process according to another embodiment of the present invention. DETAILED DESCRIPTION

[0095] Embodiments of the present invention are now described based on a cellular sensing and communication network environment, such as 5G. However, the present invention can also be used in conjunction with other wireless technologies, such as IEEE 802.11 / Wi-Fi or IEEE 802.15.4 / Ultra-Wideband (UWB), in which target sensing is provided or can be introduced.

[0096] Throughout this disclosure, the abbreviation "gNB" (5G terminology) or "BS" (base station) is intended to refer to a wireless access device, such as a cellular base station, WiFi access point, or Universal Serial Bus (USB) Personal Area Network (PAN) coordinator. A gNB may consist of a centralized control plane unit (gNB-CU-CP), multiple centralized user plane units (gNB-CU-UP), and / or multiple distributed units (gNB-DU). The gNB is part of the Radio Access Network (RAN), providing an interface to functions in the Core Network (CN). The RAN is part of a wireless communication network. It implements the Radio Access Technology (RAT). Conceptually, it resides between communication devices, such as mobile phones, computers, or any remotely controlled machine, and provides connectivity to their CN. The CN is the core component of the communication network, providing many services to customers interconnected via the RAN. More specifically, it directs communication flows through the communication network and potentially other networks.

[0097] Furthermore, the terms "base station" and "network" may be used synonymously in this disclosure. This means, for example, that when a "network" is written to perform a certain operation, it may be performed by a CN function of the wireless communication network or by at least one base station that is part of such a wireless communication network, or vice versa. It may also mean that a portion of the function is performed by the CN function of the wireless communication network, and a portion of the function is performed by a base station.

[0098] Furthermore, the terms "radar sensing" and "wireless sensing" are intended to encompass not only techniques in which a single device both transmits and receives radar signals, but also distributed RF-based sensing techniques, such as techniques in which sensing signals are received by multiple devices in a distributed manner or techniques based on sensing of channel state information (CSI) in a distributed sensing solution based on CSI and / or based on other types of measurement information related to RF signals (e.g., multiple-input multiple-output (MIMO) sounding signal feedback, Doppler phase shift measurements). It should be noted that the terms "radar sensing" and "wireless sensing" above are used interchangeably throughout this disclosure, and embodiments describing radar sensing can also be extended to other types of wireless sensing, such as those using reference signals such that the UE reports measurements related to the reference signals, e.g., sensing based on channel state information (CSI).

[0099] The term "sensing" is used not only to mean "radar sensing" or "wireless sensing," but also for sensing using any sensor modality, including cameras, pressure sensors, motion sensors, thermal sensors, etc.

[0100] Furthermore, the term "data type" is intended to cover different types of data output by different types of sensors. For example, a camera may output video data, and a lidar sensor may output point cloud data. Furthermore, intermediate data types are covered that are not directly output by a sensor, but may have been generated by processing other types of data sets, such as three-dimensional (3D) mesh data (as explained later). Furthermore, the terms "target" and "target object" indicate any entity that may be subject to wireless sensing. This may include people, animals, inanimate objects, structures composed of several smaller entities (e.g., a cloud composed of small water droplets). Furthermore, the terms "target" and "target object" may be used as synonyms in this disclosure.

[0101] Unless otherwise specified, the term "object" is intended to encompass any three-dimensional form of interest within the environment about which information can be collected by a sensor. Typically, this includes people (and their movements), animals, vehicles, drones, immobile objects, structures composed of several smaller entities (e.g., a cloud composed of small water droplets), etc.

[0102] Note that throughout this disclosure, only those blocks, components, and / or devices relevant to the proposed sensing and / or matching functionality are shown in the accompanying drawings. For the sake of brevity, other blocks are omitted. In addition, blocks designated by the same reference numerals are intended to have the same or at least similar functionality, so that their functionality will not be described again later.

[0103] Sensing signal

[0104] The sensing function of the following embodiments may be implemented, for example, by a radar function in wireless communications involving one or more access devices (eg, base stations (BSs)) and / or one or more terminal devices (eg, UEs).

[0105] For example, a frequency modulated continuous wave (FMCW) millimeter wave radar system can measure the range, velocity, and angle of arrival (if two receivers are available) of objects in a scene that reflect radio waves. Such a radar system transmits a chirp signal, such as a sine wave whose frequency increases over time. The chirp signal (e.g., a continuous wave pulse) has a bandwidth and a rate of increase in frequency. Typically, a series of continuous chirps is transmitted. The transmitted and received analog chirp signals are mixed to produce an intermediate frequency (IF) signal that corresponds to the frequency difference between the two signals (outbound and inbound), and whose output phase corresponds to the phase difference between the two signals.

[0106] Therefore, each surface in the scene or environment generates an IF signal with a constant frequency, whose frequency is related to the distance to the surface (i.e., the first distance from the chirp signal transmitter to the surface plus the second distance from the surface to the chirp signal receiver). To distinguish between two surfaces at different distances, the two IF signals can be frequency resolved. The longer the time window of the IF signal, the higher the resolution. Because the chirp time is related to its bandwidth (the chirp frequency constantly changes), the radar's resolution is related to the chirp bandwidth. The IF signal can then be bandpass filtered (to remove signals below a certain minimum range and frequencies above a maximum frequency for subsequent analog-to-digital converter (ADC) use) and digitized before further processing. The bandpass filter and the upper frequency sensing range of the ADC set the maximum range that can be detected (i.e., the IF frequency increases with range).

[0107] To detect vibrations, the phase of the IF signal is important because the phase (i.e., the difference in phase between the transmitted and received chirp signals) is a sensitive measure of small changes in distance to the surface. Small distance changes can be detected in the phase signal but may not be discernible in the frequency signal. Furthermore, the phase difference measurement between two consecutive chirp signals can be used to determine the velocity of the surface.

[0108] As an example, a Fast Fourier Transform (FFT) process can be performed across multiple chirp signals to enable the separation of objects that have the same range but move at different speeds. The Fourier transform converts a signal from the spatial or time domain to the frequency domain. In the frequency domain, a signal is represented by a weighted sum of sine and cosine waves. A discrete digital signal with N samples can be accurately represented by the sum of N waves. The FFT provides a faster way to combine samples by exploiting the symmetry and repetition of the waves and reusing partial results to calculate the discrete Fourier transform. This method can save a lot of processing time, especially in the case of real-world signals that can have thousands or even millions of samples.

[0109] As another example, angle estimation may be performed by using the phase difference between received chirp signals at two separate receivers.

[0110] As another option, channel state information (CSI) can be used. CSI is a measure of the phase and amplitude of many frequencies detected at the receiver, forming a 'map' of the complex radio environment, including the influence of objects within that environment. CSI characterizes how wireless signals propagate from the transmitter to the receiver at certain carrier frequencies. CSI amplitude and phase are affected by multipath effects, including amplitude attenuation and phase shifts, for example, by the displacement and movement of the transmitter, receiver, and surrounding objects and humans. In other words, CSI captures the wireless characteristics of the nearby environment. These characteristics, assisted by mathematical modeling or machine learning algorithms, can be used for different sensing applications.

[0111] The radio channel can be divided into multiple subcarriers, such as is done in 5G communication systems (using, for example, orthogonal frequency division multiplexing (OFDM)). To measure CSI, the transmitter can send long training symbols (LTFs), which contain predefined symbols for each subcarrier, for example, in a packet preamble. When these LTFs are received, the receiver can estimate the CSI matrix using the received signal and the original LTFs. For each subcarrier, the channel can be modeled by y = Hx + n, where y is the received signal, x is the transmitted signal, H is the CSI matrix, and n is the noise vector. The receiver estimates the CSI matrix H using the predefined signal x and the received signal y after signal processing (such as removing the cyclic prefix, demapping, and demodulation). The estimated CSI is then a complex-valued three-dimensional matrix, and the matrix represents an 'image' of the radio environment at the time. By processing the time series of information about movement of such an 'image', the position and vibration of the object can be extracted.

[0112] This processing of the CSI matrix can be used for vital sign monitoring, presence detection, and human motion recognition. As an example, a neural network (such as recognition technology) can be used to process the CSI matrix to perform such recognition.

[0113] Note that systems using channel state information (CSI) are related in some way to systems with FMCW millimeter wave radars. In a CSI-based system, the input signal X can be defined, and the receiver can use the received signal Y to obtain H, i.e., H = (YN) / X. In an FMCW millimeter wave radar, the transmitted signal chirp X can also be predefined, and the receiver can use the received signal Y to obtain a transfer function such as H = Y / X. This last step is actually related to multiplying the locally calculated chirp signal and the received chirp signal and applying a bandpass filter. According to the various embodiments described below, the above-mentioned wireless sensing technology is implemented in a mobile communication system (e.g., 5G or other cellular or WiFi communication system), and the functional coexistence of radar and communication operating in the same frequency band is configured to avoid interference bandwidth. Thus, radio sensing can be integrated into large-scale mobile networks to create a perceptual mobile network.

[0114] As another example, the sensing signal may be composed of a plurality of pulses transmitted by a sensing transmitter at a specific frequency and timing (sensing signal parameter information). The sensing receiver may include a plurality of bandpass filters that allow identification of the sensing signal parameter information (e.g., the timing and frequency of the received pulses). In particular, if the transmitter determines a given pseudo-random sequence of frequency / timing pulses and beams them in a specific direction, for example, by means of beamforming, and if the transmitter transmits the timing / frequency of the transmitted sensing signal (typically the sensing signal parameter information) to the receiver, the receiver may use its bandpass filter to identify the reception of the same transmitted pulses (i.e., sensing signal) based on the received sensing signal parameter information.

[0115] (Distributed) Sensing Configuration and Operation

[0116] Figure 1 Schematically illustrates distributed radar functionality created via wireless communication system links that may be used in embodiments of the present invention.

[0117] However, it is to be noted that the present invention is equally applicable to non-distributed sensing services / functions, where a first sensing device performs sensing centrally and then (after handover) a second sensing device performs sensing centrally. Thus, the described embodiments may be implemented in a single device comprising both a transmitter and a receiver.

[0118] In a distributed radar function, unlike a purely centralized radar solution (i.e., where the transmitter and receiver of the radar signal are part of or operated by the same device), a portion of the 5G (or other cellular or WiFi) network spectrum is configured (e.g., set to radar mode) or detected as quiet / clear of communication for a period of time to enable remote vital signs and other measurements to be performed by establishing a distributed radar system between a base station (BS) 100 or UE (as a transmitter) and at least one UE 120 or base station (as a receiver), while the lack of analog signal exchange and the additional path length caused by the transmitter-receiver distance and the distance between the receiver (e.g., UE 120) and the target (e.g., a human) can be corrected. To this end, the base station 100 (or UE) acting as a transmitter can establish a communication link with the UE 120 (or base station) acting as a receiver (or vice versa) to exchange some control information and / or sensing measurements and / or (partial) sensing results. The control information can include a set of configuration parameters related to the distributed sensing operation.The parameters may include, for example, the distance and angle from the transmitter to the receiver, the pulse initiation time, the pulse phase, the frequency (possibly including chirp timing (CT), chirp profile (CP), target position (TL), phase offset (PO), the time between subsequent sensing signals, the number of repetitions, sensing signal waveform information, amplitude, MIMO / beamforming parameters, the number of transmitter antennas used, transmit power, potential interference patterns, an identifier / address (e.g., an Internet Protocol (IP) address / Uniform Resource Locator (URL) address) of a destination server and / or network function / device to which the sensing results are to be sent (e.g., for storage or further processing), session or application related information (e.g., a session identifier or application identifier), a desired accuracy for the sensing measurements, etc., and may be transmitted as a response (e.g., as a Radio Resource Control (RRC) Connection Reconfiguration message (including, for example, a measurement configuration as specified in 3GPP TS 38.331, which is extended with sensing configuration parameters)) to a request for the radar (RR) (e.g., an initial attach request message from a UE to a base station or as specified in 3GPP TS 38.331). The RRC message or system information from the base station to the UE as specified in TS 38.331 is extended with a sensing request field), or it may be sent by the transmitter side to the receiver side before the transmitter will start sending the sensing signal (for example, as part of a configuration / assistance information message / signal), or it may be (partially) pre-configured on the receiver (for example, stored in a Universal Subscriber Identity Module (USIM) or stored in a non-volatile memory at the time of manufacture), or it may be configured on the receiver by means of a local application, or it may be provided by the network (possibly via the transmitter or via another transmitter, or for example by an Access and Mobility Management Function (AMF), a Policy Control Function (PCF), a Network Exposure Function (NEF), a Location Management Function (LMF), a Gateway Mobile Location Centre (GMLC) or other core network functions (for example, such as 3GPP The parameters may be configured differently per application (e.g., based on the sensing target or based on the sensing algorithm). The parameter sets may be combined in the form of sensing profiles identifiable, for example, by means of a profile identifier or an application identifier or a device identifier. After the sensing profile is sent / configured / pre-configured on the receiver, activation of the sensing profile may be triggered by sending a signal / message with the indicated sensing profile identifier to the receiver. The sensing profile and / or configuration parameters may also include an algorithm identifier, a filter identifier, or a machine learning model identifier to trigger the application of a specific sensing algorithm, filter, or machine learning model, respectively, for analyzing / processing the received sensing signals.These algorithms, filters, or models can be pre-configured / stored at the receiver, or sent to the receiver by the transmitter (e.g., as virtual machine code, filter parameters / code, or model data), such as in a separate message, or can be downloaded by the receiver based on, for example, a download URL or IP address of a server (e.g., as virtual machine code, filter parameters / code, or model data), and can be configured for the desired application. For example, if precise distance measurement is required, the complete parameter set can be transmitted, while if phase-based velocity is required, only the chirp parameters may be required. In some applications, the chirp parameters can be pre-defined, and only an identifier indicating the chirp parameter set can be exchanged. The parameters may also include a set of time / frequency resources (e.g., semi-persistent scheduling as defined in 3GPP TS 38.321) and / or a time / frequency offset for the sensing signal to be transmitted and / or when these parameters are expected to arrive at the receiver. This information may also be provided as the time interval for which the receiver is expected to listen for incoming reflected sensing signals (e.g., as an offset from the start time or system frame number / subframe / symbol at which the transmitter will transmit the signal). The start time, offset, or time interval for sensing by the receiver can be specified so that it begins at the start time or end time of the first instance of the sensing signal received by the receiver (i.e., the sensing signal received via a direct, non-reflected path). That is, the receiver can use the receipt of the first instance of the sensing signal to trigger / activate active sensing of the reflected sensing signal. Parameters can also include information about quiet periods or guard intervals that can be taken into account by the receiver device. Furthermore, parameters can include information about encoded identity information or special symbols / preambles or unique signal characteristics that can enable the receiver to uniquely identify the corresponding sensing signal from possible other sensing or communication signals. To enable the receiver to determine which parts of the sensing signal have encoded information therein (e.g., signal identity information, timestamp of the transmitter sending the signal), additional timing or frequency information can be provided to identify the start / end time or subdivision of the time interval for receiving a complete single sensing signal within the time interval, which indicates where the receiver can find the encoded information in the sensing signal.In a similar manner to the sensing receiver, the sensing transmitter may be configured by the network (e.g., by an Access and Mobility Management Function (AMF), a Policy Control Function (PCF), a Network Exposure Function (NEF), a Location Management Function (LMF), a Gateway Mobile Location Center (GMLC), or other core network functions (e.g., as specified in 3GPP TS 23.501)) as part of policy / system information / RRC configuration / session configuration (e.g., at initial registration or connection establishment of the sensing transmitter to the network or a previous initial registration / connection establishment) with parameters on how to perform sensing (e.g., pulse initiation). The parameters for sensing may include the time, pulse phase, frequency, which may include chirp timing (CT), chirp profile (CP), target position (TL), phase offset (PO), time between subsequent sensing signals, sensing signal waveform information, amplitude, MIMO / beamforming parameters, number of transmitter antennas to be used, transmit power, silent periods or guard intervals that may be considered, etc.) and / or which algorithm, filter, sensing profile to use and / or which destination server and / or network function / device to send the sensing results to (e.g., for storage or further processing) and / or session or application related information (e.g., session identifier / application identifier), etc. The above parameters for sensing may also be pre-configured on the transmitter (e.g., stored in the USIM at the time of manufacturing or stored in non-volatile memory), or may be configured on the transmitter through a local application, or may be provided by the receiver.

[0119] Note that the LMF may include or be connected to a set of services / functions (e.g., a Gateway Mobile Location Center (GMLC)) that may together be responsible for / capable of determining, validating, providing, and / or storing a set of location, distance, angle, coordinates, and other related information for location and / or ranging services, and / or managing / configuring / operating a set of location and / or ranging services, and / or combining distance, angle, location information with distance, angle, location information from other sources or generated by various location / ranging mechanisms. The term "LMF" refers to any such service / function or combination thereof.

[0120] To facilitate configuration of the above-mentioned sensing parameters, a sensing receiver or sensing transmitter device may provide sensing-related capabilities to the network (e.g., a core network function or service (operated / provided by the network) responsible for managing and / or performing sensing (i.e., sensing services) or an application function for managing and / or using the results of sensing operations (i.e., sensing applications)), to one or more base stations, or to (one or more) other devices involved in distributed sensing (e.g., a sensing transmitter device in the case of a sensing receiver device) by means of a capability exchange message (e.g., as part of a request for a radar message or an RRC UECapabilityInformation message as known in 3GPP TS 38.331, which is extended with some fields indicating sensing-related capabilities). The sensing-related capability information may include, for example, device information (such as the number of antennas or supported frequency ranges), wireless sensing signal processing capabilities (such as which algorithms are supported and / or whether it can determine certain sensing results / targets (e.g., the ability to determine the position or movement of a target object or the shape of a target object), one or more supported sensing profiles, etc.), and wireless sensing signal transmission capabilities (whether the sensing profile is supported, etc.). The sensing receiver may be configured differently based on the receiving capabilities of the sensing receiver and / or the sensing transmitter.The sensing transmitter may be configured differently and / or adapt the sensing signal based on the received capabilities of the sensing receiver and / or the sensing transmitter.

[0121] Parameters for the configuration of the sensing transmitter and the sensing receiver may be adapted depending on sensing requirements that may be provided, for example, by an application function or a network exposed function or other core network function / service or application (e.g., a sensing service or a sensing application). Such sensing requirements may, for example, identify the type of sensing result that is expected to be calculated (e.g., movement, position, shape, material, biometric), information about one or more target objects (e.g., information about a rough position, a last known position, identifiable features or known features such as size or material or shape) and / or quality of service (e.g., desired accuracy, sampling rate) and / or information about the algorithms / filters to be used and / or session / application related information (e.g., an application identifier or a session identifier).

[0122] exist Figure 1 In the present invention, a base station (BS) 100 and / or a UE 120 determines the (rough) position or area or volume of a target 150 by transmitting a series of signals (e.g., chirp signals) that can be beamformed in the direction of the target 150. The (rough) position can also be in the form of a relative position, such as a set of distances and / or angles relative to a reference point (e.g., a transmitter or a receiver).

[0123] Optionally, for example, before the actual radar sensing process begins between the transmitter and the receiver, unless known, the target angle and distance and / or target shape and / or target material / reflectivity characteristics can be determined using a position estimation radar operation and / or a target shape determination operation and / or a target material / reflectivity characteristics determination operation at the transmitter (e.g., base station (BS) 100). This information can be stored at the transmitter and / or provided to the receiver and / or provided to a network function responsible for collecting sensing measurements and / or (partial) sensing results, and further processing can be performed on these sensing measurements / results to determine further sensing characteristics of the specific target.

[0124] Depending on the target sensing application, before transmitting the (chirp) signal, the precise timing of the phase and frequency (and optionally the amplitude) of each individual (chirp) signal can be optionally transmitted (e.g., using a protected standard communication signal) to the receiver (e.g., UE 120) along with the position or relative position of the transmitter (e.g., BS 100) and optionally the rough position of the target 150. The idea of protected communication (encryption and / or integrity protection) is to ensure that only the intended receiver can use this information. Based on this, the receiver can optionally determine the path length and angle from the transmitter to the receiver and internally synthesize an analog (chirp) signal that matches the transmitted (chirp) signal. The received and synthesized signal can be used for sensing purposes.

[0125] If the relative position and exact time are known, the path length of the reflected sensing signal through the target 150 can be determined and / or the target surface can be accurately reconstructed, for example, by detecting the correct intermediate frequency (IF) signal at the mixer output when the signal is a chirped signal. Knowing the rough position of the target object and / or by detecting the angle of arrival of the incoming reflected sensing signal, the distance or angle between the receiver and the target object and / or the transmitter and the target object can be calculated. Knowing the phase and therefore the phase difference, the velocity of the target 150 can be determined based on the frequency.

[0126] If only the velocity of the target 150 is desired (rather than its position and velocity), the transmitter can optionally avoid providing its relative position and transmit only the phase, timing, and frequency of the transmitted sensing signal. In some cases, only the sensing signal itself can be sent to the receiver so that the receiver can use it, assuming a fixed time delay, to calculate an IF signal from which the velocity of the target can be derived. This is particularly interesting for measuring vital signs such as respiration or heart rate. For example, it can allow the velocity of the chest to be measured while breathing and to derive the respiratory rhythm from it.

[0127] Given a sufficiently good estimate of the reflecting surface position, the receiver may enable collection of additional data, such as skin conductivity.

[0128] In an example, radar sensing capabilities may be implemented by determining and transmitting a sensing signal parameter to be used in a transmitter sensing generation process, a coarse or relative position of a target and a position offset / angle from the transmitter to a receiver (e.g., UE 120), or an absolute / geographic location of the transmitter, and a future time or set of time / frequency resources for a first (and subsequent) sensing signal from the transmitter to the receiver using, for example, a protected communication signal.

[0129] Alternatively, some of the parameters may be pre-configured at the receiver, or may be configured at the receiver by a local application, or may be sent by the transmitter or network at an earlier time (e.g., during a previous session). The transmitted parameter information is then (optionally) decrypted and / or verified by the receiver. Thereafter, the transmitter transmits the sensing signal at the time to generate the sensing signal using, for example, its discrete Fourier transform spread orthogonal frequency division multiplexing (DFT-s-OFDM) signal generation process. The receiver may listen for the sensing signal at the time / resource indicated in the parameter information. The receiver may use its DFT-s-OFDM signal generation process to generate an internal synthetic sensing signal (e.g., a chirp) that matches the provided parameters, optionally with a delay corresponding to the direct distance from the transmitter to the receiver, thereby minimizing the IF frequency generated in the receiver. The receiver may use the provided sensing parameter information and / or the internal representation of the sensing signal to configure its radio frequency (RF) receive front end or signal detection unit to identify / detect the sensing signal among the signals received by the RF receive front end. Upon detecting and / or further processing received sensing signals, the receiver may determine and record / store start / end times, phase shift, frequency, amplitude, signal distortion, signal strength, interference patterns, detected special symbols / preambles, encoded identity information of the sensing signals, and / or the timing of quiet periods between sensing signals. The receiver may use this information to further determine whether the received sensing signals were actually reflected by the target object or received via a direct, non-reflective path between the transmitter and receiver, thereby filtering out only relevant sensing signals to extract sensing information about the target object. To this end, the receiver may calculate the expected path loss and / or timing between the transmitter and receiver for the direct path, as well as the expected path loss and / or timing for the indirect, reflective path via the target, and use this information when determining whether the received sensing signals were actually reflected by the target object or received via a direct, non-reflective path between the transmitter and receiver.

[0130] Alternatively, the transmitter may calculate the expected path loss and / or timing for the direct path between the transmitter and the receiver, as well as the expected path loss and / or timing, via an indirect reflection path through the target, and send this information to the receiver, which may then use this information in its determination. The receiver may use (e.g., mix) the internally synthesized "transmitted" sensing signal reflected at the target 150 and the received sensing signal to form an IF signal, and may perform bandpass filtering (or optionally high-pass filtering only at the maximum frequency of the ADC) filtering and ADC to digitize the IF data and / or digitize the raw / filtered received reflected sensing signal data. To this end, the receiver may generate a compressed or uncompressed digital sample representation of the IF signal or the received raw / filtered reflected sensing signal at a sampling frequency preconfigured at the receiver device or provided by the transmitter (e.g., as part of the sensing signal parameters). Furthermore, information regarding which compression method / format to apply may be provided by the transmitter (e.g., as part of the sensing signal parameters) or preconfigured at the receiver. The digital IF signal can then be processed to produce application-specific data (e.g., the output of one or more (pre-configured) algorithms or machine learning models), in this case, sensing results related to the target (e.g., certain characteristics of the target, such as its position, velocity, shape, size, material composition, etc., which can be determined after performing corresponding signal processing / analysis on the received (reflected) sensing signal), or the digitized data from the receiver can be sent to a transmitter or a network function / device or the cloud to perform further application-specific processing.

[0131] In addition to the processed or digitized data, the receiver may also include identification information of the signal, sensing profile, algorithm / model and / or device, and may include timing and / or measurement information used by the receiver for sensing (e.g., arrival / end time, phase shift, frequency, amplitude or signal deformation of the sensing signal) and / or antenna information / antenna sensitivity / MIMO configuration / beamforming configuration, and / or information related to the position / distance / angle of the receiver relative to the transmitter and / or target, or as absolute coordinates, and / or information about the sensing application or sensing session (e.g., application identifier or session identifier).

[0132] The complete separation of transmitter and receiver in digital radio systems (such as 5G) means that the receiver cannot access the analog version of the directly transmitted signal (phase, frequency), only the reflected sensed signal, and therefore cannot form the IF signal in the analog domain. This would mean that all processing would have to be performed on the received analog signal (which requires a very fast ADC to digitize the received "raw" sensed signal).

[0133] Furthermore, in the proposed distributed radar sensing system, the distance to the reflecting surface of the target 150 depends on the distance from the transmitter to the target 150 and from the receiver to the target 150 (rather than simply being twice the distance from the transmitter to the target, as in a non-distributed radar system).

[0134] The "minimum range" of a measurement corresponds to the direct distance from the transmitter to the receiver. Of course, objects located at a smaller distance from the receiver can be measured, but their indicated range will always be greater than the direct distance from the transmitter to the receiver. Equal time returns lie on a spatial position ellipse (return ellipse) with the transmitter and receiver positions as its two foci. The minimum (degenerate) ellipse with a minor axis length of zero (the straight line between the transmitter and receiver) has the minimum delay time, which is the time it takes to travel directly from the transmitter to the receiver.

[0135] The receiver may receive a signal corresponding to a directly transmitted signal transmitted directly from the transmitter to the receiver (the pseudo surface is in the "zero" range, ie, a point on a direct line between the transmitter and the receiver).

[0136] Therefore, the proposed integrated distributed radar system may require a type of clock-level synchronization between the transmitter and receiver to remove the ambiguity in the sensing parameter estimation.

[0137] In addition, auxiliary information signals (e.g., radar request and response parameters) can be transmitted between the transmitter and the receiver via an alternative communication route (using, for example, a separate frequency band, beamforming sub-beams directed at the receiver, or time-interleaved signals between the sensing signals), so that the receiver can obtain a representation of the required details of the transmitted signal (e.g., precise timing and phase of a continuous (chirp) signal) in order to simulate a mixture of transmit and receive signals to obtain an IF signal without the need for direct analysis of the simulated transmit signal. This can be accomplished, for example, by internally generating a simulated version of the same transmit sensing signal using the parameters supplied via the auxiliary information signal. Therefore, to ensure that the correct timing is provided for this mixture of simulated transmitter sensing signals and actual received sensing signals, the transmitter should signal the precise timing, phase, frequency, etc. of the transmit signal to the receiver in advance.

[0138] In addition, the receiver can use the auxiliary / (pre-)configured information / parameters about the sensing signals to distinguish between sensing signals received via a direct non-reflection path and reflected sensing signals. The receiver can ignore the sensing signals received via the direct non-reflection path (e.g., by ignoring the first instance of receiving the sensing signals (e.g., by examining the arrival time of the sensing signals, or by examining the phase shift, frequency change, signal deformation, amplitude change, interference pattern corresponding to identifying which sensing signal has been reflected), or can use these signals to more accurately determine its relative position / distance / angle toward the transmitter. The receiver can also use the signals received via the direct non-reflection path as further input to the signal analysis algorithm / model, for example, as additional reference signals for IF calculation, (relative) position calculation, or additional phase shift / signal deformation / frequency / amplitude calculation.

[0139] Additionally, the distance and angle from the transmitter to the receiver or the absolute / geographic location of the transmitter may also be signaled in order to calculate the correct position of the detected surface.

[0140] Finally, if the receiver (or transmitter, or both) is a handheld device, the movement and vibration of the device may be measured by corresponding sensors in order to subtract it from the movement and vibration of the detected surface for some sensing applications.

[0141] The proposed distributed radar system between, for example, a base station (BS) 100 (acting as a transmitter) and a UE 120 (acting as a receiver and analyzer) provides the following advantages: the receiver can be located at a higher signal strength than the transmitter to obtain the reflected sensing signal more preferentially (i.e., using the receiver part of the transmitter device to monitor the reflected sensing signal, e.g., as in the case of non-distributed sensing), for example, it can be closer or more in the path of the reflected sensing signal, and can avoid some clutter from the transmitted signal.

[0142] Furthermore, a single antenna may not be able to operate in full continuous duplex mode, while the proposed distributed radar system separates the transmitter antenna from the receiver antenna.

[0143] As another advantage, multiple receivers may be used with a single transmitter, each transmitter potentially associated with collecting vital signs from a different target (eg, an individual human).

[0144] However, as described above, sensing may be performed centrally by a single first device, and after the sensing switch, sensing may again be performed centrally by a single second device.

[0145] Sensing transmitter and receiver architecture

[0146] Figure 2An embodiment summarizing a transmitter and receiver architecture (including optional elements and functions) of a communication system with distributed sensing capabilities is schematically shown.

[0147] Although the architecture shows the transmitter device and the receiver device as different devices in a distributed sensing system, the functionality of the sensing transmitter and the sensing receiver may be co-located in the same device (e.g., in the case of a centralized sensing architecture), and thus similar functionality and elements (subsets) are expected to exist.

[0148] The proposed distributed radio wave sensing radar / communication system includes a transmitter device (TX) 10 and a receiver device (RX) 20, and is configured to operate over a suitable radio frequency range (such as the millimeter wave range initially mentioned), and includes RF hardware and signal processing algorithms to implement both standard communications (e.g., 5G) and radar sensing for vital signs, object detection, and / or mobile identification. In 5G systems, two options are provided for uplink (UL) waveforms. One is cyclic prefix OFDM (CP-OFDM, the same as the downlink (DL) waveform), and the other is discrete Fourier transform spread OFDM (DFT-s-OFDM), which corresponds to the UL waveform in the long-term evolution (LTE) system (i.e., the fourth generation (4G)). Transform precoding is the first step in creating the DFT-s-OFDM waveform, followed by subcarrier mapping, inverse FFT, and cyclic prefix (CP) insertion. Whether the UE needs to use CP-OFDM or DFT-s-OFDM can be determined by radio resource control (RRC) parameters.

[0149] 5G transmitters or receivers with integrated radar sensing capabilities can have slightly modified DFT-s-OFDM and frequency-domain spectral shaping (FDSS) filters that enable them to generate suitable chirps. Linear and other chirp signals can be generated with DFT-s-OFDM signals via well-designed FDSS filters that enable standard communications hardware to generate suitable signals for radar with only minor modifications. Their framework provides a way to efficiently synthesize chirps that can be used in dual-function radar and communications (DFRC) or wireless sensing applications with existing DFT-s-OFDM transceivers.

[0150] Cong Li et al., “Radar Communication Integrated Waveform Design Based on OFDM and Circular Shift Sequence,” Mathematical Problems in Engineering, July 2017, describe other options for generating signals suitable for simultaneous data transmission and radar sensing, based on the peak-to-average envelope power ratio (PMERP) and peak-to-sidelobe ratio (PSLR) of the OFDM waveform. Specifically, Gray code technology can be used to reduce PMERP and simultaneously select the optimal cyclic sequence to improve the PSLR of the OFDM waveform. Based on changes in the communication data, the optimal cyclic sequence is dynamically generated to continuously provide the optimal waveform. In addition, in order to meet the requirements of different radar detection tasks, two simple methods can be used to adjust the bandwidth of the OFDM waveform. One method is to design different subcarrier complex weights, and the other method is to use phase code technology.

[0151] The transmitter device (TX) 10 may be an access device (e.g., a base station) or a terminal device (e.g., a UE or an Internet of Things (IoT) device) and includes a standard transmitter communication unit or system (S-TX-COM) 101 that implements standard communication (e.g., 5G) capabilities using, for example, DFT-s-OFDM generated data communication signals. By operating in "radar mode," the transmitter communication system 101 can form a radar mode signal generator (RM-SIG-GEN) 102 that can, for example, generate a linear chirp signal (chirp) using minimally modified communication components. This can be achieved, for example, by using a (slightly) modified DFT-s-OFDM with a suitable FDSS filter for converting the single-carrier nature of the DFT-s-OFDM signal into a linear combination of cyclically shifted chirp signals in the time domain, as described, for example, in Alphan et al., “DFT-spread-OFDM Based Chirp Transmission”, IEEE Communications Letters, Volume: 25, Issue: 3, March 2021. By exploiting the properties of the first Fourier series and Bessel functions, an FDSS filter for arbitrary chirps can be obtained.

[0152] Furthermore, the transmitter device 10 includes a transmit front end (TX / ANT) 103 (eg, capable of operating at millimeter wave frequencies) comprising a transmitter coupled to an antenna with beamforming capabilities.

[0153] Optionally, a receive front end (RX / ANT) 104 (e.g., capable of operating in mmWave frequencies) may be provided (e.g., as a separate component or integrated with the transmit front end 103 in a joint transceiver front end) comprising a receiver coupled to an antenna with beamforming receive capabilities (e.g., if additional non-distributed transmitter-only radar operations are to be performed to determine target location, shape / size, or material / reflectivity characteristics).

[0154] In addition, the transmitter device 10 includes a transmitter clock generator (TX-CLK) 105 for generating an accurate system clock of the transmitter device 10 .

[0155] Optionally, a transmitter time delay measurement function (not shown) may be provided (e.g., implemented by a processor / controller of the transmitter device 10) which uses the standard transmitter communication unit 101 to perform two-way time delay measurements with a cooperating receiver device (e.g., receiver device 20).

[0156] Optionally, an encryption and decryption function (ENCR / DECR) 106 may be provided for implementing a suitable data encryption / decryption scheme (based on, for example, the Advanced Encryption Standard (AES) algorithm or the Rivest, Shamir, and Adleman (RSA) algorithm) and data integrity verification (e.g., a data authentication scheme using a message authentication code or digital signature). For example, the data is distributed in a protected radio resource control (RRC) message.

[0157] As another option, the transmitter device 10 may include a non-distributed (low-resolution) transmitter radar analysis system (L-RES RAS) 107, i.e., a radar analysis system, which may include a receiver device and / or may include a (low-resolution) transmitter radar analysis system that provides a non-distributed position radar scanning capability, and may include an intermediate frequency (IF) generating mixer (IF-MIX) 107-1, to which a transmitted sensing signal and a replica of an externally received reflected sensing signal are provided and mixed to generate a mixed signal including an IF signal. In addition, the transmitter radar analysis system 107 may include electronic signal processing components, including a transmitter bandpass filter (BPF) 107-2 and an analog-to-digital converter (ADC) 107-3, which is capable of performing intermediate frequency filtering and analog-to-digital conversion on the generated IF signal. Furthermore, the transmitter radar analysis system 107 may include a digital signal processing component and algorithm system (DSP, implemented by, for example, a digital signal processor) 107 - 4 , which provides DSP capabilities for, for example, position detection, pre-processing by clutter removal, and the like.

[0158] As yet another option, the transmitter device 10 may include a sensor assembly including a transmitter movement sensor (TX-MOV-SEN) 108 , such as an accelerometer or the like, that measures movement and vibration of the transmitter device 10 .

[0159] Furthermore, the receiver device 20 may be an access device (e.g., a base station) or a terminal device (e.g., a UE or Internet of Things (IoT) device) and may include a standard receiver communication unit or system (S-RX-COM) 201, which provides standard communication capabilities, such as in 5G, using a data communication signal generated, for example, by DFT-s-OFDM. By operating in "radar mode," the receiver communication system 201 may be capable of forming a radar mode signal generator (RM-SIG-GEN) 202, which generates a linear sensing signal, such as by using a (slightly) modified DFT-s-OFDM signal. The generated sensing signal may be used internally and not coupled to a transmitter or antenna. The waveform of the sensing signal may be generated according to specific input parameters, which may include at least one of a specific start time, phase, amplitude, base frequency, bandwidth, frequency slope, sensing signal repetition frequency, gaps between sensing signals, and the total number of sensing signals.

[0160] Furthermore, the receiver device 20 includes a receive front end (RX / ANT) 204, which includes a receiver coupled to an antenna having beamforming receive capabilities, and which may be capable of operating in millimeter wave frequencies.

[0161] Additionally, the receiver device 20 includes a receiver clock generator (RX-CLK) 205 for generating an accurate system clock of the receiver device 20 .

[0162] Optionally, a receiver time delay measurement function (not shown) may be provided (eg, implemented by a processor / controller of the receiver device 20) which uses the standard receiver communication unit 201 to perform two-way time delay measurements with a cooperating transmitter device (eg, the transmitter device 10).

[0163] Optionally, an encryption and decryption function (ENCR / DECR) 206 may be provided for implementing a suitable data encryption / decryption scheme (based on, for example, the Advanced Encryption Standard (AES) algorithm or the Rivest, Shamir, and Adleman (RSA) algorithm) and data integrity verification that matches the scheme used on the transmitter side (e.g., a data authentication scheme using a message authentication code or digital signature). For example, the data may be distributed in a protected radio resource control (RRC) message.

[0164] As another option, the receiver device 20 may include a (low resolution) non-distributed radar analysis system (L-RES RAS) 207 providing non-distributed positioning radar scanning capability, i.e., a radar analysis system that may include a receiver device and / or may include a (low resolution) transmitter radar analysis system, which may include a transmitter front end (TX / ANT) 203, TX / ANT 203 including a transmitter coupled to an antenna having beamforming capabilities of the receiver device 20.

[0165] In addition, the (low-resolution) radar analysis system 207 may include components shared with an additional high-resolution distributed radar analysis system (H-RES RAS) 209, and may include an IF generating mixer (IF-MIX) 207-1, to which the (internally generated) replica of the transmitted sensing signal and the externally received reflected sensing signal are input to generate a mixed signal including the IF signal; electronic signal processing components, which include a receiver bandpass filter (BPF) 207-2 and an ADC 207-3 and are capable of IF filtering and analog-to-digital conversion of the generated IF signal; and electronic and digital components and algorithmic systems (DSP, such as a digital signal processor) 207-4, which provide DSP capabilities for, for example, position detection, pre-processing by clutter removal, etc.

[0166] The high-resolution distributed radar analysis system 209 can be configured to share the electronics of an IF generation mixer 207-1, configured to mix the input of the internally generated sensing signal with the external received sensing signal provided by the receiver front end 204 based on the provided timing / phase parameters generated by the radar pattern signal generator 202; the electronics of the receiver bandpass filter 207-2 and ADC 207-3, which receive the analog IF signal, filter it with an appropriate bandpass filter, and perform analog-to-digital conversion; and the electronics and digital components and algorithm system 207-4, which provide DSP functionality for the required application, including pre-processing through clutter removal. To prevent the leakage / tampering of potentially privacy-sensitive sensing information about the target, the radar analysis should be run in a secure, tamper-resistant subsystem, and the generated sensing information should be stored in secure memory and / or encrypted with an untamperable certificate, such as a subscriber identity module (e.g., USIM) certificate.

[0167] Alternatively, the final digital processing may be offloaded from the receiver device 20 to the transmitter device 10 or a network function / device or cloud computing resource, which may return the obtained results.

[0168] Optionally, the receiver device 20 may include a user interface (UI / MEM) 210 with data storage and display capabilities that can input information from the user, store the data in the receiver device 20, and output a display to the user. The specific elements of the user interface 210 may depend on the type of receiver device (e.g., UE) and its functionality. For example, a handheld smartphone device may have a complex user interface 210 and display, while an IoT monitoring device may simply have a visual or audible alarm.

[0169] As another option, the receiver device 20 may include a receiver motion sensor (RX-MOV-SEN) 208, such as an accelerometer, a camera, a structured light sensor, etc., which measures the movement and vibration of the receiver device 20 and the position of nearby objects. The receiver device 20 may also transmit its movement and vibration to the transmitter device 10 via its transmitter standard communication unit 201 during the sensing time interval using a series of receiver motion data, which has been obtained by the receiver motion sensor 208. The receiver motion data series may be sent to the transmitter using a separate communication channel between the receiver and the transmitter (e.g., as a series of RRC or medium access control (MAC) control element (CE) messages).

[0170] Matching sensed objects from multiple viewpoints

[0171] The following embodiments enable various use cases for identifying objects in the field of view of a device (e.g., AR glasses), as well as for identifying when two different devices / sensors have sensed or are sensing the same person or object. The underlying "perceptual" wireless network may include many terminal devices (e.g., UEs) and base stations (e.g., gNBs) with different capabilities and modalities deployed to sense objects in the environment. When one or more devices / sensors generate data from one or more viewpoints, identification / matching features may be implemented, whereby the data is matched against a set of criteria and / or whereby the data is matched against a set of (possibly synthesized) simulated / computed / received data from the same or another viewpoint, and / or whereby the data from two or more devices / sensors generates data of different data types, whereby the semantics of the data of one data type matches the semantics of the data of another data type.

[0172] The viewpoint (or observation point) is the location of a sensing object or target area / volume in a reference coordinate system. Together with the field of view of the sensor used to sense the target object or target area / volume and the heading of the sensor (e.g., the direction / orientation / angle of the sensor's field of view or viewing angle), it determines how the object or area is sensed (e.g., which parts of the object's surface and at which angles can be captured / sensed by the corresponding sensor).

[0173] The field of view (FoV) is generally the span of a given scene that can be imaged by a sensor (e.g., a camera), i.e., the extent of the observable world that can be sensed. It can be represented by a set of angles in 3D space and / or by angles together with direction / orientation and / or by angular area and / or by focal length (e.g., of a lens) and sensor size.

[0174] The sensor may be omnidirectional, ie able to sense all surroundings, which may be indicated by a 360 degree FoV or an omnidirectional sign / attribute.

[0175] The proposed solution can be implemented in multiple use cases, such as:

[0176] 1. In a virtual reality or MR scenario where multiple users are using UEs or other terminal devices to interact with their respective elements in a single shared physical location, interoperability issues may arise where digital assets associated with one user need to be rendered by the UE or other terminal device of the user currently viewing them. The viewing user's UE may not locally have the information required to identify key details of the viewed user (such as the identity of the currently viewing user) and / or the virtual reality in which the viewing user is participating, and therefore which digital assets are rendered for them (e.g., their digital clothing). Therefore, the viewing user's UE needs to obtain the above information. In an example, the viewed user's information (e.g., identity) can be derived from data locally available to the viewing user's UE (such as the viewed user's posture data) and / or from the capabilities of the wireless network to which all participating UEs are connected (including sensing and communication).

[0177] 2. In asset tracking, assets are typically tracked by attaching networked asset tags to them. However, such asset tags may be removed from the asset or attached to other assets without the knowledge of the network or the asset owner. Therefore, the proposed matching feature can be applied to such asset tags.

[0178] 3. A sensing network capable of collecting posture, gait, or form information from an individual via Doppler radar may be able to assist in the authentication of that individual.

[0179] 4. When a UE or other terminal device passes between cells, service continuity will be required for sensing functions (such as in call and data functions). This can be achieved by using the proposed matching function to "anticipate" (expect) the arrival of a UE or other terminal device of a given physical form and movement at a cell. In a sensing scenario, sensing the same target object from different viewpoints and / or different sensing modalities can improve the accuracy of sensing measurements / results and / or improve the identification / matching of the target object (for example, in a crowded area) and / or improve the robustness of the sensing of the target (in the case where one of the sensing modalities is impaired (for example, something blocks the camera's field of view)). To this end, it is important to be able to identify whether two devices / sensors are sensing the same target object and / or to be able to convert one type of sensing data into other types of sensing data and / or to be able to calculate, match or interpret sensing data from different viewpoints or matching criteria.

[0180] Figure 3 A sensing and communication system with data processing and matching algorithms according to a first embodiment is schematically shown.

[0181] The first device (A) 10 includes the necessary antennas, communication interfaces, and other components (e.g., a central processing unit (CPU) 14 for processing data) to communicate via a communication network (such as a 5G system including a mobile station (MS) 100 (such as a UE), a radio access network (RAN) 200 including at least one access device (e.g., a gNB) 220, and a core network (CN) 300).

[0182] Furthermore, the first device 10 comprises at least one sensor (S A ) 12 (with optional transmit (Tx) and receive (Rx) units for radio-based sensing) for generating at least one data type (measurement data of the first device 10) based on the sensed information. The at least one sensor 12 may include a camera, a lidar, a sonar, an accelerometer, a radar, etc.

[0183] The second device (B) 20 (which may have a similar structure to the first device 10 (eg, a CPU 24 and optional transmitter and receiver for radio-based sensing)) includes at least one sensor (S B ) 22, which generates different data types (measurement data of the second device 20) based on the sensed information and has different sensing parameters (for example, different positions, different fields of view, different viewing angles, etc.).

[0184] Sensors 12 and 22 may have a set of attributes, which may include a field of view (FoV) of the sensor and / or a heading of the sensor and / or a 3D position of the sensor. Furthermore, sensors 12 and 22 may be operated by and / or housed in and / or attached to the same device, i.e., the first device 10 and the second device 20 may be the same device. In this case, an intra-device communication mechanism may be used to enable the transmission of measurement data and / or segmentation data and / or capability information, etc.

[0185] Depending on the specific use case of the embodiment (as described above and in more detail later), the first device 10 and the second device 20 can be terminal devices (e.g., UE), base stations (e.g., gNB) or other types of access devices, or any other (network) devices with sensing capabilities and network access.

[0186] In addition, the system includes a collection of algorithms, wherein any given algorithm can run locally on hardware of the first device 10 and / or the second device 20, and / or run as part of a network function (e.g., location management function (LMF) 320) on a core network (CN) 300 of the wireless network using hardware accessible to the core network 300, and / or run on third-party hardware as part of an application function (AF), and / or run on any other hardware accessible to the first device 10 or the second device 20.

[0187] The algorithm may include a segmentation algorithm (SA) 40 (set) that can segment the measurement data of the first device 10 and the measurement data of the second device 20 into object-related data about discrete objects of interest (segmented measurement data of the first device 10 and segmented measurement data of the second device 20) and optionally additional (meta) data related to the discrete objects, such as location. The nature of the segmentation algorithm depends on the data type and the use case specific embodiment. For example, for Doppler radar data type, the segmentation algorithm can be configured to cluster reflections and assign temporary labels, while for video data type, the segmentation algorithm can be equivalent to a pre-trained object recognition algorithm that classifies objects within the video.

[0188] In addition, the algorithm may include a synthetic data algorithm (SDA) 30 (set), which can be configured to generate a synthetic data set based on the segmented measurement data of the first device 10. The synthetic data algorithm 30 can be divided into a first algorithm and a second algorithm. The first algorithm is an X to Mesh algorithm (XTM) 32, which is configured to generate a 3D mesh data set for a given segmented measurement data set of a given data type of the first device 10. The second algorithm is a Mesh to Y algorithm (MTY) 34, which uses the 3D mesh data to generate the synthetic data. The Mesh to Y algorithm can have information about the second device 20 so that the synthetic data can be generated to meet certain criteria, including at least one of the same data type as the segmented measurement data of the second device and the same perspective as the sensor 22 of the second device 20 (i.e., adapting the appearance of the same object in the segmented measurement data of the second device 20) or vice versa (i.e., adapting the appearance of the segmented measurement data of the first device 10 based on the objects detected according to the measurement data of the second device 10).

[0189] In addition, the algorithm may include a matching algorithm (MA) 50 that compares the synthetic data derived from the measurement data of the first device 10 with the segmented measurement data of the second device 20 to identify whether any segment in the segmented measurement data of the second device 20 matches the synthetic data of the first device 10, and may output a binary result (match result) for each segment. Optionally, the matching algorithm may be configured to generate a confidence measure (match confidence) for each matching result.

[0190] Note that the above algorithms 30, 32, 34, 40 and 50 may not always be required or may be combined into more complex algorithms (e.g., all algorithms may be combined in a single algorithm) or may be divided into simpler algorithms (e.g., a matching algorithm may include a matching algorithm and a confidence estimator algorithm).

[0191] Figure 4 A process flow chart according to a first embodiment is schematically shown.

[0192] A process is described for matching objects described by data of one given data type and collected by one device with objects described by data of a different given data type collected by a different device. The process is designed to enable two different devices with potentially different data collection capabilities to recognize when they sense the same object.

[0193] The sensor (S) of the first device (A) 10 A )12 Collect measurement data D MA, which may include data about one or more objects (O) 60. Device (A) 10 may send this data to a second device (B) 20 or a wireless network (e.g., to an object matching service). In addition to the data, device (A) 10 may also send information about the field of view (FoV) of sensor 12, the capabilities of sensor 12 (e.g., sensing modality, resolution), the heading of sensor 12, and / or the 3D position of sensor 12 or first device 10 to the second device (B) 20 or the wireless network.

[0194] The sensor (SB) 22 of the second device (B) 20 collects the measurement data D MB , which may include data about one or more objects (e.g., including, for example, one or more objects 60). Device (B) 20 may send this data to the first device (A) 10 or the wireless network (e.g., to an object matching service). In addition to the data, device (B) 20 may also send information about the field of view (FoV) of sensor 22, the capabilities of sensor 22 (e.g., sensing modality, resolution), the heading of sensor 22, and / or the 3D position of sensor 22 or second device 20 to the first device (A) 10 or the wireless network.

[0195] The segmentation algorithm (SA) 40 can be used to calculate the measurement data D of the first device 10. MA and / or the measurement data D of the second device 20 MB Run on to generate the segmented measurement data D of the first device 10 respectively. MAS and / or segmented measurement data D of the second device 20 associated with one or more objects 60 in the data MBS .

[0196] The synthetic data algorithm (SDA) 30 can be used to measure the segmented data D MAS Run on to generate synthetic data D S For example, first, the X to Mesh algorithm (XTM) 32 generates mesh data for each segment-related or object-related data, and second, the Mesh to Y algorithm (MTY) 34 generates synthetic data D for each segment-related or object-related data using the mesh data. S .

[0197] Finally, the matching algorithm (MA) 50 converts the synthesized data D S Each segment and the segmented measurement data D MBS The algorithm compares each segment of the image and can output a binary matching result for each segment (i.e., whether they match or not) and an optional matching confidence.

[0198] The steps of segmentation and synthetic data generation are an exemplary instantiation of a method in which the synthetic data algorithm is based on the measurement data D of the first device 10.MA to generate synthetic data comprising data about at least one object.

[0199] In an alternative embodiment, the measurement data D of the second device 20 may be MB The steps of segmentation and synthetic data generation are performed, and the obtained synthetic data can be combined with the segmented measurement data D of the first device 10 MAS Make a comparison.

[0200] Figure 5 The flowchart of the matching process according to the second embodiment is schematically shown.

[0201] In step S310, measurement data D of a first data type collected by a first device for one or more objects is received or retrieved (eg, by a network device, which may be a terminal device, an access device, or a network function). MA .

[0202] In step S320, measurement data D of a second data type collected by a second device remote from the first device is received or retrieved (eg, by the network device). MB , which may contain data about one or more objects (eg, including, for example, one or more objects of step S310 ).

[0203] In the subsequent step S330, the measurement data D of the first device MA and / or the measurement data D of the second device MB is segmented (for example, at a network device) to respectively generate segmented measurement data D of the first device MAS and / or segmented measurement data D of a second device associated with one or more objects in the data MBS .

[0204] Then, in step S340, the segmented measurement data D of the first device is processed (eg, at the network device). MAS To generate synthetic data D S This can be achieved by first generating mesh data for each segment-related or object-related data, and then using the mesh data to generate synthetic data D for each segment-related or object-related data. S to achieve.

[0205] Finally, in step S350, the synthesized data D S Each segment and the segmented measurement data D MBS Each segment of the is compared (CMP), whereby the output can be a binary match result (MO) for each segment (ie, whether they match or not) and an optional confidence of the match.

[0206] In an additional embodiment that can be combined with other embodiments, the (segmented) measurement data of the second device can be converted into the same intermediate form as the measurement data of the first device, such as grid data, and matching can be performed in the intermediate grid domain, as described in the third embodiment below.

[0207] Figure 6 A modified system structure according to the third embodiment is schematically shown, in which an alternative set of algorithms is used to determine a match.

[0208] An alternative set of algorithms includes a synthesis transformation algorithm (STA) 70 (set) which can combine the two segmented measurement data D of the first device 10 and the second device 20 MAS 、D MBS The set of images is mapped into a common domain (e.g., the 3D mesh data described above) that is intended to facilitate matching. Other examples of common domains could be Fourier transforms or other kinds of machine vision transforms or intermediate forms to be compared at a later stage. Such intermediate forms could be, for example, 3D mesh data or Hough transforms used in computer vision.

[0209] The composite transform algorithm(s) 70 may be divided to cover two types of transforms that may be implemented by a first algorithm and a second algorithm.

[0210] The first algorithm is the X to Grid Algorithm (XTM) 32 (described above), which is configured to segment the measurement data D of a given data type of the first device 10. MAS A given set of segmented measurement data D representing the first device 10 is generated MAS The 3D mesh data set D of the object described MAM .

[0211] The second algorithm is a Y to Grid Algorithm (YTM) 74, which is configured to segment the measurement data D of a given data type of the second device 20. MBS A given set of segmented measurement data D representing the measurement data D of the second device 20 is generated. MBS 3D mesh data set D of the object described MBM .

[0212] Furthermore, the set of alternative algorithms includes an additional mesh alignment algorithm (MAL) 76, which is configured to ensure that the 3D mesh datasets D of the first device 10 and the second device 20 are aligned when necessary. MAM and D MBM The alignment is performed using, for example, the corresponding positions and / or viewpoint data and / or FoV and / or sensing capabilities of the first device 10 and the second device 20. Thus, an aligned grid dataset D is obtained. MAML and D MBML .

[0213] Alternatively, either device may have information (eg, position information) about the other device so that transformed data (eg, mesh data) may be generated from the perspective of the respective other device.

[0214] As another alternative, each device may be supplied (eg, over a network) with the new view coordinates needed to obtain and / or generate the transformed data. This may allow matching between remote devices that are further away.

[0215] Additionally, the set of alternative algorithms may include a matching algorithm (MA) 50 that compares two aligned grid data sets D MAML and D MBML To identify the aligned grid D of the second device 20 MBML Does any of the segments of the data match the aligned grid data D of the first device 10? MAML And a binary result (matching result (MO)) may be output for each segment. Optionally, the matching algorithm may be configured to generate a confidence measure (match confidence) for each matching result.

[0216] Note that the above algorithms 70, 32, 74, 76 and 50 may not always be required or may be combined into more complex algorithms (e.g., all algorithms may be combined in a single algorithm) or may be divided into simpler algorithms (e.g., a matching algorithm may include a matching algorithm and a confidence estimator algorithm).

[0217] Figure 7 The flowchart of the matching process according to the fourth embodiment is schematically shown.

[0218] Figure 7 Steps S510 to S530 correspond to Figure 5 Steps S310 to S330 are not described in detail here.

[0219] In step S540, the segmented measurement data D of the first device and the second device are processed (eg, at the network device). MAS and D MBS , to generate mesh data D for each segment-related or object-related data MAM and D MBM .

[0220] Thereafter, in step S550, the mesh data D of the first and second devices are aligned (e.g., at a network device) using, for example, their respective positions and / or viewpoint data and / or sensing capabilities. MAM and D MBM Thus, the aligned grid dataset D is obtained MAML and D MBML .

[0221] Finally, in step S560, the two aligned grid datasets D are compared. MAML and D MBML , to identify the alignment grid data D of the second device MBML Whether any segment is aligned with the first device grid data D MAML Matching, whereby the output may be a binary result (matching result (MO)) for each segment. Optionally, the matching algorithm may be configured to generate a confidence measure (match confidence) for each matching result.

[0222] In additional embodiments that can be combined with other embodiments, the measurement data D of the first device and / or the second device MA and / or D MB It can be stored in a database, for example.

[0223] In an additional embodiment that can be combined with other embodiments, the segmented measurement data D of the first device and / or the second device MAS and / or D MBS Can be stored in a database, for example.

[0224] In additional embodiments that may be combined with other embodiments, the mesh data or the composite data D S It can be stored in a database, for example.

[0225] In additional embodiments, which may be combined with other embodiments, data stored, for example in a database, may be stored with metadata identifying the type of device or algorithm used to sense or compute the data.

[0226] In additional embodiments that may be combined with other embodiments, when matching is required, the device performing the matching may retrieve the most appropriate data, such as mesh data, from a storage service (e.g., a database) as it reduces the computational complexity of the device (as a single additional transformation is required).

[0227] In additional embodiments that may be combined with other embodiments, the measured data D of the first device and / or the second device MA and D MB This may correspond to measurements of an object over a period of time. This may correspond to, for example, video measurements of a user while walking, from which not only grid data representing the user's form or posture may be extracted, but also frequency data corresponding to the user's walking pattern or the user's heart rate. When creating synthetic data (which may correspond to millimeter wave data), the synthetic data algorithm may not only transform a specific aspect of the measured data (in this example, the video) of the sensed object (e.g., form or posture), but it may also transform multiple aspects of the measured data, such as, in this example, form / posture as well as walking gait and / or heart rate.

[0228] Additionally or alternatively, an AI model targeted / taught to recognize certain objects or movement patterns (e.g., walking or breathing or heartbeat) can be used to determine that a set of measurements of an object over a period of time matches a certain object or movement pattern based on measurement data and / or mesh data or other segmented or synthesized data sets.

[0229] In additional embodiments that may be combined with other embodiments, the matching algorithm may match not only a single aspect of the measured data, but multiple aspects to become a multi-dimensional matching algorithm. Matching can be performed in a variety of ways, for example, by examining all n aspects as matches of an n-dimensional vector, or by examining all n aspects as matches of an n-dimensional weighted vector, or by deriving the combined confidence value as the norm of an n-dimensional (weighted / normalized) vector of confidence values (e.g., norm 0, norm 1, norm 2, norm infinity).

[0230] In additional embodiments that may be combined with other embodiments or implemented independently, if a match is found by the first device 10, the second device 20, or a service in the network (e.g., an object matching service) based on data received from the first device 10 and / or the second device 20 (e.g., the same object can be detected by both the sensor or target object that matches the model of the object, or a data set stored for a viewpoint set, sensor heading, and / or FoV is found), the first device 10 or the second device 20 or the service in the network may send a message to the first device 10 or the second device 20 to adapt its FoV, sensor heading, viewpoint, or sensing resolution, for example, to improve sensing of a particular target or initiate sensing of another target. Such a message may include FoV information, angle information, position information, resolution information. Upon receiving such a message, the first device 10 or the second device 20 may adjust its sensor according to the information in the message. Additionally or alternatively, such a message may include information about focus or target object information (e.g., mesh data, a semantic model of a target, a set of target identification information, a set of reference coordinates) or target area / volume information, which the first device 10 or the second device 20 may use to determine the FoV, sensor heading, or viewpoint, which enables the first device 10 or the second device 20 to sense a given focus or target object or target area, at which point the first device 10 or the second device 20 may adjust its sensor according to the determined FoV, sensor heading, or viewpoint. To this end, the first device 10 or the second device 20 may have some hardware components to implement this (e.g., an adaptive lens for changing the focus, a shutter for blocking a portion of the sensor, a rotation mechanism for changing the sensor heading, a different radio for performing wireless sensing at a higher frequency). Similarly, if the first device 10, the second device 20, or a service in the network does not find a match based on data received from the first device 10 and / or the second device 20, the first device 10 or the second device 20, or the service in the network may send a message to the first device 10 or the second device 20 to adapt its FoV, sensor heading, viewpoint, or sensing resolution, for example, to improve sensing of a particular target or initiate sensing of another target.

[0231] Additionally or alternatively, the first device 10 may send information about the field of view (FoV) of the sensor 22, the heading of the sensor 22, and / or the 3D position of the sensor 22 to the second device 20 or to a service in the network. This information may indicate to which viewpoint, angle, and / or FoV the data sent by the first device is adapted (e.g., to DMAML and DMBML), and / or may indicate the desired viewpoint, sensor heading, and / or FoV that the sensor 22 of the device 20 should use to perform sensing and / or perform matching. Based on this information, the device 20 may be configured or instructed to adapt its viewpoint, sensor heading, or FoV accordingly. Similarly, the second device 20 may send information about the field of view (FoV), the heading of the sensor 12, and / or the 3D position of the sensor 12 to the second device 10 or to a service in the network. This information may indicate to which viewpoint, angle, and / or FoV the data sent by the sensor device is adapted (e.g., to DMAML and DMBML), and / or may indicate a desired viewpoint, sensor heading, and / or FoV that should be used by sensor 12 of device 10 to perform sensing and / or perform matching. Based on this information, device 10 may be configured or instructed to adapt its viewpoint, sensor heading, or FoV accordingly.

[0232] In the following, the combination of Figures 1 to 7 The above embodiments are described.

[0233] Asset Tracking

[0234] In asset tracking use cases, assets are typically tracked via physically attached tags, but tags can be removed and attached to different objects or dropped and lost.

[0235] To address this issue, users can use a UE (e.g., a smartphone with a camera or lidar) or other terminal device to image the object at the moment the tag is attached. The tag can then be used to generate synthetic radar data. This synthetic data can be compared with real radar measurements taken later by the wireless network to confirm that the tag is still attached to the same physical asset.

[0236] Note that if the UE has radar capabilities, the user can also use the UE to directly generate or obtain radar data. In this case, the radar data can be combined with the synthetic data, and the combined data can be used in a later comparison.

[0237] Note that the radar data obtained by the UE and the radar data obtained by the wireless network may not directly match because the pose / orientation of the sensors may be different. Therefore, it may still be necessary to convert the data in one of the datasets (e.g., the radar data obtained by the UE) into a synthetic dataset of radar data, taking into account the sensors and / or viewpoints and / or viewing directions of the UE and the wireless network, etc.

[0238] In such asset tracking use cases, Figure 3 The first device (A) 10 may be a UE such as a smartphone, and the second device (B) 20 may be a line-of-sight sensor, for example, a camera or a lidar sensor. The measurement data D of the first device 10 MA This can be a series of photos or videos from multiple angles of the asset (if sensor 12 is a camera), and / or a collection of lidar measurements taken from multiple angles of the asset (if sensor 12 is a lidar) and / or other measurements from other sensors.

[0239] Figure 3 The second device (B) 20 may be a UE or a base station in close proximity to the tracked asset. The sensor 22 may be a radar sensor, which may include at least one of a dedicated radar sensor placed on a base station (e.g., a gNB), a communication component used in a dedicated sensing mode (e.g., ISAC), and a passive sensing option derived from normal communication signals.

[0240] In this use case, X-to-grid algorithm 32 may be an image-to-grid algorithm (such an algorithm may be configured to take multiple photos of an object (e.g., from different angles) as input to generate a representative grid) or a lidar-to-grid algorithm (such an algorithm may be configured to receive one or more lidar measurements of an object from different angles to produce a representative grid, where the more angles covered, the better the accuracy).

[0241] Additionally, the Grid to Y algorithm 34 may generate synthetic data D that simulates one or more cross sections of the asset to be tracked. S , where cross-sections based on different viewpoints can be synthesized that correspond to predicted views of the imaged asset obtained by the sensor 22 of the second device 20.

[0242] An additional device (asset tag) can be designed to be attached to an object (asset) and / or easily geo-tracked. The asset tag may contain all necessary antennas and other components to communicate via a communication network such as a 5G system. As part of its normal operation, the asset tag may periodically report its location to the 5G system. The asset tag may have an associated identifier (asset tag ID) known to the 5G system.

[0243] Furthermore, an additional database (asset database) may be provided which stores asset tag IDs as well as grid data and / or a set of (other) matching criteria describing the associated assets.

[0244] In addition, an additional algorithm (tag check algorithm) can be provided that initiates the process of checking that the asset tag is still attached to the correct asset by requesting the second device 20 to take a measurement and requesting verification. This can be triggered periodically, opportunistically based on the asset tag coming into proximity with an appropriate second device 20, or can be called by another process on the network when a check is required. If triggered periodically or by an external process, the tag check algorithm can also be responsible for identifying an appropriate second device 20, i.e., a device with, for example, radar or lidar sensing capabilities and within range of the asset tag's location.

[0245] In the following, an example of a process related to this use case is described.

[0246] The user attaches the asset tag to the asset to be tracked. Upon attachment, the user uses the sensor 12 of the first device 10 to capture one or more images of the asset as measurement data D MA , measurement data D MA The X is sent to the gridding algorithm 32 which generates the grid data of the asset (with the asset tag). The grid data and the associated asset tag ID are stored in the asset database. Additionally or alternatively, the raw measured data D may also be stored. MA .

[0247] Later, the tag check algorithm may be triggered periodically or on demand. This may be requested, for example, by the asset owner. In an example, it may be triggered when the asset tag location is determined to be within the range of an appropriate second device 20 (i.e., a UE or gNB with radar capabilities). The tag check algorithm may request an appropriate second device 20 in the vicinity of the asset tag to start collecting radar measurements as measurement data D of the second device 20. MB Knowing the asset tag location can be used to guide measurement parameters.

[0248] The Grid to Y algorithm 34 is then triggered, for example by a tag check algorithm, to generate synthetic data D of the asset from the perspective of the sensor 22 of the second device 20. S The algorithm may synthesize the correct virtual viewpoint using the known asset tag location and the known location of the appropriate second device 20 as a first step, and then generate the synthesized data D of the asset by retrieving the appropriate mesh data from the asset database S .

[0249] Finally, the matching algorithm 50 converts the measurement data D MB With the generated synthetic data D SThe comparison is performed to output a positive or negative match result. A positive match result can be output when the virtual and real Doppler radar datasets have a similarity that exceeds a predetermined numerical threshold. Furthermore, a match confidence level can be calculated based on the average magnitude of the differences between the datasets. If a negative match result is returned, the label checking algorithm can trigger an alert and / or request further action.

[0250] User authentication and authorization

[0251] In the user authentication (identification) use case, an object (e.g., a user) can gain access to a network-assisted (network-supported) authentication (identification) system, where the user initially uses UE sensors to image itself and / or objects (e.g., vehicles) surrounding / carrying the UE, and this data is then used to generate synthetic radar data representing the user / object. Later, the UE can request authentication functionality, where a local base station (e.g., gNB) or another UE images the user / object via radar and compares the image data with the synthetic data to authenticate the UE's user or the object containing / carrying the UE.

[0252] In this use case, Figure 3 The first device (A) 10 may be a UE such as a smartphone or a wearable device, and the sensor 12 of the first device 10 may be a line-of-sight sensor such as a camera or a lidar sensor. Here, the measurement data D MA It can be a series of photos or videos carrying / covering the UE's user's body, face or other biometric features and / or objects from multiple angles (if the sensor 12 is a camera), or a collection of lidar measurements carrying / covering the UE's user's body, face or other biometric features and / or objects from multiple angles (if the sensor 12 is a lidar).

[0253] The second device (B) 20 may be a base station, and the sensor 22 of the second device 20 may be a radar sensor, which may include a dedicated radar sensor placed on a base station (e.g., a gNB), a communication component used in a dedicated sensing mode (e.g., ISAC), and at least one of a passive sensing option derived from normal communication signals.

[0254] For this use case, the synthetic data algorithm 30 may include:

[0255] The X-to-grid algorithm 32 may include a pre-trained adversarial network based on the measurement data D of the second device 20. MB Generate 3D mesh data of the user's body, face, or other biometric features and / or objects carrying / covering the UE.

[0256] The Grid to Y algorithm 34 generates synthetic data D of the radar cross section simulating the imaged user / object SIn this case, cross-sections from different viewpoints may be synthesized based on the positions and / or viewpoint data and / or viewing angles and / or sensing capabilities of the second device 20 and the first device 10, corresponding to the predicted views of the imaged user / object by the sensor 22 of the second device.

[0257] An additional database (user grid database) may be provided, which stores the generated grid data.

[0258] Furthermore, an additional algorithm (authentication request algorithm) may be provided which, when triggered by the first device 10 , initiates synthetic data-assisted authentication.

[0259] In the following, an example of the procedure for this use case is described.

[0260] The user opts in (participates, registers) to a network-assisted authentication (identification) system in which the user can use the sensor 12 of the first device 10 to image or otherwise sense his / her body at several different angles and output that data as measurement data D that is sent to an X-to-mesh algorithm 32 that generates mesh data of the user's body. The mesh data is stored in a user mesh database.

[0261] When the user later uses the first device 10, the authentication request algorithm triggers an authentication session. The local second device 20 (e.g., the base station (e.g., gNB) where the first device 10 is being served) collects the user's body measurement data D MB The device location of the first device 10 may be used to assist in setting up the sensor 22 of the second device 20 to collect this data.

[0262] From the perspective of the sensor 22 of the second device 20, the mesh-to-Y algorithm 32 operates on the mesh data of the user to generate synthetic data D of the user's body. S .

[0263] Finally, the matching algorithm 50 converts the measurement data D MB With the generated synthetic data D S A comparison is performed to output a positive or negative match result. A positive match result can be output when the virtual Doppler radar dataset and the real Doppler radar dataset have a similarity exceeding a predetermined numerical threshold. Furthermore, a match confidence level can be calculated based on the average magnitude of the differences between the datasets. If the match result is negative, or the match confidence level is too low, authentication fails. In this case, reauthentication can be requested, or an alert can be sent to the operator of the first device 10. Otherwise, authentication is positive, and the user is granted access to the first device 10.

[0264] In an embodiment that can be used with other embodiments, the second device 20 can also rely on the first device 10 to perform certain measurements. For example, the second device 20 can use a given sensing technology, such as millimeter wave radar, as a transmitter, and the first device 10 can act as a receiver, where the first device 10 is instructed to provide measurements to the second device 20.

[0265] In embodiments that can be used with other embodiments, this use case may also be applicable to UEs or other terminal devices, including standalone devices, for example, for authentication or enhanced authentication of a user. This may be because, if UEs with sensing capabilities (e.g., mmWave sensing capabilities) are increasingly used, such UEs may also be used to sense certain parameters of the user or the user's environment.

[0266] In one embodiment, user / object authentication may be performed when a user attempts to access a UE. User / object authentication may also be performed when a user / object's UE initiates access to a wireless network or service (such as a sensing service) in the core network, as described in detail in other embodiments of this disclosure.

[0267] In an embodiment, user / object authentication may be based on data sensed over a period of time (eg, when a user is walking towards the UE to access the UE), as this may allow for the determination of certain user-specific characteristics, such as the way the user walks.

[0268] One of the problems with radar systems and wireless sensing systems in general, for both distributed and non-distributed / centralized radar systems, but also for other systems using other sensing modalities, is that within a sensing area / volume, there may be multiple objects that could be sensed / detected. Not all of these objects may be subject to wireless sensing services, may not have subscribed to such wireless sensing services, may not be the intended targets of wireless sensing services, and / or may not even wish to be sensed or participate in sensing services or sensing procedures. Similarly, for systems using other sensing modalities, this problem applies not only to wireless sensing services, but also to other services such as monitoring services, virtual reality or augmented reality services, and / or matching services or viewing object recognition services that utilize wireless sensing or other sensing modalities. In the text that follows, the term sensing service also covers these types of services.

[0269] This is a problem because wireless sensing or sensing using other sensing modalities can reveal personal identification information (e.g., biometrics) and / or other information that may be privacy sensitive (e.g., where a person is or what he is doing). In many countries, users must consent to participate in services that may obtain privacy-sensitive information, particularly in private areas such as one's home. Similarly, 3GPP features may require user consent, depending on local regulations as described in TS 33.501 Annex V, where, for example, the collection, processing and use of privacy-sensitive data (e.g., by means of sensing) may also be limited to specific uses. In addition, devices involved in sensing, particularly devices that may obtain / receive privacy-sensitive information in the process, should be appropriately authorized.

[0270] Typically, if the sensing service or sensing transmitter or sensing receiver determines that the sensing information (e.g., sensing measurements or sensing results related to a detected object) or input / output data of the sensing signal processing does not correspond to given information about how to identify the target (e.g., the determined location is too far from the UE so that the target is being carried, or the shape / size of the target is different (e.g., smaller or larger), or the biometrics are not suitable for the target, or one or more sensing measurements / results are above or below certain thresholds, or the grid data does not match (as described in other embodiments)), the sensing service or sensing transmitter or sensing receiver may discard the received sensing signal and / or discard the sensing information (e.g., sensing measurements or sensing results), and / or discard the input / output data of the sensing signal processing, and / or may not perform any further processing on these measurements, results and / or input / output data and / or may not send them to another processing unit. The sensing service or sensing transmitter or sensing receiver may also generate a notification message and, for example, send it to an application, an application server, a core network function or via / through the NEF for further processing or storage, and / or if the target is not (no longer) detected, information about this situation may be stored on a non-volatile storage device (such as a database).

[0271] The following embodiments describe methods in which authorization may be obtained / provided to initiate sensing of specific targets, and sensing (particularly detailed sensing) of unauthorized / unintended targets may be mitigated / prevented.

[0272] To achieve this, the sensing service, sensing transmitter, or sensing receiver may receive or may be configured with information (e.g., from / by an application, a network exposure function, a policy control function, a subscription database (e.g., a home subscriber service, a unified data management service), an identity database, an authentication / authorization control function, a public safety answering point, e.g., as part of the sensing configuration / parameters) about a target location / area / volume (e.g., a bounded geographic area represented by a set of coordinates, length, size, diameter) in which a target is to be sensed or is expected to be a target and / or how the target is to be identified (e.g., physical characteristics of the target). The target identification information may include information such as size, shape, mass, material composition, biometric characteristics associated with the target (e.g., heart rate signal characteristics, body shape, body absorption / reflectivity characteristics, body posture / movement, body size / mass, diseases / disorders that cause certain identifiable characteristics, such as sleep apnea that causes interrupted breathing during sleep, asthma that causes potentially rapid irregular breathing rates or gasping for breath, claudication that causes unusual body movements, tremors (e.g., Parkinson's disease), expected body temperature patterns, heart rate variability / patterns), the identity and / or location of wireless communication devices or other devices that the target may possess, encompass, include, or carry, etc.). The target identification information may include thresholds or other criteria associated with sensing measurements / results, such as minimum / maximum deviations from a specific location, a set of different shapes or scatter plots of allowed shapes, or multiple shape definitions indicating minimum and maximum shape outlines, size deviations (e.g., maximum / minimum allowed differences in height, width, length, or kilograms), minimum / maximum speeds, a set of possible movement patterns and / or possible deviations thereof, minimum / maximum values of sensed biometric characteristics (e.g., minimum / maximum heart rate or breathing rate), etc. Note that depending on the resolution / accuracy of the radar-based sensing (e.g., depending on the number of transmitters and receivers, the frequencies used, whether non-distributed or distributed sensing is used), target identification information can be defined with different levels of accuracy, granularity, matching criteria (e.g., thresholds).

[0273] Alternatively or additionally, a target may also be indicated by exclusion, i.e., as a person or animal or structure or as not matching a set of criteria (e.g., not a person, animal, object or structure, e.g., matching certain known biometrics or size) and / or as another type of object that should not be detected at a certain location / area or volume (e.g., not matching the biometrics of a person registered to the site, where the biometrics may have been pre-stored), e.g., to detect an intruder / burglar at a house. The information provided to the sensing service, sensing transmitter or sensing receiver (possibly indirectly via the sensing service) may also include a set of phone numbers that should be contacted in the event of certain alarm conditions (e.g., an emergency call number), a set of time periods (e.g., only at night), or a set of triggers (e.g., only when a person is known to be at home, e.g., by receiving a signal from a device that the person may be carrying), when the service should be active.

[0274] The sensing service, sensing transmitter or sensing receiver may also obtain information about devices (e.g., their identities and estimated locations) in the vicinity of the target or target's address / location / home (e.g., a nearby set of nearby base stations or nearby UEs (e.g., UEs placed in a person's home or carried by the person or his family, friends or neighbors) that are able and may be authorized by the network and / or by the user of the device and / or by the target object (or authorized by the network and / or by the user of the device and / or by the target object) to participate in (distributed) sensing of the intended target. Authorization information (which may also include user consent information) may be stored as part of the user's subscription (e.g., in a unified data management (UDM) function of the core network) and / or as part of the sensing service and / or received from a service or application function or an external application or authentication, authorization and accounting (AAA) server (e.g., via an NEF).

[0275] Based on the above-mentioned target position / area / volume information and / or target identification information, the sensing service may select and / or configure one or more sensing transmitter devices and / or one or more sensing receiver devices with a sensing configuration that enables sensing to be performed with the required accuracy to enable matching with the target identification information, for example, by configuring a set of frequencies for the sensing signals, which measurements need to be performed, the number of times the sensing signals should be sent or the number of times measurements should be performed, etc. The sensing service may also provide information about a (sub)set of target areas / positions / volumes and / or target identification information to be sensed to the one or more sensing transmitter devices and / or one or more sensing receiver devices.

[0276] Based on the above-mentioned target identification information, the sensing service and / or the sensing transmitter and / or the sensing receiver can be configured to perform a target matching process based on the configured target identification information, whereby the target matching process includes determining (e.g., by algorithmic processing of the sensing data (i.e., sensing measurements and / or (partial) sensing results) generated by the sensing receiver and / or obtained from the sensing receiver) whether a set of sensing measurements performed on the received sensing signals or a result from the processing performed on the set of sensing measurements and / or (partial) sensing results meets one or more configured criteria (e.g., thresholds) for identifying the target object. This may include determining whether the sensing measurements and / or sensing results fall within certain thresholds and / or boundary conditions, such as, for example, the object is sufficiently close to the target location, the shape of the identified object falls within certain boundaries, the size of the object is close to the expected size, the speed of the object is below a minimum or above a maximum expected speed of the target or below a minimum or above a maximum value to achieve correct sensing of the target object, the movement pattern is a movement pattern that may be expected for the target, the measured biometric characteristic (e.g., heart rate or breathing rate) is below / above a certain expected value for the target, etc.

[0277] In an embodiment that may be combined with other embodiments or implemented independently, the sensing service and / or the sensing transmitter and / or the sensing receiver and / or the first device 10 (which may be a sensing transmitter and / or receiver) and / or the second device 20 (which may be a sensing transmitter and / or receiver) may receive (e.g., from / through an application) or preconfigure or determine information about a model (e.g., a semantic model, a digital twin) of an object (e.g., a metadata set describing the object, or a virtual graphical representation of the object) and / or sensor-related data (e.g., measurement data, (pre)processed sensor output or segmented data or mesh data, It can be captured, stored and / or (pre-)processed by a sensor, and / or synthesized by a sensing device or a sensing service or application) for a set of viewpoints, sensor headings and / or FoV (e.g., radar cross-section) of an object and / or a set of video shots of the object and / or a set of grid data of the object stored in an object database, whereby the data for the viewpoints, sensor headings and / or FoV sets can be generated or stored according to a predefined set of positions (e.g., known positions of base stations) or angles (e.g., one or more angles relative to a reference line oriented towards magnetic north) and / or FoV (e.g., omnidirectional). This information can be used as target identification information and can be used to match sensing data from the sensing transmitter and / or sensing receiver and / or the first device 10 and / or the second device 20 with received information using processes as described in other embodiments, such as by generating data for a viewpoint (e.g., radar cross section) for a particular angle and / or FoV from the received sensing measurements / data and / or sensing capabilities and / or information about viewpoint, heading, FoV from the sensing transmitter / receiver or the first device 10 or the second device 20 and matching it with data for the viewpoint, sensor heading and / or FoV (e.g., radar cross section), sensor heading and / or FoV for a received, preconfigured or determined set of viewpoints. Depending on whether a match is found (e.g., with a certain confidence level), the sensing session may be continued or terminated, or the sensing data may be approved for further processing / storage or discarded, additional sensing operations may be initiated, a (different) target or sensing receiver or sensing transmitter or first device 10 or second device 20 may be selected for further sensing, an event may be generated or a signal may be sent indicating that a matching target was detected or not detected, or authorization of the target may be initiated / continued for sensing (e.g., verifying whether the detected object is an authorized target for the sensing service). In the case of a virtual reality or augmented reality service, the target object may be another participant in the virtual reality or augmented reality service. Target object recognition may be performed to exclude recognition or sensing of "innocent" bystanders without their permission.

[0278] The target matching process may be given as input an (ideal) representation of a signal, and the result of the signal processing (which may include passing the signal through one or more filters) needs to be matched by finding similarities between the processed signal and this (ideal) representation of the signal. This may include identifying overlaps of the processed signal with the (ideal) representation of the signal, possibly changing the amplitude or timing of the signal. This may also include identifying signal shapes, signal peaks and verifying whether these may or may not occur in the (ideal) representation of the signal. Similarly, for sensing modalities such as video or image feeds, the video or image output may first need to be passed through various image processing algorithms, such as noise removal, sharpening, resizing, before additional actions are taken, such as creating segmentation data, mesh data or radar representations of the video or image.

[0279] Additionally or alternatively, the input to such a target matching process may include a description of at least one or more signal characteristics that need to be present in order for the signals to match (e.g., certain signal peaks or signal shapes). The input to this target matching process may also include a set of signal characteristics that should not be present in order for the signals to match (e.g., certain signal shapes, signal peaks). Because some sensing measurements and / or sensing results may be unstable (e.g., measurements that fluctuate between certain values, movement that causes Doppler shifts, small movements, or RF signal interference that causes noise in certain signals), the signal may need to be passed through certain filters (e.g., low-pass or high-pass filters) to remove noise, unwanted spikes, outliers, or trends, or Doppler shifts from the signal. Note that the sensing measurements and sensing results may be measured or calculated over a period of time, thereby removing some outliers during that period and / or using some average values during that period for the signal processing and matching algorithms. The resulting output after these processing steps may be a signal that matches a given (ideal) representation and / or a given set of signal characteristics, thus making the match potentially never 100% accurate. This is further exacerbated if the original or processed sensing signal or sensing measurement or (partial) sensing result lacks sufficient accuracy (for example, because it is represented by a low frequency signal or a low sampling rate or a low accuracy signal). Therefore, the matching result can be provided together with a confidence level or a matching percentage or a standard deviation value. The target matching process can be assigned a minimum confidence level, or a confidence interval, or a minimum matching percentage, or a maximum standard deviation value of one or more configured standards or other target identification information. If the minimum confidence level or the minimum matching percentage or the maximum deviation is not met, the target matching process may not include this in the set of matching criteria or other target identification information.

[0280] Additionally or alternatively, the target matching process may perform matching of sensory measurements and / or (partial) sensory results with an artificial intelligence (AI) model, whereby the AI model may have been trained to recognize a specific target or set of targets, for example, by using sensory measurements and / or (partial) sensory results based on sensing targets in a controlled environment (possibly in various settings). Such an AI model may be provided as input to the target matching process, or may be made available to the target matching process via a communication interface (e.g., running on an edge server). By passing sensory measurements and / or (partial) sensory result sets of actual targets with such an AI model, the AI model may determine whether a given sensory measurement and / or (partial) sensory result, such as a processed signal, matches the content of a model that the model has learned to recognize a specific target. Additionally or alternatively, the AI model may determine a machine learning confidence score that a given sensory measurement and / or (partial) sensory result does identify a target and / or that it matches one or more of the target identification information of the target. The AI model may provide a matching learning confidence score and / or other matching results for further processing in the target matching process.

[0281] The target matching process may produce a set of objects (i.e., matching targets) that match a subset of the target identification information set in the case of a partial match and the entire target identification information set in the case of a full match, whereby, as described above, the match may be enhanced or adjusted using a confidence level or a match percentage. In short, a matching target refers to an object that matches at least a subset of the target identification information (with a certain confidence level or match percentage), for example, by satisfying one or more configuration criteria (e.g., a threshold) for identifying the target object. When a new and / or different object is detected, the sensing service, sensing transmitter, or sensing receiver, or the first device 10 or the second device 20 that performs target sensing or performs a target matching process may assign a new identifier, or may assign an identifier associated with the target identification information set (e.g., the matching criteria for the target), or may assign an identifier based on a target identifier provided by the application, or may assign an identifier based on a subscription identifier associated with the sensing service and / or target sensing, or may assign an identifier based on an identifier of the sensing session. In case of an exact match and / or when the confidence level or match percentage is above a preconfigured threshold, the entity responsible for the target matching process may replace the assigned identifier with an identifier associated with the target identification information set.

[0282] In order to identify the target in the target location / area / volume, the sensing service, the sensing transmitter or the sensing receiver or the first device 10 or the second device 20 may initiate an initial scan of the target area and / or obtain sensing measurements / results resulting from the initial scan of the target area as input to the target matching process. This initial scan may be a low-resolution scan, but may also be a high-accuracy scan, for example, if allowed / enabled / authorized, for example, in certain countries or facilities (e.g., in the case of non-public networks) or certain use cases (e.g., for lawful intercept or emergency situations), such as using distributed radar sensing or in higher frequencies (such as millimeter waves). As described in other embodiments, the sensing signals / measurements may be processed to obtain a set of sensing results, which may reveal zero, one or more objects (e.g., people, animals, houses, cars) detected in the target area. Similarly, in Figure 3 In the FoV of sensor 12 of the first device 10 or sensor 22 of the second device 20, the initial sensing (i.e., initial scan) performed by sensor 12 or sensor 22 may be at low resolution (e.g., low-resolution video, or only outline detection, which may blur the face or other features of a person), but if allowed / enabled / authorized, such as in certain countries or facilities (e.g., in the case of non-public networks) or certain use cases (e.g., for lawful interception or emergency situations), sensing may be performed at high resolution (e.g., high-resolution video). These sensing signals / measurements / results may be processed as described in other embodiments to obtain a set of sensing results, which may reveal zero, one, or multiple objects detected in the FoV of sensor 12 or sensor 22.

[0283] If only one object is detected that may (or may not) match the set of target identification information (depending on the target matching process), the sensing service, sensing transmitter or sensing receiver or the first device 10 or the second device 20 may generate an event and / or send a signal (which may carry a message, for example, to an application server, a core network function or via an NEF) indicating that a matching target or an expected target is present in the scanned area / volume / FoV (possibly enhanced with location information and / or other sensing results related to the detected target), and / or if a target is detected based on the target identification information, information about the detected target may be stored in a non-volatile memory (such as a database) (possibly enhanced with location information and / or other sensing results related to the detected target), and / or additional scans may be initiated and / or further sensing measurements may be performed to verify or determine additional matches with the target identification information, and / or the start of a (detailed) sensing session may be initiated / triggered (only) when the presence of an expected target is detected. To this end, the sensing service, sensing transmitter or sensing receiver or the first device 10 or the second device 20 may initiate additional sensing operations, for example by sending a signal to notify one or more other sensing services or sensing transmitters, sensing receivers, or other devices that may perform sensing using one or more sensing modalities (e.g., the first device 10 or the second device 20) that may involve target (detailed) sensing.

[0284] If multiple objects are detected that may (or may not) match the target identification information set (depending on the target matching process), the sensing service, the sensing transmitter or the sensing receiver or the first device 10 or the second device 20 may generate an event and / or send a signal (which may carry a message, e.g., to an application server, a core network function, or via an NEF) indicating that multiple expected targets were detected and / or multiple objects (e.g., matching targets) were detected that matched (or did not match) the identification information set (but, e.g., it was not sufficiently certain that the expected target was present in the scan area / volume / FoV and / or which detected object was the expected target) and / or the start of the (detailed) sensing session may be delayed / canceled and / or another scan may be initiated and / or further sensing measurements may be performed to verify or determine additional matches to the target identification information (e.g., to reduce the number of potential targets and / or to find a better match to the target identification information set of the expected target).

[0285] In another embodiment, the sensing service or the first device 10 or the second device 20 may initiate an initial scan of the target location / area / volume / FoV and obtain sensing measurements / results resulting from the initial scan of the target area or FoV. This may include raw measurement results (such as the timing or signal strength of the signal), or may be (partial) sensing results derived from the sensing measurements (e.g., the number of detected objects, the location of the objects, the speed of the objects, the size of the objects, the movement pattern of the objects). The sensing service, the sensing transmitter or the sensing receiver or the first device 10 or the second device 20 (as a requesting entity) may provide these sensing measurements / results or a subset thereof to one / another sensing service or sensing application or core network function (e.g., authentication server function (AUSF) or UDM) or an external server responsible for performing the target matching process. For security and privacy reasons, the target matching process may need to be performed within the secure / privacy domain of a specific target (e.g., in a home network (e.g., a Home Public Land Mobile Network (H-PLMN)) that has the target's subscription to the sensing service, or a server operated by a trusted identification authority (e.g., provided by a government) or a server operated by an authorized / trusted application provider), and therefore the target identity may not be shared with the sensing service, sensing transmitter, or sensing receiver, particularly if these will operate in a visited network (e.g., a Visited Public Land Mobile Network (V-PLMN)). After the sensing service, sensing application, or core network performs the target matching process on the provided sensing measurements / results, the sensing service, sensing application, or core network may respond to the requesting entity with whether a match has been found or not and / or with a (temporary) identity associated with the identified target that can be used for further authentication and authorization, as described in later embodiments. The response may also contain information about whether the target is authorized as a target for sensing and / or may contain credentials that can be used to encrypt / decrypt subsequent messages (e.g., if the (temporary) identity is provided in a subsequent message protected by a key based on those credentials). Based on the received response, the sensing service, the sensing transmitter or the sensing receiver or the first device 10 or the second device 20 may stop or continue the sensing operation, initiate additional sensing operations, generate an event or send a signal indicating that a matching target was detected or not detected, or initiate / continue authorization of a target for sensing (e.g., verifying whether the detected object is an authorized target of the sensing service).

[0286] In another embodiment, the sensing service, sensing transmitter or sensing receiver or the first device 10 or the second device 20 may initiate an initial scan of the target location / area / volume / FoV and obtain sensing measurements / results resulting from the initial scan of the target area. This may include raw measurement results (such as the timing or signal strength of the signal), or may be (partial) sensing results derived from the sensing measurements (e.g., the number of detected objects, the location of the objects, the speed of the objects, the size of the objects, the movement pattern of the objects). The sensing service, sensing transmitter or sensing receiver or the first device 10 or the second device 20 (as a requesting entity) may request one or more (other) sensing services or sensing applications or core network functions (e.g., AUSF or UDM) or identity databases (e.g., provided by a government) that maintain / store target identification information to provide one or more target identification information sets (e.g., target identification information that matches one or more sensing measurements / results). Such a request may include information about the scanned target location / area / volume / FoV, one or more sensing parameters / measurements / results (e.g., size of the object, location of the object, speed of the object, movement pattern of the object, shape of the object, material of the object), and / or information about the subscribed sensing service (which may also configure / control the sensing transmitter or sensing receiver) and / or one or more targets expected to be within / near the target location / area / volume / FoV. Based on the request, one or more (other) sensing services or sensing applications or core network functions or identity databases may provide a (sub)set of target identification information for targets whose target location / area / volume and / or target identification information (partially) matches the provided information (e.g., about the scanned target location / area / volume and / or one or more sensing parameters / measurements / results). Similarly, matching with the sensing data from the sensor 22 of the second device or a model (e.g., a semantic model) of an object or data set for different viewpoints, the sensor heading and / or FoV of the object (e.g., stored in a matching database) can be accomplished by calculating data for different viewpoints, sensor headings and / or FoVs (e.g., radar cross-sections) based on the sensing data (e.g., measurement data or segmented data) from the sensor 12 of the first device 10, as described in other embodiments of the present disclosure. Additionally or alternatively, a target identification information set is provided by a network (e.g., a sensing service) or an application (e.g., via an NEF) or an external entity (e.g., a public safety answering point (PSAP)) to the sensing service, sensing transmitter and / or sensing receiver or the first device 10 or the second device 20 as part of configuration information for sensing a target based on the target identification information set, or as part of a request to start sensing a target or target position / area / volume / FoV.The target identification information (sub)set received by the sensing service, sensing transmitter or sensing receiver or the first device 10 or the second device 20 can then be used by the sensing service, sensing transmitter or sensing receiver or the first device 10 or the second device 20 to perform further and / or more detailed sensing of the target, which can be fine-tuned to the provided target identification (sub)set to achieve better matching results, or for example to further determine / exclude one or more detected objects in the initial (low resolution) scan that may or may not match (for example, fall within or outside a threshold set for position, velocity, size or other parameters) the target identification information set to become the expected target.

[0287] Depending on the circumstances detailed / extended / sustained sensing of a target area or set of target objects or other objects detected in a target area or FoV, which may include, for example, sensing through the use of higher frequency or distributed radar or for longer time periods or utilizing more advanced / more accurate targeting algorithms, may be initiated in any event in certain circumstances. Examples of such situations include, for example, in the case of an emergency call or lawful intercept initiating a request based on radar-based sensing of one or more targets and / or a specific area, or where the target area / volume covers a house or facility (e.g., a factory), for which the owner / resident has (implicitly or explicitly) granted permission (e.g., provided user consent) when subscribing to the sensing service or subscribing to the operator's network communication service, or for example through their healthcare provider / service or for example because the sensing service is operated by a non-public network (which may include private infrastructure equipment and core network components, which may include the sensing service, sensing receiver or sensing transmitter), whereby the sensing service / device operates in and / or covers the intended facility, or where the targets and / or sensing receivers and / or sensing transmitters and / or the first device 10 and / or the second device 20 subscribe to the same service / application or are part of the same group (e.g., shared group ID or shared group credentials).

[0288] In an example embodiment, a UE (which may or may not be the first device 10 having the sensor 12 or the second device having the sensor 22) initiates an emergency call with a public safety answering point via a (cellular) network to which it is attached and based on location information provided / obtained during an emergency call in accordance with local regulations (e.g., enhanced 911), sensing transmitters in the vicinity of the location where the emergency call is initiated (e.g., a nearby base station or a nearby mobile phone or the mobile phone making the emergency call) may be instructed (e.g., via a configuration message) to perform a sensing session (e.g., to sense a specified target victim or a target area / volume around the victim or an emergency area given the location of the mobile phone). The instruction may include authorization information, information about the target (e.g., target location / area / volume or some characteristics of the target victim, such as whether the target victim is moving, lying on the ground, in cardiac arrest, etc.) or context (e.g., how many people are gathered around the victim, the distance of people and their devices relative to the victim, the number of injured people, nearby debris), or an identifier or address of the target server, network function / device or public safety answering point (e.g., IP address, URL), or credentials (e.g., public key) for encrypting the results, or requested sensory output / results, such as target location or motion or vital signs. The information about the target may be a target identification information set (as described elsewhere in this disclosure). The target identification information set may be provided by the UE to the core network (e.g., the Emergency Call Session Control Function (e-CSCF) specified in 3GPP TS 23.167) and / or the PSAP, for example, by sending an emergency connection establishment request (e.g., emergency PDU session establishment (e.g., as specified in 3GPP TS 23.167)). The information may be included in an emergency PDU session as defined in TS23.501 and TS23.167, and extended accordingly), or provided to the core network and / or PSAP via an emergency connection (e.g., an emergency PDU session), whereby the E-CSCF may forward the received information to the PSAP. If the UE is capable of performing wireless sensing, the information may be determined by the UE performing an initial scan (e.g., a radar scan) of the victim or another target or emergency area. Similarly, the UE may be a first device 10 having a sensor 12 and capable of sensing one or more objects in the FoV of the sensor 12. Such a UE may include measurement or segmented data from the sensor 12, or result information or FoV information about the detected objects (and other information that may be related to the sensor 12, such as viewpoint and / or sensing heading and / or sensing capabilities) in the emergency connection establishment request or via the emergency connection. The UE may be configured to sense a target victim (e.g., matching one or more default features, such as the shape or size of a person lying on the ground or breathing or bleeding heavily), for example, based on a preconfigured set of target identification information (e.g., sensing criteria).The information provided by the UE and received by the core network and / or PSAP (e.g., a set of target identification information) may then be provided (together with one or more of said instructions) to the sensing service (or another network function, e.g., a location retrieval function (LRF) or LMF responsible for initiating target sensing based on the provided information) and / or directly to a set of sensing transmitters and / or receivers.

[0289] Additionally or alternatively, the UE may provide a set of wireless sensing measurements or sensing results to the core network (e.g., to the E-CSCF) and / or PSAP, for example, by including this information in an emergency connection establishment request (e.g., emergency PDU session establishment) or via an emergency connection (e.g., emergency PDU session). The core network or PSAP may determine the target identification information set based on the provided wireless sensing measurements or sensing results set, and then may provide the target identification information set (along with one or more of the aforementioned instructions) to the sensing service (or another network function, such as an LRF or LMF responsible for initiating sensing of the target based on the provided information) and / or directly to the sensing transmitter and / or receiver set. Similarly, the UE may be a first device 10 having a sensor 12 and capable of sensing one or more objects in the FoV of the sensor 12. Such a UE may include measurement or segmentation data from the sensor 12 or result information about the detected object or FoV information (and possibly other information related to the sensor 12, such as viewpoint and / or sensing heading and / or sensing capabilities) in the emergency connection establishment request or via the emergency connection.

[0290] Additionally or alternatively, a target identification information set may be received from a core network function or database (e.g., UDM / UDR) based on the UE identity received from the UE (e.g., by the E-CSCF), which maps the UE identity with an associated target identification information set. To this end, the UE may indicate (e.g., in a message field during emergency connection establishment) whether the target is a carrying UE or covers a UE that has initiated an emergency call, e.g., because the person is the victim. The retrieved target identification information set may then (together with one or more of the mentioned instructions) be provided to a sensing service (or another network function, e.g., an LRF or LMF, which is responsible for initiating sensing of the target based on the provided information) and / or directly to a set of sensing transmitters and / or receivers or other devices capable of performing sensing using one or more sensing modalities (such as the first device 10 or the second device 20).

[0291] In the case of an emergency call, authorization (including user consent) to perform sensing on the target (e.g., initial scan or detailed / extended sensing) and / or to share sensing results of the target with the PSAP may be provided implicitly, for example, because the request to initiate sensing is made by a core network function that is specifically used in the case of emergency calls (e.g., E-CSCF or LRF) or by the PSAP, or for example, because the request to initiate sensing includes a flag indicating that this is for an emergency call. Similarly, one or more receivers (or if the receiver is part of the same device as the transmitter) or other devices capable of performing sensing using one or more sensing modalities (such as the first device 10 or the second device 20) are activated to participate in the sensing session, and the transmitter and receiver or other devices capable of performing sensing using one or more sensing modalities (such as the first device 10 or the second device 20) may perform sensing according to other embodiments in this document. The sensing results (which may be filtered to include only results related to the specified target, i.e., targets that match a set of target identification criteria provided to the sensing service, sensing transmitter, or sensing receiver, for example, by the E-CSCF or PSAP) may be forwarded by the core network (e.g., via the E-CSCF) to the PSAP. To this end, when the UE includes the E-CSCF during PDU session establishment, the sensing results may be provided to the E-CSCF via the AMF, or the E-CSCF may be provided via, for example, 3GPP The LRF / GMLC specified in TS 23.167 / 23.273 is used to retrieve them, extended for this purpose, for example, by providing functionality similar to the sensing service or by involving the sensing service as described in other embodiments of the present disclosure, or by collecting sensing results directly from a sensing receiver and / or sensing transmitter or other device capable of performing sensing using one or more sensing modalities (such as the first device 10 or the second device 20).

[0292] Figure 8 An example target authorization process according to various embodiments of the present invention is schematically illustrated.

[0293] In an embodiment that can be combined with any other embodiment or can be implemented independently, the first device 10 or the second device 20 may need to initiate an authorization process before initiating or continuing a sensing session (for example, before initiating another scan or before initiating detailed and / or distributed sensing). Such an authorization process may include verifying the authorization information and / or certificates of the network operator or application or user or device or third party that issues the target sensing request and / or provides information on how to identify the intended target and / or the user who subscribes to the sensing service, so as to assess whether the respective entity is authorized to receive sensing measurements or sensing results or other sensing data, and / or is authorized to initiate a sensing request for the target, and / or is authorized to provide configuration information for sensing the target (for example, is authorized to provide a target identification information set). The authorization can be provided by a subscription database (for example, UDM) of the requesting user or device or intended target and / or stored in a subscription database (for example, UDM) and / or retrieved from a subscription database (for example, UDM). Alternatively, the authorization can be provided by an application server or core network function and / or obtained from an application server or core network function or through an NEF. Alternatively, authorization may be provided by and / or obtained from a lawful intercept service or PSAP. In the case of a lawful intercept or emergency call (i.e., using a PSAP), authorization (including user consent) to sense the target (e.g., initial scan or detailed / extended sensing) and / or share target sensing results with the PSAP or lawful intercept service may be provided implicitly, for example, because the request to initiate sensing is completed by a core network function (e.g., E-CSCF or LRF) specifically for emergency call situations or by the PSAP, or, for example, because the request to initiate sensing includes a flag indicating that this is for an emergency call. If authorization fails or cannot be verified, an event and / or error message may be generated, and / or sensing of the target may be aborted. Because the sensing rules for public spaces may be different from those for private spaces, authorization and whether it needs to be performed may also vary depending on the location, area, or volume where the target is to be sensed or the sensing is to be performed. Furthermore, in the event that only one object (i.e., a matching target) is detected that matches the target identification information set (partially when matching a subset of the target identification information set or completely when matching the entirety of the target identification information set), it may be necessary to perform this authorization procedure or authorization verification. In one example, the target identification information set (and / or the set of sensing measurements and / or results within certain thresholds) may be linked to a mobile subscription identifier or user identifier, such as a subscription permanent identifier (SUPI), or to an identifier (e.g., an identifier of a wireless communication device carried or covered by the target, or a wireless communication device carried or owned by a person subscribed to the sensing service) from which the mobile subscription identifier or user identifier can be derived (e.g., after verification with an authentication server function (AUSF)).The link between the target identification information set and the mobile subscription identifier or user identifier can be stored, for example, as part of a unified data repository (UDR) or UDM function in the core network or in a separate database or AAA server, from which a core network function (such as the AUSF) can retrieve the link information during or after authentication. Information linking the target identification information set to the mobile subscription identifier or user identifier can also be pre-provisioned by the application or retrieved from the application, or retrieved from the application during or after authentication. To this end, the application can communicate with the corresponding core network function (such as the UDM / UDR or AUSF) via the NEF. The information linking the target identification information set to the mobile subscription identifier or user identifier can further include an association with one or more identifiers (preferably temporary or intermediate identifiers that can be changed or updated for privacy reasons (e.g., based on a set of rules or matching criteria)), and can include information about whether the user or device is subscribed to the sensing service and / or whether the device associated with the mobile subscription is authorized and / or capable of acting as a sensing transmitter or sensing receiver or as a first device 10 or a second device 20. These (temporary or intermediate) identifiers may be provided to a target matching entity (e.g., a sensing service or a sensing transmitter or a sensing receiver (possibly indirectly via a sensing service) or a sensing application or a core network function) that is capable of performing a target matching process. If (e.g., by an initial radar scan) the target matching entity finds a potential target, the target matching entity (or the sensing transmitter or the sensing receiver or the first device 10 or the second device 20 or the sensing service to which the result of the target matching process (which may include a (temporary) target identifier) is sent) may initiate an authentication and / or authorization process using such a (temporary / intermediate) identifier as input to an authentication and / or authorization request, and / or may use a set of target identification information (and / or a set of sensing measurements and / or results) as input to an authentication and / or authorization request, and / or may first retrieve a mobile subscription identifier or a user identifier based on the set of target identification information and / or the set of sensing measurements and / or results, and then use the retrieved identifier as input to the authentication and / or authorization request. The authentication and / or authorization request may be directed to a core network function, such as the AUSF and / or UDM, which may verify whether the intended target is authorized for the sensing service and may also verify whether user consent has been provided. To this end, the core network function (e.g., the AUSF and / or UDM) may retrieve a mobile subscription identifier or user identifier (e.g., from a UDR or a database) by using a (temporary / intermediate) identifier and / or target identification information (and / or sensing measurement / result set).Since the mobile subscription identifier or user identifier can be associated with one or more UEs, the network can also send a notification to the one or more UEs (e.g., to inform the user that the sensing service is activated), and / or can request confirmation from the user of the one or more UEs to initiate and / or approve sensing of the target, and / or can also request the location of the one or more UEs and use the location of the one or more UEs to verify whether the one or more UEs are in the vicinity of the target (e.g., as an additional check that the target is correct or to request these one or more UEs to participate in sensing the target), and / or can perform a primary authentication with the one or more UEs.

[0294] In such Figure 8In the example authorization process shown, the sensing service 30 and / or the first device (e.g., sensing transmitter) 10 and / or the second device (e.g., sensing receiver) 20 performs an initial scan 801 of a target location, area, or volume (i.e., an initial sensing operation 801). As shown, the sensing service 30 (or the first device 10 or the second device 20) can send sensing measurements and / or results (e.g., a sensing information set) from the initial scan 801 (i.e., send the output of the initial sensing operation 801) to the target matching entity 40 via a message exchange 802. The target matching entity 40 can then perform a target matching process 803 based on the sensing measurements and / or results from the initial scan 801 and the target identification information set. If a partial or full match with the target identification information set is found for the target (i.e., if the target is matched, a subset of the target identification information set is matched in the case of a partial match or the entire target identification information set is matched in the case of a full match), then as shown, the target matching entity 40 (or the sensing service 30 or the first device 10 or the second device 20 to which the result of the target matching is sent) may request authorization for the target by sending a (temporary) identifier associated with the target or the target identification information set to an authentication and / or authorization entity 50 (e.g., an AUSF, a UDM, an AAA server, a sensing application, or a combination thereof) via a message exchange 804. The authentication and / or authorization entity 50 may perform an authentication and / or authorization process 805, wherein the authentication and / or authorization entity 50 may further authenticate the target (e.g., by deriving the identity of the device or user subscribing to the sensing service based on the provided (temporary) identifier and, for example, by performing a primary authentication with the corresponding device), and / or may verify whether the target is authorized to be a target for sensing (e.g., based on subscription information directly or indirectly linked to the provided (temporary) identifier associated with the target or target identification information set), and / or may verify whether the user or target subscribing to the sensing service or affected by the sensing service has provided user consent to be sensed / used for sensing. The authentication and / or authorization entity 50 (possibly in collaboration with other core network and RAN entities) may also send a notification to the device 60 linked to the same subscription in a message exchange 806 indicating that the target is subscribed to the target for the sensing service. In the same message exchange 806, the device 60 may send a message back to the authentication and / or authorization entity 50 to confirm that sensing of the target may proceed. Once the authentication and / or authorization process 805 performed by the authentication and / or authorization entity 50 has been completed, the authentication and / or authorization entity 50 will notify the entities involved in the sensing operation of the corresponding target (e.g., 10, 20, 30, and 40) through the authorization information process 807, which authorizes the target as a target for sensing, and based on this, it can then continue to sense the target.

[0295] In an embodiment that may be combined with other embodiments or implemented independently, in order to further improve the privacy of sensing operations, a device carried or surrounded by a target (particularly a wireless communication device (e.g., a UE device)) may be used to trigger or initiate a sensing operation of a target or target object that carries or covers the device. The wireless communication device may establish a connection to a network that can operate a sensing service, or to an application server or core network function that can communicate with the sensing service, or to a sensing transmitter, or to a sensing receiver, and may trigger or initiate a sensing operation by directly or indirectly sending a signal (which may carry a message) indicating such a trigger to the sensing service or the sensing transmitter or the sensing receiver. Such a message may include the device's potential sensing transmitter or sensing receiver capabilities, may include location or area or volume information about the device itself or about the intended target, may include authorization information and / or credentials, and / or information about user consent, may include identification information of the target or an identifier associated with a set of target identification information, and / or may include a set of sensing measurements or results. Upon receiving such a trigger for initiating a sensing operation, the sensing service may obtain and / or verify authorization of the device (e.g., by obtaining the identity of the device and by checking information in a subscription database (e.g., UDM) to determine whether the user of the device is subscribed to the sensing service, and / or whether the device is authorized to participate in the sensing operation, and / or whether the user of the device has provided consent to be the target of the sensing operation). If the user of the device or the device is indeed authorized, the sensing service and / or the first device 10 and / or the second device 20 may initiate and / or perform the sensing operation as described in the present disclosure. Note that initiating a sensing operation may include receiving and / or retrieving a target identification information set or an identifier associated with the target identification information set (e.g., if the target identification information set and its associated identifier (set) have been provided before or during pre-configuration of the first device 10 and / or second device 20 and / or the sensing service 30 involved).

[0296] Optionally, the sensing service may send a signal to a device carried or covered by the target, indicating that a sensing operation is commencing or is about to commence. The device may display a notification to the user, or may request confirmation from the user that the sensing operation is commencing (or automatically provide confirmation based on device configuration). Upon the sensing operation, a signal may be sent back to the sensing service indicating whether confirmation has been obtained, after which, if confirmation has been obtained, the sensing operation is initiated or further performed. In an example, a wireless communication device (e.g., a mobile phone, IoT device, sensor device, wireless tag, or other UE) carried or covered by the target has a subscription with the network. The user of the wireless communication device may also subscribe to the sensing service. A core network function (e.g., a UDR or UDM, or a separate database or AAA server) may store an association between a mobile subscription identifier or user identifier (such as the SUPI of the wireless communication device carried or covered by the target (subject), or the SUPI of a wireless communication device carried or owned by a person subscribing to the sensing service), or a (temporary or intermediate) identifier from which the mobile subscription identifier or user identifier can be derived, and a set of target identification information (and / or a set of sensing measurements and / or results within certain thresholds). The information linking these identifiers to the target identification information set may also include information about whether the user of the device or the device is subscribed to the sensing service and / or whether the device associated with the mobile subscription can be authorized and / or capable of acting as a sensing transmitter or sensing receiver and / or the first device 10 or the second device 20. When a wireless communication device carried or covered by a target (object) or user subscribed to the sensing service registers to the network and / or the sensing service, or when a wireless communication device carried or covered by a target or user subscribed to the sensing service is connected to a sensing transmitter or sensing receiver or the first device 10 or the second device 20, the identifier of the wireless communication device may be provided by the wireless communication device to the core network function responsible for authentication and / or authorization of the device (e.g., to the AUSF or UDM). After authentication or as part of the authentication process, the core network function responsible for authentication and / or authorization of the device may check information stored in the UDR or UDM or a separate database or AAA server regarding whether the user of the device or the device is subscribed to the sensing service and / or whether user consent has been provided and / or whether the device associated with the mobile subscription can be authorized and / or capable of acting as a sensing transmitter or sensing receiver or the first device 10 or the second device 20 based on a given identifier and / or may retrieve a mobile subscription identifier or user identifier based on a given identifier. The identifier used by the wireless communication device carried or covered by the target may be a subscription concealed identifier (SUCI) or a 5G globally unique temporary identifier (GUTI), which the wireless communication sends to the core network as part of the connection establishment and / or primary authentication process as specified in TS 33.501.However, benefits may be provided if a wireless communication device carried or covered by a target can use another or additional identifier (preferably a temporary identifier) to indicate to the core network that the wireless communication device is subject to wireless sensing or sensing via other sensing modalities. The identifier may be pre-configured by the core network on the device (e.g., by a policy control function (PCF)), or configured by the network (e.g., by an AMF) when the device connects to the network, or may be provided as part of a sensing request (e.g., a mobile terminated or network initiated sensing request initiated by an RSMF). The core network function responsible for authentication and / or authorization of the device (e.g., an AUSF or UDM) may use the identifier to verify whether the device is authorized to use sensing services, retrieve user consent information, retrieve a set of target identification information associated with the device, etc.

[0297] Alternatively or additionally, authorization may be provided or obtained by an application server or from a core network function or through an NEF, or may be provided and / or obtained from a lawful interception service or PSAP. The core network function responsible for authentication and / or authorization of the device may also retrieve a target identification information set associated with a given identifier or a mobile subscription identifier or a user identifier retrieved based on a given identifier, or may retrieve or create an (intermediate or temporary) identifier associated with the target identification information set. If the authentication and / or authorization is successful and / or if the target identification information set can be successfully retrieved, the target identification information set or the (intermediate or temporary) identifier associated therewith may be provided to the sensing service 30 or the sensing transmitter or the sensing receiver or the first device 10 or the second device 20.

[0298] In addition, credentials can be provided that the relevant devices (e.g., one or more sensing transmitters and / or one or more sensing receivers) need to use to securely send (e.g., with integrity and / or confidentiality protected) any sensing measurements and / or results or other sensing information about one or more targets / objects, and / or sensing configuration information to other devices or services and / or applications involved in the sensing service or sensing session and / or operation.

[0299] Additionally or alternatively, it is verified whether identification information of a target (and / or sensed measurements and / or result set) provided during registration and / or connection setup matches such retrieved target identification information set.

[0300] Additionally or alternatively, the network may use a mobile subscription identifier or user identifier associated with one or more UEs to send a notification to the one or more UEs (e.g., notifying the user that a sensing service is activated) and / or request confirmation from the user of the UE for initiating and / or approving sensing of a target, and / or may also be used to request the UE's location and use it to verify whether the UE is in the vicinity of the target (e.g., as an additional check that the target is correct or to trigger a sensing session and / or operation).

[0301] Additionally or alternatively, a wireless communication device carried or possessed by a potential target may be instructed to display instructions for the target or target object to perform a specific movement (e.g., waving, swinging, taking a few steps in a certain direction) that can be detected by the sensing service, for example, when performing an initial radar scan or at a specific time. If motion is indeed detected, then it can be determined that the potential target is indeed the intended target or target object.

[0302] In an embodiment that may be combined with other embodiments or implemented independently, a wireless communication device (possibly in conjunction with a set of sensors and / or a set of sensing transmitters and / or sensing receivers connected to the wireless communication device) (e.g., the first device 10 or the second device 20) may determine a set of target identification information by performing wireless medium measurements or sensor readings or performing an initial radar scan of the target in order to identify a set of unique characteristics by which the target can be identified. For example, it may use signal / data processing / analysis to detect specific patterns in wireless medium measurements, sensor readings, or radar scan measurements / results (e.g., unique movement patterns or biometrics), for example, by analyzing segmented data or grid data as mentioned in other embodiments. To this end, the wireless communication device or a network function / server to which the wireless communication device is connected may run an AI model to learn how to identify the target (e.g., by identifying specific patterns) by feeding the target with corresponding wireless medium measurements, sensor readings, and / or radar scan measurements / results. The model may also be fed with information related to different objects that should not be identified as targets (e.g., wireless medium measurements, sensor readings, and / or radar scan measurements / results). The AI model may initially perform a coarse-grained classification of objects and people based on some high-level features (e.g., male, medium height, weight), and use a set of features of a specific target object as input to determine a specific set of target objects with these features in a specific area and / or select a specific AI model trained for objects with these features. A user / subscriber of the sensing service may be required (e.g., based on a re-request / message received from the network) to place his phone very close to the target object so that the AI model can learn about the specific target object during this initial phase, and then use the AI model to sense the target without requiring the phone to be very close to the target.

[0303] Additionally or alternatively, a wireless communication device carried / surrounded by a potential target can be instructed to display instructions for the target to perform a specific movement (e.g., waving, swinging, moving a few steps in a certain direction), which can be detected by the AI model, for example, when performing an initial radar scan or at a specific time. The resulting target identification information set or the AI model itself (or a portion thereof) can be transmitted to a core network function or application server and / or a sensing service, a sensing transmitter or a sensing receiver, or the first device 10 or the second device 20, where it can be used to identify the target using the mechanism described in other embodiments. The target identification set can be stored together with an identifier of the wireless communication device or an identifier of the AI model. The sensing service, the sensing transmitter or the sensing receiver, or the first device 10 or the second device 20 can use such an identifier to identify the wireless communication device or the AI model and send a request to verify whether the target identification information set and / or the sensing measurement / result set matches the target.

[0304] In embodiments that may be combined with other embodiments or implemented independently, a sensing service, a sensing transmitter, or a sensing receiver, or the first device 10 or the second device 20 may receive information about a target for sensing and / or about other potential objects that should be excluded from sensing or from sensing measurements / results from a heat / motion sensor, camera, or monitoring system (e.g., capable of generating heat maps or process video footage) or via an external application program interface (e.g., a web-based exposure function). The sensing service, the sensing transmitter, or the sensing receiver, or the first device 10 or the second device 20 may use this information to determine a target location, target area, or target direction in order to, for example, direct and / or cause the receiver to focus its antenna / receiving element toward the target by changing the Field of View (FOV). The sensing service, the sensing transmitter, or the sensing receiver, or the first device 10 or the second device 20 may also use this information to correlate sensing measurements / results with the information to determine whether the sensing measurements / results correspond to the target for sensing (e.g., by comparing measured / calculated characteristics of the sensed object / target with measured / calculated characteristics of the object / target based on the information). The sensing service, the sensing transmitter or the sensing receiver or the first device 10 or the second device 20 may also use this information to trigger the start of a (only) (detailed / distributed) sensing session when the presence of an expected target is detected in this information.

[0305] According to another embodiment, the sensing service, the sensing transmitter or the sensing receiver or the first device 10 or the second device 20 determines, based on an initial (low resolution) scan of the target or a detailed scan of the target (e.g., if allowed / enabled / authorized), that the sensing signal does not or cannot adequately identify the target object based on the target identification information set. For example, this may be because the resolution / accuracy may be too low (e.g., due to a low frequency being used), because the sensing signal may be blocked, because the distance may be too great, because the target may not adequately reflect the sensing signal or may absorb too much of the sensing signal, or because the target is moving, or because the sensing transmitter or the sensing receiver is moving). Based on this determination, the sensing service, sensing transmitter or sensing receiver or first device 10 or second device 20 may decide to reposition itself, delay sending the sensing signal (e.g., waiting for the target, receiver or transmitter to move to a new location), adjust the sensing signal transmission characteristics / waveform, such as sending information / instructions (e.g., a warning signal, requesting the receiver to move closer to or farther from the target location or change its angle toward the target, reconfigure its antenna, adjust sensing parameters or sensing measurements / results that the transmitter can use to adjust the transmission of the sensing signal) to the sensing transmitter, sensing receiver, first device 10, second device 20 or sensing service or sensing application via NEF, select another receiver or first device 10 or second device 20 to sense the target, or send a signal to another transmitter or receiver or first device 10 or second device 20 to initiate sensing of the target. If the first device 10 or the second device 20 has a display (for example, in the case of a mobile phone) or is connected to a display, the first device 10 or the second device 10 can display a notification, whereby the notification can display a request and / or instruction to the user to move the first device 10 or the second device 20 or the target to another location, or change its FoV or sensor heading.

[0306] Figure 9 An embodiment of a flow diagram of a sensing operation (eg, a radar-based sensing operation) including identification and authorization for sensed targets is schematically illustrated.

[0307] In the optional initial session request (RS-REQ) step S401, a receiver device (e.g., a terminal device), or a transmitter device (e.g., an access device), or a first device 10, or a second device 20, or a sensing service, or a sensing application (e.g., via NEF), or a mobile device carried / included by a target, or a mobile device subscribed to a sensing service may send a sensing session request (e.g., using an RRC or NAS message) or a request for a service that may involve sensing (such as a virtual reality or augmented reality service), which may be enhanced with information about the location of the receiver device, transmitter device, first device 10, second device 20, or mobile device to a wireless network that operates or provides access to the corresponding service. The request and / or corresponding information may be sent as part of a PDU session request.

[0308] Optionally, the receiver device, the transmitter device, the first device 10, the second device 20 or the mobile device may also provide information about the target location or area or volume of the FoV, and / or a target identification information set or an identifier associated with the target identification information set, and / or (a part of) an AI model capable of identifying the target, and / or an identifier for authorizing the device to use the sensing service or participate in the sensing operation, and / or the required scanning time.

[0309] Optionally, the receiver device, transmitter device, first device 10, second device 20 or mobile device is authenticated by the network and is authorized to use the sensing service or participate in the sensing operation (e.g., by verifying whether subscription information associated with the device's unique identifier includes information whether the device has subscribed to the sensing service or is authorized by the user (e.g., the target of the sensing service) to participate in the sensing operation of the target).

[0310] In the optional response request confirmation (REQ-CONF) / rejection (REQ-DEN) step S402, the sensing service and / or transmitter device and / or receiver device and / or first device 10 and / or second device 20 determines whether it / they can respond to the request (e.g., given its current communication needs, sufficient bandwidth is available for the signal) and sends a confirmation or rejection response to the requesting device. The response (e.g., using an RRC or NAS message) may include a target identification information set or an identifier associated with the target identification information set and / or other sensing configuration information. The response may also include credentials for securely transmitting (e.g., integrity / confidentiality protected) any sensing measurements / results or other sensing information about one or more targets / objects, and / or sensing configuration information about other devices, services, or applications involved in the sensing service or sensing session / operation. The response may also include a message notifying the user that the sensing service is activated and / or requesting confirmation from the user of the UE for initiating / approving sensing of the target and / or may also include a request for the UE's location (if not provided in the request), for example, to use it to verify whether the UE is near the target.

[0311] Optionally or alternatively, the sensing service or transmitter device or the first device 10 or the second device 20 may find potential transmitter or receiver devices or potential first devices 10 or the second device 20 that are close to the intended target (e.g., by requesting the last known location from a location database / service, or by requesting the potential device to send its known location information, or obtaining the location from the potential device through trilateration / triangulation / round-trip time calculation based on the signal received from the potential device), and may voluntarily request (e.g., using an RRC or NAS message) the transmitter or receiver device or the first device 10 or the second device 20 for sensing. The sensing service or transmitter device or the first device 10 or the second device 20 may send sensing configuration information to the transmitter or receiver device or the first device 10 or the second device 20 involved in sensing the target based on the target identification information set. Similar to the above-mentioned confirmation or rejection response, the request may include a target identification information set or an identifier associated with a target identification information set and / or other sensing configuration information, and may also include credentials for securely sending (e.g., integrity / confidentiality protection) any sensing measurements / results or other sensing information about one or more targets / objects, and / or sensing configuration information about other devices or services or applications involved in the sensing service or sensing session / operation. The request may also include a message for notifying the user that the sensing service is activated and / or requesting confirmation from the user of the UE to initiate / approve sensing of the target, and / or may also include a request for the UE's location (if not provided in the request), for example, to use it to verify whether the UE is in the vicinity of the target.

[0312] Then, an optional time synchronization (T-SYNC) and delay compensation (D-COMP) step S403 is initiated, in which the receiver clock is synchronized to the transmitter clock by sending a timing signal to the receiver device. Similarly, other devices involved in sensing (such as the first device 10 or the second device 20) can synchronize their clocks.

[0313] In an optional subsequent target position acquisition (TP-ACQ) step S404, the target position / area / volume information is determined by the transmitter device, the receiver device, the first device 10, the second device 20, or the sensing service, for example, by performing an approximate radar object position scan in the direction or FoV indicated by the receiver device, the first device 10, or the second device 20 as an initial target position estimate.

[0314] Alternatively or additionally, information about the target position / area / volume / FoV may be provided as part of the sensing configuration or may be provided (indirectly) from the receiver device, the transmitter device, the first device 10, the second device 20 or the mobile device (as mentioned in step RS-REQ), which the transmitter device may use as target position information.

[0315] Alternatively or additionally, the target identification set or an identifier associated with the target identification information set may be provided to the receiver device, the transmitter device, the first device 10, the second device 20, or a sensing service.

[0316] Then, in a transmitter beamforming direction selection (BFD-SEL) step S405, the transmitter device selects an appropriate direction (for beamforming) for performing radar-based sensing (distributed or non-distributed) based on the target location information / area / volume as a transmitter target direction. Similarly, the first device 10 and the second device 20 can select an appropriate direction or FoV based on the target location information / area / volume to perform sensing of the target, or can select an appropriate viewpoint to calculate data for different viewpoints, sensor headings, and / or FoVs (e.g., radar cross-sections) for matching (e.g., corresponding to the viewpoint, sensor heading, and / or FoV of another device (e.g., the second device 10 in the case of the first device 10, and the first device 10 in the case of the second device), the other device involves matching or corresponding to the position, angle, and / or FoV of data stored or synthesized for a (predefined) set of viewpoints, sensor headings, and / or FoVs.

[0317] In the subsequent signal parameter generation, such as chirp parameter generation (CP-GEN), step S406, the transmitter device may select appropriate parameters of the signal and generate matching parameters for signal generation (eg, through DFT-s-OFDM processing).

[0318] Then, in an optional subsequent (radar-based) sensing session parameter transmission (RSP-TX) step S407, the generated parameters and / or the selected start time and / or the position of the transmitter device, the first device 10 or the second device 20 and / or the target position information / area / volume / FoV are protected, for example, encrypted using an encryption algorithm and sent to the receiver device, the first device 10, the second device 20, and decrypted at the receiver device, the first device 10, the second device 20 using a corresponding decryption algorithm.

[0319] In the following optional receiver-transmitter relative position and delay estimation (RX-TX-P / D-EST) step S408, the receiver device can use the transmitter position plus its own known receiver position or round-trip delay measurement to calculate the relative offset (or equivalent optical transit time) between the transmitter device and the receiver device. Similarly, the first device 10 and the second device 20 can use each other's position or round-trip delay measurement to calculate the relative offset (or equivalent optical transit time) between the first device 10 and the second device 10.

[0320] At the signal (e.g., chirp) start time, the transmitter device may initiate a transmitter generation (TX-C-GEN) step S409 and generate and transmit a signal or signal sequence based on generation parameters via an antenna beam formed in the direction of the transmitter target direction. Similarly, the first device 10 and the second device 20 may initiate sensing of the target at the indicated start time.

[0321] In an optional transmitter movement serial transmission (TX-MOV-TX) step S410, the transmitter device or the first device 10 or the second device 20 transmits its detected movement and / or vibration to the receiver device or other device (e.g., the second device 20 in the case of the first device 10, or the first device 10 in the case of the second device 20) during the sequence or service sense as a series of transmitter movement data. This information can be used to compensate for movement while performing matching (e.g., between the viewpoint of the first device 10 and the viewpoint of the second device 20).

[0322] In a receiver reflected signal acquisition (RX-R-SIG-ACQ) step S411 , the receiver may collect reflected radio signals, whereby it may obtain received signals using beamformed reception directed toward a target.

[0323] The above steps S401 to S411 may also be applied to a CSI-based distributed sensing system.

[0324] In an optional receiver IF signal generation (RX-IF-GEN) step S412, the receiver device uses the obtained sensing signal start time, transmitter-receiver delay, and sensing signal generation parameters to generate a synthetic internal analog sensing signal that matches the transmitted sensing signal, and mixes the signal with the received signal to generate an IF signal.

[0325] Additionally or alternatively, the receiver may perform measurements (e.g., determining the time of arrival of a received sensing signal, determining the angle of arrival of a sensing signal, determining the amplitude or frequency of a signal) or perform digital signal processing of the received sensing signal (e.g., performing filtering of the signal, such as bandpass filtering, or determining a deformation of the signal).

[0326] In a subsequent optional receiver signal processing (RX-SIG-PROC) step S413, the resulting IF digital signal data or output of measurements and / or digital signal processing performed on the received sensing signals is processed to produce sensing information (e.g., sensing measurements / results or application-specific data, such as the position, motion, vibration, etc. of a detection object that may be a potential / intended target).

[0327] Additionally or alternatively, the resulting IF digital signal data or output resulting from measurements and / or digital signal processing performed on the received sensing signals and / or generated sensing information is sent to a sensing service or transmitter device for further processing.

[0328] In an optional target identification (T-ID) step, the receiver device, transmitter device, or sensing service uses IF digital signal data, or outputs generated by measurements and / or digital signal processing performed on received sensing signals, or sensing information generated from previous steps, to detect a set of objects and / or determine a set of sensing information for one or more detected objects and / or determine whether a set of sensing information for one or more detected objects satisfies one or more configuration criteria for identifying a target based on a set of target identification information. Similarly, the first device 10, the second device 20, or the sensing service can use measurement data or segmented data from a sensing target (in the FoV of the device's corresponding sensor) to match and / or identify the object in the manner described in other embodiments. For example, the target identification set may be pre-configured, or may be transmitted as part of a sensing operation / session request (e.g., from a core network function or application (e.g., via NEF), or from a device connected to the network), or may be sent (from an AUSF or UDM) to the corresponding receiver device, transmitter device, first device 10, second device 20, or sensing service after authentication or authorization of the sensing service of the device connected to the network (which may be carried or covered by the sensing target), or it may be retrieved from a core network function or database based on an identifier received as part of the sensing operation / session request or as part of the authentication / authorization step, whereby the identifier is associated with the target identification information set. Based on the determination, the receiver device, transmitter device, first device 10, second device 20, and / or sensing service may:

[0329] Stop or continue the sensing operation;

[0330] Initiate additional sensing operations;

[0331] ●·Generate an event or send a signal indicating the detection or non-detection of a matching target; or

[0332] • Initiate / continue authorization of a target for sensing (eg, to verify whether a detected object is an authorized target for sensing services).

[0333] Furthermore, in an optional receiver target position update transmission (RX-TP-UD-TX) step S414, the receiver device may send updated and improved target position information to the transmitter device based on the result of step S413 to enable the transmitter device to continue accurate beamforming toward the target.

[0334] Additionally, an optional transmitter and receiver motion compensation (TX / RX-MOV-COMP) step S415 may be integrated, wherein the measured movement and / or vibration of the transmitter device and receiver device are subtracted from the motion detected by the radar.

[0335] Finally, in a user interface, data storage, and display (UI / DS / DISP) step S416, the resulting data (e.g., sensing information about the target object or information about whether a matching target is detected or not detected) may be stored and / or may be sent to a network service or application (e.g., via an NEF) and / or may be displayed by a receiver device, a transmitter device, the first device 10, the second device 20, or other device that can receive the result data from the core network service or application (e.g., a mobile device carried / contained by the target). The user interface is used to collect (if necessary) user input information.

[0336] In the following additional embodiments, details of the specialized processing applied to the digitized IF signal are described (e.g., in Figure 4 in step S413).

[0337] Figure 10 An embodiment of a flow chart of a position and movement detection process is schematically shown.

[0338] This embodiment may be relevant to use cases such as object counting, object motion detection and measurement, infrastructure monitoring, etc. In this case, the receiver device or the transmitter device may request to establish a process for regular radar operation, for example, repeat radar sensing every fifteen (15) minutes.

[0339] In the initial background clutter subtraction (BG-C-SUB) step S501, background subtraction of clutter (e.g., undesired multipath signals) from the digital IF signal (i.e., IF frequency data) is performed. Background subtraction can be achieved by distinguishing foreground information from background information based on the variation in data received at different times. This can be achieved by applying a recursive moving average (RMA) or a Gaussian mixture model (GMM) to learn the mean of the path distribution.

[0340] Then, in a surface identification (SF-ID) step S502, each surface is identified based on the constant lines detected in the IF frequency data.

[0341] For objects with measurable velocity, in the surface velocity identification (SF-V-ID) step S503, the velocity of each isolated surface is identified by averaging the phase change of data extracted from that surface through several sequential sensing signals (e.g., by applying a Doppler FFT) after phase extraction and phase unwrapping. The sensing signal reflected at the moving surface causes a Doppler frequency shift proportional to the velocity of the surface. This frequency shift introduces a phase shift in the detected sensing signal.

[0342] For objects with slow and long-term movement, the movement can be found in the slow movement detection (SL-MOV-DET) step S504 by determining its position (range, direction) at regular times and calculating the change of the position over time.

[0343] Figure 11 An embodiment of a flow chart of a heart rate and respiratory rate detection process is schematically shown.

[0344] Next, in an initial background clutter subtraction (BG-C-SUB) step S601, background subtraction of clutter from the digital IF signal (ie, IF frequency data) is performed.

[0345] Then, in the target surface selection (T-SF-SEL) step S602, the correct surface of the target user is selected from the constant line (in the correct range) in the IF frequency data.

[0346] In a subsequent phase data isolation (PD-ISO) step S603, the phase data from the selected surface is isolated and phase unwrapped (eg, by applying a Doppler FFT).

[0347] Alternatively, the phase can be represented by the complex components of the sine and cosine of the signal (this avoids the need for phase unwrapping).

[0348] Then, in a phase filtering (PS-FIL) step S604, the phase signal is bandpass filtered for a heart rate frequency range (e.g., 0.6-4 Hz) and / or a respiratory rate (e.g., 0.1-0.6 Hz) to derive heart rate data and / or respiratory rate data.

[0349] Finally, in a vital signal extraction (VS-EXTR) step S605, the resulting data is processed to extract vital sign signals from the noise, for example using an algorithm such as a deep neural network trained on a dataset collected together with a "gold standard" (such as an electrocardiogram (ECG) and / or a stretch-respiratory sensor) to compensate for noise and background motion to extract the desired signal (heart rate, respiratory rate), signal variability (e.g., heart rate variability), and confidence values for the accuracy of the data values.

[0350] Figure 12 Another embodiment is shown in FIG. Figure 12 An example sensing system 700 is schematically shown whereby a network (e.g., Figure 7) configured or controlled by the wireless network as depicted in the RF sensing management function (RSMF) deployed by the wireless network configures or controls configuration parameters and / or sensing requirements, and / or collects or combines sensing transmitters (sTX) and / or sensing receivers (sRX) and / or sensing results of the first device 10 and / or the second device 20, for example to perform matching and / or identify a target object. Such an RSMF may be deployed as a separate function or service in the core network, as part of an existing function in the core network (e.g., as part of or extension of the location management function (LMF) specified in, for example, 3GPP TS23.273), as part of a wireless access device (e.g., a base station), or, for example, as part of an application function or edge application or cloud server (which may indirectly provide configuration information or sensing requirements and / or receive sensing results via a network exposure function (NEF)), and may generally be considered a sensing service and / or may support sensing capabilities as described for the sensing service in this disclosure.

[0351] The RSMF may comprise a (network) communication unit capable of sending and receiving messages to / from a sensing transmitter (sTX) and / or a sensing receiver (sRX) and / or the first device 10 and / or the second device 20 and / or other core network functions and / or services (e.g. as specified in 3GPP TS 23.501, in particular as Figure 12 , UDM, UDR, AUSF, and AMF functions and / or services depicted in the present disclosure), may include non-volatile storage for storing sensing capabilities received from a sensing transmitter (sTX) and / or a sensing receiver (sRX), and may include a processing unit for running a sensing application or operation to determine parameters to be configured for the sensing transmitter (sTX) and / or the sensing receiver (sRX) (e.g., based on the sensing capabilities received from the sensing receiver (sRX) and / or from the sensing transmitter (sTX), and / or based on sensing requirements (e.g., as received or determined from an application or other service), and / or based on information about a target object (TO) (e.g., a target identification information set, as described in other embodiments of the present disclosure)), collect sensing results from the sensing transmitter (sTX) and / or from the sensing receiver (sRX), and / or perform matching or object identification (e.g., using algorithms such as one or more synthetic data algorithms (SDA) 30, one or more segmentation algorithms (SA) 40, matching algorithm (MA) 50), and / or further process the collected sensing results.

[0352] The RSMF may be deployed as part of a system 700 comprising a set of sensing transmitter devices (sTX) (e.g., base stations, access points, or UEs (e.g., mobile phones)) and a set of sensing receiver devices (sRX) (e.g., base stations, access points, or UEs (e.g., mobile phones)) and a set of first devices 10 and a second device 20, whereby the sensing transmitter and receiver devices (sTXs, sRX) may be co-located and therefore one device and part of the same device (and therefore may be controlled and operated as a single entity), and whereby the RSMF may be (securely) connected directly or indirectly to these sensing transmitter, receiver devices (sTX, sRX), the first device 10, and / or the second device 20 via a set of wireless and / or wired connections, and whereby the RSMF and the involved sensing transmitter, receiver devices (sTX, sRX), the first device 10, and / or the second device 20 may communicate via a messaging protocol (e.g., based on or extending the NAS protocol as defined in 3GPP TS 24.501, or as defined in 3GPP TS 24.502). The LTE positioning protocol and the NR positioning protocol are configured to communicate with each other using the RRC protocol defined in TS38.331, the Long Term Evolution (LTE) Positioning Protocol (LPP) as defined in 3GPP TS37.355, or the New Radio (NR) Positioning Protocol (NRPP) as defined in TS38.455.

[0353] The RSMF and / or the sensing transmitter device (sTX) and / or the sensing receiver device (sRX) and / or the first device 10 and / or the second device 20 may support a method or service flow comprising the following steps which may be performed in any order:

[0354] When a sensing receiver device (sRX) (e.g., a UE) or the first device 10 or the second device 20 registers with the network, the sensing receiver device (sRX) may provide its wireless sensing capabilities (e.g., device information (such as the number of antennas or the frequency range supported), wireless sensing signal processing capabilities, the ability to act as a sensing receiver or sensing transmitter or both, wireless sensing signal transmission capabilities (e.g., frequency, timing, phase, the type of signal it can generate), etc.), and other sensing capabilities (such as video or other sensing modalities) directly to the RSMF using a signal or message sent from the sensing receiver device (sRX) to the RSMF at 709 or indirectly to the RSMF using a signal or message sent from the sensing receiver device (sRX) to the sensing transmitter device (sTX) at 712 and then sent from the sensing transmitter device (sTX) to the RSMF at 710. This may also include capability information about supported sensing data types, algorithms (e.g., for segmenting data), etc. The sensing receiver device (sRX) may also include its own location information (if known).

[0355] Alternatively or additionally, the location of the sensing receiver device (sRX) may be obtained from the LMF or location server or from a radio access device (eg, base station) to which the sensing receiver device (sRX) is connected or co-located.

[0356] Similarly, when a sensing transmitter device (sTX) (e.g., a wireless access device such as a base station (e.g., a mobile base station relay device)) or the first device 10 or the second device 20 is added to the network, it can use the signal or message on 710 to provide its wireless sensing capabilities to the RSMF.

[0357] It should be noted that in alternative embodiments, the (wireless) access device may also be OAM (operation, administration and maintenance) managed, whereby the RSMF may be deployed as part of the OAM or may be connected to the RSMF to exchange signals or messages (e.g., sensing capabilities of the wireless access device, configuration messages for sensing, or sensing measurements or sensing results).

[0358] The sensing receiver device (sRX) or the sensing transmitter device (sTX) or the wireless access device or the core network function (e.g., AMF) with which the first device 10 or the second device 20 is registered may forward or redirect the signal or message or capability information (as received from the sensing receiver device (sRX) or from the sensing transmitter device (sTX) or from the first device 10 or from the second device 20) to the RSMF (e.g., based on the device's identity or session identity or the RSMF identity that may be provided in the registration message). The sensing receiver device (sRX) or the sensing transmitter device (sTX) or the first device 10 or the second device 20 may also send its capabilities after the initial registration, for example, using an RRCUECapabilityInformation message as specified in 3GPP TS 38.331, or through an LPPProvideCapabilities message as specified in 3GPP TS 37.355, or as part of a sensing session establishment request message (e.g., through a separate / new NAS message extending a message as defined in 3GPP TS 24.501, through a separate or new RRC message extending a message as defined in 3GPP TS 38.331, or through a separate or new LPP or NRPP message extending a message as defined in 3GPP TS 37.355 and TS 38.455, respectively). Note that the capabilities of each device involved in sensing may be different. For example, the RF signal processing capabilities of a UE may differ from those of a base station. For example, a UE may be able to determine the position or movement of a target object (TO) but may not be able to determine the shape of the target object (TO). Or, for example, a UE may be able to receive and perform measurements on received sensing signals but may not be able to generate and transmit wireless sensing signals. Furthermore, the supported sensing modalities or data types may differ. Consequently, the configuration of each of these sensing transmitter and sensing receiver devices (sTX, sRX) and the first device 10 and the second device 20 may differ, or may vary depending on the capabilities or roles they assume (e.g., whether they serve as a sensing transmitter or a sensing receiver). If a device can serve as both a sensing transmitter (sTX) and a sensing receiver (sRX), the sensing transmitter and receiver roles may be independently configured and / or activated and may change dynamically (e.g., they may serve as both intermittently or simultaneously depending on a given schedule or based on messages received, for example, by the RSMF or another network function or by a local application).

[0359] -Based on the sensing requirements of a (5G) core network service (e.g., provided by or via a GMLC or LMF or AMF) or an external application (e.g., provided via an NEF) or an external application (e.g., provided during registration with the core network), and / or based on the received capabilities, the RSMF may determine a set of wireless access devices (e.g., base stations) and / or UEs and / or other devices to be used for sensing, and may configure one or more of these devices as transmitters of wireless sensing signals, or configure one or more of these devices to participate in sensing of a target (e.g., using sensor 12 or sensor 22) using a signal or message sent directly from the RSMF to a sensing transmitter device (sTX) at 706. To this end, the core network service may provide relevant information for sensing (e.g., sensing needs / requirements) by issuing a request to the RSMF for sensing using a network initiated location request (NI-LR) (e.g., as defined in TS 23.273), which may be extended to include information about the target to be sensed and / or about sensing requirements (e.g., which sensing results, such as speed, need to be calculated and / or accuracy requirements) and / or about sensing configuration information (e.g., target location / area / volume information, which may be based on the location of the UE initiating the request, or if the location of the UE is unknown and still needs to be determined, based on an identifier of the UE initiating the request) and / or capability information about one or more sensing receivers or sensing transmitters or the first device 10 or the second device 20. This may also include information about the object's model (e.g., semantic model) and / or datasets for different viewpoints, the object's sensor heading and / or FoV (e.g., radar cross section) and / or mesh datasets of the object stored in the object database, information about the FoV of the device involved in sensing the target (and possibly other information related to the sensor used, such as viewpoint and / or sensing heading and / or sensing capabilities) or the viewpoint / angle of stored data for different viewpoints, information about the sensor heading and / or FoV, information about the sensing modes or data types supported by the device involved in target sensing, and information about which segmentation algorithms are supported or required. The RSMF is capable of receiving and interpreting such information, on which the RSMF can then initiate the selection and configuration of the sensing transmitter device. Similarly, the UE can issue a Mobile Originated Location Request (MO-LR), or another client (e.g., an application function) can issue a Mobile Terminated Location Request (MT-LR) carrying the above information to the RMSF.If the location of the requesting UE (or the identity of the UE included in the request to the RSMF, for example, triggered by a core network function to initiate sensing via the RSMF) is used as the target location and the location of the UE is unknown, the RSMF may first request the LMF to determine the location of the UE, after which the RSMF may use the obtained location as the target location, possibly in addition to some other information (such as the (preconfigured or estimated) distance between the UE and the target, or (preconfigured or estimated) information about the emergency / disaster area). In addition, one or more of the wireless access device (e.g., a base station) and / or the UE and / or other devices to be used for sensing may be configured as a second device 20 for matching purposes, or configured as a receiver of a wireless sensing signal, using a signal or message transmitted directly from the RSMF to the sensing receiver device (sRX) 707 or indirectly from the RSMF, i.e., sent from the RSMF to the sensing transmitter device (sTX) at 706 and then transmitted from the sensing transmitter device (sTX) to the sensing receiver device (sRX) at 711. The sensing transmitter and receiver devices (sTX, sRX) may also be co-located.

[0360] The device configuration information may include information about the wireless sensing signal to be used (e.g., timing, frequency, phase offset, wireless sensing signal identification), identification of the algorithm or filter used for processing, wireless sensing application or session identifier, destination for sending signal processing results, information about the FoV of the device involved in sensing the target or the viewpoint / angle of the stored data of different viewpoints, the sensor heading direction and / or FoV of the target (e.g., radar cross section), information about the sensing modalities or data types supported by the device involved in sensing the target, information about which segmentation algorithms are supported or required to be used, etc. (e.g., as described in the present disclosure). Some of these parameters may also be determined by the device itself. For example, the sensing transmitter device (sTX) may determine the timing of the sensing signal (i.e., which resources are used for the sensing signal). These parameters may be exchanged directly with the sensing receiver device (e.g., via DCI or Sidelink Control Information (SCI) signals or messages specified in 3GPP TS 38.212 (e.g., using a recognizable specific (new) format to indicate reception or transmission of sensing signals and / or sensing signal parameters such as frequency), or via semi-persistent scheduling (SPS) indicating a set of repetitive resources for sensing signals), or indirectly via the core network.

[0361] - Based on the sensing requirements of the (5G) core network service (e.g., as part of the authentication and / or authorization process for the target of the sensing service) or an external application, the RSMF may obtain information about a set of target objects. This information may include (rough) location information (or, for example, the last known location) or area information (e.g., the address of a factory, hospital, or house, or the (geographical) area or volume represented) where the target object is expected to reside or where the target object often resides, or may include information about how to identify a certain target object (e.g., physical characteristics, materials, shape, etc.) (i.e., a target identification information set as described in other embodiments of the present disclosure), or may include the identity of a device that a person may own or carry, etc. (e.g., as described in other embodiments of the present disclosure). The RSMF may use this information about the set of target objects to select and configure the set of sensing transmitter and / or receiver devices (sTXs, sRX) and / or the first device 10 and / or the second device 20 to participate in sensing of the indicated target or target area / volume (this may include information about the wireless sensing signals to be used, as described above in the previous section) or for a particular FoV, and / or may forward and / or configure some of this information to the set of sensing transmitter and / or sensing receiver devices (sTX, sRX) and / or the first device 10 and / or the second device 20. For example, the RSMF may provide a target identification information set or an identifier associated with the target identification information set to the set of sensing transmitter and / or receiver devices (sTXs, sRX) and / or the first device 10 and / or the second device 20.

[0362] Additionally or alternatively, a UE device carried or covered by a target object (TO) may establish a connection to a network (e.g., to an AMF) via 701 and may trigger or initiate a sensing operation by sending a signal (which may carry a message) indicating such triggering or initiation to the RSMF directly (e.g., via a tunneled connection over 701 and 715) or indirectly (e.g., via the AMF over 715 or via the AUSF over 705, whereby the UE may use a message set to the AMF or AUSF that is different from the messages used between the AMF or AUSF and the RSMF). Upon receiving such a trigger or initiation for initiating sensing, the AMF or AUSF or RSMF may initiate or request authorization for sensing services for the UE. For example, the AUSF may obtain the UE's SUPI based on the identity provided by the UE to the AMF through 701 and then sent from the AMF to the AUSF through a message through 702, or based on the identity provided by the UE from the AMF through 710 and then sent from the AMF to the RSMF through 715 and then sent from the RSMF to the AUSB through 714. Based on the obtained SUPI, the AUSF may send a message to the UDM through 703 to check or verify information in a subscription database (e.g., UDM) to determine whether the user of the UE device is subscribed to the sensing service and / or whether the UE device is authorized to participate in the sensing operation and / or whether the user of the UE device has agreed to become the target of the sensing operation. If the user of the UE device is indeed authorized, the UDM or the AUSF or the AMF may notify the RSMF through a message sent at 704, 705, or 715, respectively. The message may contain a target identification information set or an identifier associated with the target identification information set (e.g., provided by the UDM / UDR, which may store this information as part of the subscription information for the sensing service). Thereafter, the RSMF, the sensing transmitter device (sTX) and / or the sensing receiver device (sRX) and / or the first device 10 and / or the second device 20 may initiate or perform sensing as described in the present disclosure. Note that initiating a sensing operation may include receiving or retrieving a target identification information set, or an identifier associated with the target identification information set (e.g., if the target identification information set and its associated identifier set have been provided previously or during pre-configuration of the sensing transmitter and receiver devices (sTX, sRX) and / or the RSMF involved).

[0363] Optionally, the RSMF may send a signal or message to a UE device carried or covered by the target object (TO) (e.g., via a tunnel connection over 715 and 701) indicating that a sensing operation is starting or is about to start. The UE device may display a notification to the user, or may request the user to provide confirmation that he / she / it agrees to start the sensing operation (or automatically provide confirmation based on the UE device configuration), and upon the sensing operation may send a signal back to the sensing service (e.g., via a tunnel connection over 715 and 701) indicating whether confirmation has been obtained. And if confirmation is obtained, sensing is initiated or further performed. The AUSF may optionally provide credential information to the RSMF via 705, and / or the RSMF may determine a set of credential information and may provide it to the AUSF via 714. After successful authentication and / or authorization, the AUSF or RSMF can provide the credential information to the devices involved (e.g., sensing transmitter device (sTX), sensing receiver device (sRX), first device 10, second device 20), and the devices involved can use the credential information to securely send (e.g., integrity and / or confidentiality protected) any sensing measurements and / or results (i.e., sensing information sets) or other sensing information, and / or sensing configuration information about one or more target objects to the RSMF or other devices or services or applications involved in the sensing session or sensing operation.

[0364] The UE device carried or covered by the target object (TO) may provide information about its location and / or a target identification information set or an identifier associated with the target identification information and / or other sensing capability / configuration information set after it has registered with the RSMF with the network (e.g., via an AMF or LMF to which the RSMF may connect to obtain the location of the UE), or may be requested by the RSMF or LMF to provide its location or participate in a location determination process so that the RSMF can obtain the location of the UE device and / or may be requested to provide a target identification information set or an identifier associated with the target identification information and / or other sensing capability / configuration information set.

[0365] The location information can be used as an (initial) target location and / or can be used to configure one or more sensing receivers and / or one or more sensing transmitters and / or the first device 10 and / or the second device 20 to sense TO, i.e., the RSMF can use the location information of the UE device and the location information of the set of sensing receiver devices and / or the set of sensing transmitter devices and / or the first device 10 and / or the second device 20 that it may have stored or can obtain, in order to select and configure the set of sensing transmitters and / or sensing receiver devices (sTX, sRX) and / or the first device 10 and / or the second device 20 located near the UE device (and therefore near the TO) to enable these devices (sTX, sRX) to participate in the sensing operation of TO. Similarly, the RSMF can use a set of target identification information or identifiers associated with the target identification information and / or other sensing capability / configuration information sets to select and configure a set of sensing transmitters and / or sensing receiver devices (sTX, sRX) and / or a first device 10 and / or a second device 20 that are capable of participating in or are best suited to participate in TO sensing based on the target identification information (for example, by determining the required / expected accuracy, the RSMF can select sensing transmitters, sensing receiver devices (sTX, sRX) and / or a first device 10 and / or a second device 20 that can achieve the required / expected accuracy based on the accuracy, for example, because they support sensing using a high frequency band).

[0366] It should be noted that the RSMF may provide one or more of the UE device and / or (selected) sensing transmitter device (sTX) and / or sensing receiver device (sRX) and / or the first device 10 and / or the second device 20 with location information about the UE device and / or location information about one or more sensing transmitter devices (sTX) and / or one or more sensing receiver devices (sRX) and / or the first device 10 and / or the second device 20. In addition, the sensing transmitter device (sTX) or the sensing receiver device (sRX) or the first device 10 or the second device 20 may each provide location information about itself or about other sensing transmitter devices (sTX) or about other sensing receiver devices (sRX) or about other first devices 10 or second devices 20 to (further) other sensing transmitter devices (sTX) and sensing receiver devices (sRX) and the first device 10 and the second device 20. This information may be used to determine the location of the target object (TO) during processing of sensing measurements and / or sensing results (as described in other embodiments of the present disclosure).

[0367] Alternatively, if the target location or area or volume information or FoV information is not available, the RSMF can trigger a (broadcast) search function, in which the sending transmitter device (sTX) or the first device 10 or the second device 20 is requested to sense the environment to determine the rough location information of the set of target objects (TO).

[0368] Additionally or alternatively, one or more of the devices involved in the sensing (e.g., a base station that may include both sensing transmitter and sensing receiver capabilities) may determine a coarse location or position of the target object (one or more TOs) (e.g., based on non-distributed radar-based sensing) and provide this information regarding the coarse location or position of the target object (one or more TOs) to the RSMF.

[0369] Alternatively or additionally, the coarse position (or last known position) of the target object (TO) or, more generally, the target position or area or volume or FoV may be provided by an external application (e.g., via an NEF) or may be obtained, for example, from an LMF, as specified in 3GPP TS 23.273, or from a network data analysis function (NWDAF), as specified in 3GPP TS 23.288, e.g., based on the identity of a device or UE device that is expected or known to be attached to or carried by the target object (TO). The RSMF or the sensing transmitter device (sTX) or the sensing receiver device (sRX) or the first device 10 or the second device 20 may provide coarse positioning or position information about one or more target objects ( / TO) or, more generally, the target position or area or FoV volume to the one or more sensing receiver devices (sRX) and the one or more sensing transmitter devices (sTX / sTX) involved and the first device 10 and the second device 20 involved.

[0370] Alternatively or additionally, the sensing function or service (RSMF) may obtain information about devices (e.g., information about their identities and estimated locations) in the vicinity of a target object (TO) (e.g., a set of nearby base stations or nearby UEs that can and may be authorized (or authorized) by the network and / or by the user of the device and / or by the target person or target object owner to participate in the (distributed) sensing of the intended target. The authorization information (which may also include user consent information) may be stored as part of the user's subscription (e.g., in the UDM function of the core network) and / or as part of the RSMF and / or may be available from the service or application Function or external application (e.g., via NEF). RSMF may use information about the sensing transmitter and / or receiver devices (sTX, sRX) and / or the first device 10 and / or the second device 20 in its selection and configuration of the sensing transmitter and / or sensing receiver devices (sTX, sRX) to be used and / or the first device 10 and / or the second device 20. The devices involved in the sensing may be invited and / or configured by sending a message that may include a session identifier and / or a sensing signal identifier and / or a target identification information set or an identifier associated with the target identification information set.

[0371] Alternatively or additionally, an initial radar scan or sensing operation performed by one of the sensing devices that can support both transmitter and receiver roles, or one of the sensing devices that supports sensor 12 in first device 10 or sensor 22 in second device 20, may indicate that the accuracy of the sensing measurements obtained may not be sufficient to meet the required accuracy (e.g., as indicated in the RSMF or received or configured, e.g., by an external application). The sensing device involved may determine this on its own and notify the RSMF, or the RSMF may determine this based on sensing results it may receive from the respective sensing devices.

[0372] Alternatively or additionally, the RSMF may determine, based on the capabilities of the sensing transmitter and / or receiver devices (sTX, sRX) and / or the first device 10 and / or the second device 20 and / or the available frequency band or spectrum in a particular area, and / or through previous measurements (e.g., obtained by or from a network analysis function such as NWDAF), that the accuracy of the sensing transmitter, receiver device (sTX, sRX) involved and / or the accuracy that can be obtained in a given sensing area may not be sufficient to meet the requirements of the application. The RSMF may use this information (possibly together with the received capabilities and location information of the sensing transmitter and / or receiver devices (sTX, sRX) and / or the first device 10 and / or the second device 20 in the area) as a trigger to select other or additional sensing transmitters and / or sensing receiver devices and / or the first device 10 or the second device 20 in the vicinity of the target object (TO), and / or improve the sensing measurements and sensing accuracy (e.g., by changing to a higher frequency and / or a larger bandwidth, by increasing the number of signals and / or the number of signal measurements, or by selecting a different algorithm).

[0373] - The RSMF may activate one or more of the selected sensing transmitter device (sTX) and / or sensing receiver device (sRX) and / or the first device 10 and / or the second device 20 to activate sensing, for example, by initiating a sensing session directly at 706 and / or 707, respectively, or indirectly via the sensing transmitter device (sTX) at 706 and subsequently at 711. Activation of the sensing transmitter device (sTX) and / or sensing receiver device (sRX) and / or the first device 10 and / or the second device 20 may be automatically triggered by receiving the above-mentioned sensing configuration (e.g., giving a start time or a set of time intervals when sending a sensing signal), or may be triggered by a separate message (e.g., an additional LPP message containing, for example, a sensing session identifier) or by a separate signal (e.g., detection of a recognizable sensing signal matching one or more of the given signal characteristics or signal identifiers provided during configuration).

[0374] Based on the received configuration information and / or the rough location of the target object (TO) or more generally based on the target location or area or volume or FoV, the sensing transmitter device (sTX) and / or one or more of the first device 10 and / or the second device 20 will direct a wireless sensing signal 708 or will initiate sensing in the direction of the target location or area or volume or FoV using the sensor 12 or the sensor 22. The time at which such a wireless sensing signal 708 is transmitted is based on the time at which sensing is initiated using the sensor 12 or the sensor 22, e.g., timing information (e.g., a sensing start time or a set of time intervals or a set of (preconfigured) time or frequency resources for sensing) as configured and shared with the sensing receiver device (sRX) and / or the other sensing transmitter devices (sTX) and / or the first device 10 and / or the second device 20. In the case of wireless sensing (e.g., based on radar or distributed sensing), the (one or more) sensing receiver devices (sRX) will receive the reflected wireless sensing signal 708R and can identify and process the received reflected wireless sensing signal 708R based on the provided wireless sensing configuration information (e.g., as described in the present disclosure). In one example, based on the received reflected wireless sensing signal 708R, when the signal was sent (e.g., as configured in the signal, timestamp information or a portion thereof), its own known location and the location of the sensing transmitter device (sTX) (e.g., a base station), the location or position of the (potential) target object (TO) can be estimated, for example, by using triangulation. In the case of sensing using sensor 10 or sensor 12 of the first device 10, the first device 10 or the second device 20 can send its measurement or segmented data to the RSMF or another device (for example, the second device 20 in the case of the first device 10), and the first device 10 or the second device 20 or the RSMF can calculate mesh data and / or match the data with the viewpoint, sensor heading and / or FoV of the first device 10 or the second device 20, or data stored for different (predefined) viewpoints, sensor headings and / or FoVs (for example, radar cross sections) or synthetic models of matching targets.

[0375] Additionally or alternatively, each sensing receiver or sensing transmitter device (sRX, sTX) or first device 10 or second device 20 will send its wireless sensing signal measurement and / or processing results to a configured destination (e.g., to the RSMF), which collects the results and can perform further processing on these results. This may include matching or object recognition (e.g., using algorithms such as synthetic data algorithm (SDA) 30, segmentation algorithm (SA) 40, matching algorithm (MA) 50), as described in other embodiments of the present disclosure. The RSMF can use all received / collected measurements and / or (partial) sensing results to determine a set of sensing results. This can be based on the sensing requirements received in the location / sensing request (e.g., as received from the application). The sensing results (e.g., the location of the target) can be provided to the entity that issued or forwarded the "extended" location request to the RSMF (e.g., GMLC / AMF / NEF / UE). Alternatively or additionally, the sensing results can be stored in a shared storage device (e.g., a unified data repository (UDR)), from which other entities can retrieve the sensing results based on an identifier provided to the corresponding entity by the RSMF.

[0376] Part of the further processing on the sensing receiver device (sRX) or on the sensing transmitter device (sTX) or the first device 10 or the second device 20 or on the configured destination (e.g., RSMF) may include steps for detecting a set of objects and / or for determining a set of sensing information (i.e., measurements and / or results) of one or more detected objects, for example using an initial scan or sensing operation of a target area or volume performed by the sensing service (i.e., RSMF) and / or the sensing transmitter device (sTX) and / or the sensing receiver device (sRX), as also described in other embodiments, and / or for determining, based on the target identification information set, whether the set of sensing information for one or more detected objects (i.e., measurements and / or results obtained as an output of the sensing operation) meets or does not meet one or more configured criteria (e.g., thresholds) for identifying a target. Based on the latter determination, the sensing receiver device (sRX) and / or the sensing transmitter device (sTX) and / or the first device 10 and / or the second device 20 and / or the configured destination (e.g., RSMF) may:

[0377] stopping or resuming the sensing operation, e.g., by sending a signal or message directly to the sensing transmitter device (sTX) or the first device 10 or the second device 20 at 706 and / or directly to the sensing receiver device (sRX) or the first device 10 or the second device 20 at 707, or indirectly to the sensing receiver device (sRX) or the first device 10 or the second device 20, e.g., via the sensing transmitter device (sTX) at 706 and then from the sensing transmitter device (sTX) to the sensing receiver device (sRX) at 711;

[0378] initiating additional sensing operations, e.g., by sending a signal or message directly to the sensing transmitter device (sTX) or the first device 10 or the second device 20 at 706 and / or directly to the sensing receiver device (sRX) or the first device 10 or the second device 20 at 707, or indirectly to the sensing receiver device (sRX) or the first device 10 or the second device 20, e.g., via the sensing transmitter device (sTX) at 706 and then from the sensing transmitter device (sTX) to the sensing receiver device (sRX) at 711;

[0379] Generate an event or send a signal indicating that a matching target is detected or not detected (wherein, in the case of a partial match, the matching target matches a subset of the target identification information set (with a certain confidence or matching percentage), or in the case of a complete match, the matching target completely matches the target identification information set), for example, by sending a signal or message directly to the RSMF from the sensing transmitter device (sTX) or the first device 10 or the second device 20 via 710 and / or from the sensing receiver device (sRX) or the first device 10 or the second device 20 via 709, or by sending a signal or message from the sensing receiver device (sRX) or the first device 10 or the second device 20 via 712. device (sRX) to a sensing transmitter device (sTX), and then indirectly sending a signal or message from the sensing receiver device (sRX) or the first device 10 or the second device 20 to the RSMF via 710 from the sensing transmitter device (sTX) to the RSMF, or sending a signal or message from the RSMF to the UDM / UDR via 713, or sending a signal or message from the RSMF to the AUSF via 714 (e.g., as part of an authentication and / or authorization process), or sending a signal or message to an application function or AAA server (e.g., via an NEF, not shown) or a non-volatile storage unit; or

[0380] Initiate or continue authorization of a target or target object (TO) for sensing (e.g., to verify whether the detected object is an authorized target for sensing services), for example, by sending a signal or message from the RSMF to the UDM / UDR via 713, or to the AUSF via 714, or to an application function or AAA server (e.g., via the NEF, not shown).

[0381] Thus, the RSMF may retrieve the wireless sensing capabilities of the sensing receiver device (sRX) and / or the sensing transmitter device (sTXs) and / or the first device 10 and / or the second device 20, may configure one or more sensing transmitter devices (sTXs) and / or the sensing receiver device (sRX) and / or the first device 10 and / or the second device 20 to participate in wireless sensing of the target object (TO), may configure the receiver device (sRX) with wireless sensing capabilities and / or the transmitter device (sTXs) with wireless sensing capabilities using information about the network entity or destination server that sent the wireless sensing results. The transmitter device (sTX) and / or the first device 10 and / or the second device 20 may configure the transmitter device (sTX) with wireless sensing capability and / or the receiver device with wireless sensing capability and / or the first device 10 and / or the second device 20 using information about when and how to send and / or receive and / or process wireless sensing signals, and may collect and further process wireless sensing measurements and / or results (i.e., a sensing information set) from the sensing transmitter device (sTX) and / or from the sensing receiver device (sRX) and / or the first device 10 and / or the second device 20.

[0382] Object identification (for virtual reality or mixed reality services)

[0383] A VR or MR service may be a service operated by a third party that can gain access to specific network functions of the wireless network via a service application programming interface (API) (e.g., similar to a network exposure policy). The VR or MR service provider may be the third party operating the VR or MR service, while the user may be an individual actively or passively participating in the VR or MR service. The user ID may be an identifier unique to a given user. It may be a unique identifier of the user's UE, an ID provided by the VR or MR service provider, a local ID assigned by a (serving) base station (e.g., a gNB), the local network, or other means. It may be fixed or temporary. The viewing user may be the user currently viewing another user. It is also assumed that the user's UE's sensors are viewing the other user. The viewed user may be a user being viewed by the viewing user, whose identity is initially unknown to the viewing user and / or their UE. The viewed user's location is understood to be the location of the viewed user. If the viewed user has a UE, this may be functionally equivalent to, for example, the UE's location provided by the LMF 320 or GNSS location data provided by the UE to the wireless network. In the case where the viewed user does not have a UE, this may be based on the data received from the sensor 22 or, for example, from a device carried by the viewing user (in the Figure 3 or Figure 4 The determination is made based on radar data collected by other sensors (represented as the second device 20).

[0384] In a virtual reality or mixed reality (MR) scenario (as initially described), multiple users can use their user devices (e.g., UEs) to interact with both real objects and virtual assets. Virtual assets are rendered by the UEs. Such virtual assets can be associated with a specific user, for example, virtual equipment, virtual pets, etc. When one user enters the view of another user, the virtual assets associated with the viewed user need to be correctly rendered by the viewing user's UE.

[0385] This requires the viewing user's UE to identify the viewed user, i.e., so that the correct virtual assets can be retrieved from the VR provider and presented by the UE. However, the viewing user's UE may initially have no information about the viewed user, other than information it can obtain from local sensors (e.g., video pose data of the viewed user obtained by, for example, the viewing user's UE's camera). This can be further complicated if the viewing user and the viewed user are participating in separate VRs (such that the viewing user's VR service may also initially have no information about the viewed user) or if the viewed user does not have a UE at the time they are viewing (and therefore cannot provide any identifying information).

[0386] To address this issue, the wireless network to which the UE is connected can leverage its sensing capabilities (e.g., a gNB in sensing mode collecting radar data of user gestures) to provide a "viewed user identification service." Here, data from the UE's sensors (e.g., a camera) on the viewed user is used to generate synthetic data, which can then be matched with data collected by the wireless network's sensors on the same viewed user, according to the aforementioned embodiments. Once a match is confirmed, the wireless network can provide the viewed user's UE with an identifier (e.g., a unique user ID) for the viewed user. This identifier can then be used to request digital assets from the virtual reality service provider for rendering. Alternatively, the wireless network can request the digital assets directly, for example from an identity service or subscription service and / or a user / object database operated by the network itself or from a 3D-party application function (e.g., via the Network Exposure Function (NEF)), and provide them to the viewing user's UE. Similarly, other objects (not just users) can be detected. This alternative approach protects the user's privacy because the unique ID does not need to be disclosed. In this example, the actual digital assets provided may depend on the privacy policy of the service linked to the match and the permissions of the viewing user's UE.

[0387] This final step requires that the wireless network have prior access to a list of identifiers (eg, unique user IDs) associated with data collected by the wireless network sensors.

[0388] In the case where the viewed object (e.g., a user) has a UE, the association can be achieved by providing a unique ID to the UE, or by determining the location of the UE (e.g., by the LMF320 of the 5GS), or by determining the location of the viewed object via a wireless network sensor, or by assigning the UE's unique ID or a related ID (e.g., an ID derived from the UE's unique ID) or a location-based or time-based pseudonym to the object co-located with the UE. Any other data collected by the wireless network sensor can then be associated with that ID.

[0389] In the event that the viewed object does not have a UE, the network can assign a temporary ID to all users sensed by the wireless network sensor. If necessary, further steps can be taken to identify these objects. For example, if the viewed object is known to some viewing users but not to others, the viewing user who knows the viewed object may be able to provide an identifier of the viewed object, which can then replace the temporary ID and be sent to the other viewing users. Alternatively, if authentication functionality is available (for example, network sensors are used to obtain biometric data), the network may be able to directly authenticate the viewed object and assign a unique ID to the viewed object.

[0390] like Figure 3 As shown, the wireless system (5GS) may include a core network (5GC) 300, an access network (5G-AN) 200, and mobile stations or terminal devices 100 (e.g., UEs). The LMF 320 in the core network 300 may provide the geographic location of some or all mobile stations 100.

[0391] For example, the sensing function performed by the second device (B) 20 may be implemented or supported via one or more base stations (e.g., gNBs) of the access network 200. Such sensing functions may also be based on raw base station measurement data for identification purposes and may be performed by a network function of the core network 300 or by an external application.

[0392] The execution of some or all of the algorithms described in the above embodiments may be performed by hardware of the base station 220 or mobile station (eg, UE) 100 or a network function of the core network 300 or by an external application or by a combination of some or all of the above entities.

[0393] Figure 3 and Figure 4 The first device (A) 10 may be a UE for MR or AR reality applications. For example, AR glasses or a smart phone. In this use case, the first device 10 is considered to be the UE of the user who is viewing, which may have established a communication link with the wireless network so that the position of the first device 10 can be provided to the system (for example, through the LMF 320 or through the first device 10 itself). The sensor 12 of the first device 10 may be a line of sight sensor, such as a camera or a lidar sensor. The measurement data D MA It may be a brief portion of data recorded by the sensor 12 of the first device 10 (eg, a few hundred frames of video footage) that features (eg, shows, presents) a viewed object with a moving gesture.

[0394] Figure 3 and Figure 4 The second device (B) 20 may be one or more devices that are part of a wireless network, wherein the wireless network may access the sensor 22 of the second device 20 .

[0395] In some embodiments, the second device 20 may be a gNB or a base station that is part of the access network 200. The sensor 22 of the second device 20 may be a radar sensor, which may include at least one of a dedicated radar sensor placed on the gNB, a communication component (e.g., ISAC) used in a dedicated sensing mode, and a passive sensing function derived from normal communication signals.

[0396] In some embodiments, the sensor 22 of the second device 20 may be fully virtualized and provided as part of a network function on the core network 300, where raw measurement data may be provided by many sensors accessible to the network. In such cases, there may not be a single second device 20. The sensor 22 of the second device 20 may have a set of properties including at least one of the following: data type, field of view (FoV) of the sensor, heading of the sensor, and 3D position of the sensor 22 or the second device 20. The sensor 22 may be capable of collecting measurement data D of the second device 20. MB (ie, pose data of the viewed object), but also the position of the viewed object can be determined (ie, distance and angle measurements).

[0397] In an alternative embodiment that may be combined with other embodiments or implemented independently, instead of matching measurement or segmented data from sensor 12 of first device 10 with data (e.g., measurements or virtualizations) from sensor 22 of second device 20, one or more radar cross sections may be generated based on the measurement or segmented data from sensor 12 of first device 10, whereby one or more radar cross sections may be generated for different viewing angles that may correspond to a predefined set of angles (e.g., angles relative to a reference line toward magnetic north) and / or FoVs and / or locations. These generated radar cross sections can be matched (e.g., by a "matching service" or "viewing object identification service" running in the core network) with a set of cross sections (for different view points, sensor headings, and / or FoVs) generated from a model (e.g., a digital twin) of the object and / or a data set for different view points, sensor headings, and / or FoVs (e.g., radar cross sections) and / or a mesh data set of the object stored in an object database, whereby data for a set of view points, sensor headings, and / or FoVs can be generated or stored based on a predefined set of positions (e.g., known positions of base stations) or angles (e.g., angles relative to a reference line oriented toward magnetic north) and / or FoVs (e.g., different focal lengths). Such a model of the object or the stored data set of different view points, sensor headings, and / or FoVs of the object can be associated with an identity (e.g., a UE identity such as a subscription permanent identifier (SUPI)). If a match is found between the data from the sensor 12 of the first device 10 and the model or set of viewpoints of the object, the resulting identity can be provided to entities that use these entities for additional operations (for example, another core network service that uses the identity for authentication and / or authorization, such as AUSF or UDM, or application functionality that uses the identity to obtain virtual reality assets).

[0398] In another alternative embodiment, which may be combined with other embodiments or implemented independently, measurement or segmented data from the sensor 12 of the first device 10 is used (e.g., by a network service such as a sensing service or a “viewing object recognition service” or by sending that data to a second device 20) to determine the distance and / or angle between the first device 10 and an object in the field of view of the sensor 12. The positions of objects in the field of view of the sensor 12 may be determined in combination with the position information of the second device 20 provided by the first device 10 (e.g., provided to the network (e.g., GNSS position data provided to a location management function from which other services (such as sensing or matching services) may obtain position information) or provided by the first device itself, or obtained by triangulation / trilateration of (sensing or location reference) signal measurements by the first device and / or one or more base stations or other devices. To this end, the network service or the second device may receive the position information of the first device 10 and the viewpoint, FoV, and / or heading of the sensor 12, and may obtain position information about one or more objects detected in the area by other means (e.g., based on sensing by the second device 20 or a UE carried by / covered by these objects, whose positions are received or can be determined), and may use the obtained position information as well. The received position information of the first device 10 and its FoV and / or heading is used to calculate the distance / angle between the first device 10 and one or more objects. Based on these calculations, the network service or the second device can determine whether these objects are in a given FoV and / or heading of the first device 10 (i.e., based on the FoV information and / or heading information received from the first device 10 and other information related to the sensor 12 in the first device 10, such as the viewpoint and / or sensing capabilities). In addition, the network service or the second device can use the size information and / or material information and / or other target identification information that it can obtain or retrieve (e.g., from an operational sensing service or from an external application) to determine whether an object will obscure another object and / or whether the object is only partially observable given the viewpoint, heading and / or FoV of the first device 10.The determined positions of the objects may then be matched with positions of objects and / or UEs in the area, e.g., in the vicinity of the first device 10, e.g., UEs registered to the same gNB or within a (preconfigured) maximum distance, and based on the position matching, the respective objects and / or UEs may be identified and the associated identities may be provided to entities that use these entities for additional actions (e.g., sending information about these objects (e.g., position and / or angle / distance from the first device or a reference point, identity information, whether the target object carries / covers the UE, metadata describing the object, the size of the object, whether it may be occluded by another object or only partially observable) to the first device 10, which the first device 10 may use to retrieve data about these objects from a virtual reality service (e.g., for overlaying / rendering data about these objects on a rendering device), or the first device 10 may use it to establish a connection with one or more of these targets (if these targets carry or cover the UE), or the first device 10 may use it to initiate / continue sensing of these objects). The positions of the objects and / or UEs in the area may be obtained in a similar manner as the position information of the first device (e.g., based on GNSS position data, by triangulation / trilateration, etc.).

[0399] For this use case (Virtual Reality or MR), Figures 1 to 7 The deployment algorithm of the above embodiment can be configured as follows:

[0400] The X-to-grid algorithm 32 may comprise, for example, a pre-trained neural network that maps the 3D grid to the measurement data D MB The algorithm is based on the human body pose in the dataset and outputs a time-varying mesh dataset.

[0401] The Grid to Y algorithm 34 may be configured to generate synthetic data D that simulates a radar cross section of a viewing user. S More specifically, guided by the corresponding sensor parameters (attributes) and the position of the viewed user, a viewpoint corresponding to the predicted view of the viewed user can be synthesized by the sensor 22 of the second device 20.

[0402] Additionally or alternatively, a viewpoint (e.g., a radar cross section) can be synthesized based on measurements of the object by the sensor 22 of the second device 20 or based on a model of the object and / or a set of viewpoints of the object and / or a set of grid points of the object that can be stored and retrieved from an object database (e.g., a user database that associates a UE with a model, mesh data, or a set of viewpoints representing a UE device or a user of a UE device or an object carrying / covering the device) to correspond to the predicted view of the user by the sensor 12 of the first device 10.

[0403] Optionally, an additional UE device (e.g., a UE) associated with any viewed object may be provided. This may be relevant if the viewed user has a UE and is participating in a virtual reality or MR service. The additional device may be functionally identical to the first device 10. The location of the additional device may be determined by the LMF 320 or the ISAC service (e.g., based on sensory data from one or more base stations). It is assumed that this location is approximately the same as the location of the viewed user.

[0404] In addition, an additional database may be provided, which stores the segmented measurement data D of the second devices 20 of all viewed users. MBS and its associated user ID.

[0405] Furthermore, an additional algorithm (eg, an ID assignment algorithm) may be provided that assigns user IDs to the segmented measurement data D in the user database. MBS For a viewed object with a UE, this can utilize the position of the additional device and the user position determined by the sensing sensor 22 of the second device 20 to convert a given segmented measurement data D MBS Assigned to a user ID. For a viewed object without a UE, a temporary user ID can be assigned.

[0406] When multiple users interact with the corresponding virtual reality or MR service, for example in a single physical area, the user database may be updated.

[0407] The sensor 22 of the second device 20 collects (continuously) measurement data D MB , and the segmentation algorithm 40 measures the data D MB Run on to cluster the measured time-varying reflectance and output the segmented measurement data D MBS , where each segment thus indicates the body movement of an individual subject. This data can be stored in a user database.

[0408] For the segmented measurement data D MBS For each identified object in the user database, the sensor 22 of the second device 20 is used to obtain range and angle measurements of the object and thus also output the object position of each object. This is also stored in the user database.

[0409] Then, the ID assignment algorithm can assign user IDs to all segmented measurement data D in the user database MBS This may be followed by the following steps: providing the locations of all first and additional devices in the area by the LMF 320, comparing the user location with the device location via an ID assignment algorithm, requesting a user ID for similar device locations within an acceptable error level, assigning the user ID to the segmented measurement data D MBSFor user locations that do not have corresponding device locations (i.e., the user does not have a UE), a temporary user ID can be generated and assigned to the associated segment measurement data D MBS And stored in the user database.

[0410] An object (e.g., a user) can be identified as follows:

[0411] When a (new) object enters the field of view of another user, the viewed object is initially unknown to the viewing user's first device 10. The sensor 12 of the first device 10 records measurement data D of the viewed object. MA and sends it to the synthetic data algorithm 30, which can be provided, for example, locally in the first device 10 or in an edge server or in the second device 20 or in the core network 300, etc.

[0412] The following process may be deployed by the synthetic data algorithm 30:

[0413] X to grid algorithm 32 based on measurement data D MA Generate time-varying mesh data of the viewed object.

[0414] The Grid to Y algorithm 34 uses the grid data to generate synthetic data D of the same data type for the sensor 22 of the second device 20. S , which simulates the measurement of the viewed object from the perspective of the sensor 22 of the second device 20. In the case where the sensor 22 of the second device 20 is of radar data type, synthetic data D is generated that simulates the measurement of the radar cross section of the viewed object. S The process of the algorithm 34 method may include generating a synthetic viewpoint at a position, angle, and FoV relative to the mesh data in the virtual scene such that it reflects the position, heading, and FoV of the sensor 22 of the second device 20 relative to the object position of the viewed object in the real world.

[0415] As previously described, synthetic datasets for viewpoints, sensor headings, and / or FoVs (e.g., synthetically generated radar cross sections) may be generated from data from the sensors 12 of the first device 10 for different viewing angles, positions, and / or FoVs that may correspond to predefined angles, positions, and / or FoVs. The synthetic datasets of viewpoints, sensor headings, and / or FoVs may be such that one or more of these datasets can be matched with synthetic datasets of viewpoints, sensor headings, and / or FoVs generated from a model of an object, a dataset of sensor headings and / or FoVs for an object, and / or a mesh dataset of an object stored in an object database, whereby data for the datasets of viewpoints, sensor headings, and / or FoVs may be generated or stored according to a predefined set of positions (e.g., the positions of one or more gNBs), angles (e.g., one or more angles relative to a reference line oriented toward magnetic north), or FoVs (e.g., from a narrow focus to a wide angle view).

[0416] Given a synthetic viewpoint and mesh data of a viewed object, a radar cross section can be calculated for each vertex of the mesh data for a virtual radar sensor at the location of the virtual viewpoint, whereby the virtual radar sensor can have a (predetermined) sensor heading and / or FoV. This can be done by calculating the radial velocity of each vertex of the mesh data relative to the sensor at the synthetic viewpoint. Vertices of the mesh data that are occluded by other objects (e.g., body parts) relative to the synthetic viewpoint or are outside the FoV (given the (predetermined) sensor heading and / or FoV of the virtual radar sensor) are filtered out so that they contribute to the final radar synthetic data D. S No contribution. An initial rough synthetic radial velocity distribution can then be generated from the radial velocities of the remaining vertices. The pre-trained encoder-decoder model can then be run on the initial radial velocity distribution to generate the final radar synthetic data D S The encoder-decoder model can be pre-trained on corresponding pairs of real-world and synthetic radar data.

[0417] Figure 4 The matching algorithm 50 can be run through the segmented measurement data D MBS The latest instance of , and the real Doppler radar measurements in each segment can be compared with the generated synthetic data D S A comparison is performed to identify a match. The actual Doppler radar measurements can be measured in real time or stored in a database, such as one containing user-related information for user identification / authentication. A positive match result can be output when the virtual Doppler radar dataset and the actual Doppler radar dataset have a similarity exceeding a predetermined numerical threshold. A match confidence level can be calculated, for example, based on the average magnitude of the differences between the datasets.

[0418] In the event of a positive match result, the user ID associated with the matching segment may be returned to the first device 10, which may now identify the user via the user ID and use the user ID to request additional data (such as instructions for rendering the digital asset) from the virtual reality or MR service provider.

[0419] Alternatively, the second device 20 (or another entity in the wireless network) may retrieve the additional data from the virtual reality or MR service provider on behalf of the first device 10 and may provide the additional data to the first device 10.

[0420] As an optional measure, an ID may be assigned to a user who does not have a device. This may be achieved by watching the user or by a pre-registered identification. In the first case, where a temporary user ID has been assigned to an unknown user, the corresponding user position of the unknown user may be sent to a nearby device with a request for a real user ID. The real user ID of the unknown user may be provided to the ID assignment algorithm, which may then update the user database with the real user ID, either by direct user input or by an automatic service provided by the virtual reality or MR service provider (e.g. a facial recognition algorithm). In the latter case of pre-registered identities, the wireless network may in some cases have access to a database of existing data that may be used as a biometric identifier for a particular user, such as millimeter wave radar cross section data, gait data or a set of (other) matching criteria for a given unknown user, and the associated real user ID. In this case, the segmented measurement data D of the second device 20 may be used to identify the user. MBS A comparison is made with the data in this database to match the unknown user with the biometric data and thus assign a real user ID.

[0421] In another embodiment, which may be combined with any other embodiment or implemented independently, the first device 10 may be able to determine the FoV and / or heading (e.g., based on user input or by a gyroscope or other directional sensor or by using ranging / sidelink positioning (which may include calculating or receiving information about distances / angles to nearby objects carrying / covering the UE), where one or more objects are known / determined / expected / assumed to be therein. The first device 10 may transmit information about the FoV and / or heading to the second device 20 or a "viewing object identification service" or other sensing service. Based on the location information of the first device 10 (e.g., provided by the first device itself to the network or to the GNS of the second device 20), the first device 10 may transmit information about the FoV and / or heading to the second device 20 or a "viewing object identification service" or other sensing service. S position data or a position obtained by triangulation / trilateration of (sensing or position reference) signals measured by the first device and / or one or more base stations or other devices) and position information about one or more objects detected in the area (e.g., within a (preconfigured) maximum distance from the first device 10) (e.g., based on sensing by the second device 20, or by a UE carried / covered by such objects whose positions are received or can be determined), the distance / angle between the position of the first device 10 and the set of objects can be calculated, and if these objects will be in a given FoV and / or heading (i.e., based on the FoV information and / or heading information (and possibly with sensors 10 that the device may optionally have)). 2 related information, such as viewpoint and / or sensing capabilities), as received from the first device 10), these objects may be determined based on these calculations (e.g., by a "viewing object identification service"). In addition, it may use size information and / or material information and / or other target identification information that it can obtain or retrieve (e.g., from an operational sensing service or from an external application) to determine whether an object may be occluding another object and / or whether an object may be only partially observable given the viewpoint, heading and / or FoV of the first device (e.g., by performing ray tracing). Based on the results of these calculations, the corresponding objects and / or UEs in a given FoV may be identified and the relevant identities may be provided to the An entity that uses these entities to perform additional actions (e.g., sends information about these objects (such as position and / or angle / distance from the first device or a reference point, identity information, whether the target object carries / covers the UE, metadata describing the object, the size of the object, whether it may be obscured by another object or only partially observable) to the first device 10, which may use this to retrieve data about these objects to a virtual reality service (e.g., for overlaying / rendering data about these objects on a rendering device), or may use the collection to establish a connection with one or more of these targets (if these targets carry or cover the UE), or may use this to initiate / continue sensing of these objects).The locations of objects and / or UEs in the area may be obtained in a similar manner as the location information of the first device (eg, based on GNSS location data, through triangulation / trilateration, etc.).

[0422] In other words, a first device may be adapted to communicate in a wireless network and may be adapted to determine information about its position and FoV and / or heading, and may send information about its position and FoV and / or heading to a service or a second device in the wireless network, the service or the second device being adapted to receive the information from the first device and further adapted to: obtain position information and / or target identification information about one or more objects detected in proximity and / or within a maximum distance from the first device; and calculate whether the object is in the FoV and / or heading of the first device based on the information received from the first device and the obtained position information and / or target identification information about the one or more objects. The first device may be adapted to receive information about a set of objects in a given FoV and / or heading (i.e., as sent by the first device to the service or the second device in the wireless network), and may further be adapted to obtain additional information about the objects or establish a connection to the objects based on the received information.

[0423] This may be useful for deployments where the first device may have limited or no sensing capabilities to sense nearby objects, or may be deployed in systems / configurations that do not utilize sensing capabilities to sense nearby objects.

[0424] Service Continuity

[0425] In the following, use cases related to service continuity are described where a given UE or other terminal device (or an object associated with the given UE or other terminal device (e.g., a person)) spans or moves between cells of two different base stations (e.g., gNBs) of a cellular network, and service continuity of sensing functions between the cells can be ensured by enabling easy identification that the object leaving the first cell is the same (matches) as the object now entering the second cell.

[0426] This can also be used for general tracking of specific objects or UEs by cell, for example, to track a specific drone or car of interest as it moves through an area.

[0427] In this use case, Figure 3 The first device (A) 10 and the second device (B) 20 may both be base stations (e.g., gNBs). The sensor 12 of the first device 10 and the sensor 22 of the second device 20 may be radar sensors, which may include at least one of a dedicated radar sensor placed on a base station, a communication component (e.g., ISAC) used in a dedicated sensing mode, and a passive sensing option derived from normal communication signals.

[0428] In addition, an additional device may be provided, which may be any terminal device (e.g., UE), such as a smartphone, wearable device, vehicle, drone, etc. The additional device may have an assigned unique identifier (device ID), which may be a UE-related ID or a unique identifier assigned by the wireless system (e.g., access network 200). At any given moment, the additional device has an associated location (device location) and a re-encodeable radar cross section (device cross section). In the case where the additional device is a handheld or wearable device (such as a smartphone), its cross section may be the radar cross section of the device itself and / or the user carrying the device.

[0429] The measurement data D collected at the first device 10 AM and the measurement data D collected at the second device 20 MB Both can be measurements of the device cross-section of the attached device and / or its user.

[0430] In this use case, the input data and output data of the synthetic data algorithm 30 may be of the same data type, such as Doppler radar measurements. Here, the synthetic data algorithm may be configured to use the measurement data D of the first device 10 MA to perform a view synthesis operation to generate synthesized data D representing a device cross-section of the additional device and / or its user from the perspective of the second device 20 S .

[0431] Furthermore, an additional database (device database) may be provided for storing device IDs and device locations of additional devices that pass through the sensing range of the first device 10 .

[0432] Furthermore, an additional algorithm (switching algorithm) may be provided, which may be configured to trigger the measurement data D of the first device 10. MA Collection and synthesis of data D S Generation.

[0433] In the following, an exemplary procedure for such a use case is described.

[0434] When an additional device is detected in the cell of the first device 10 but is about to leave the cell, the handover algorithm triggers the sensor 12 of the first device 10 to complete a Doppler radar measurement of the additional device, measuring the device cross section.

[0435] Then, the synthetic data algorithm 30 is implemented by first using the measured data D MA Generate a point cloud or other 3D data representing the attached device to generate synthetic data D SThe technique for achieving this can rely on a pre-trained deep learning network to construct point cloud data. The generated point cloud data is then used to generate a synthetic device cross section from the perspective (viewpoint) of the sensor 22 of the second device 20. This can be achieved by using the 3D data to reconstruct the radar cross section of the object from a specific viewpoint, sensor heading and / or FoV. This constructed cross section is used as the synthetic data D S output and may be transmitted from the first device 10 to the second device 20 or from an entity operating the synthetic data algorithm (eg in a radio access network or core network) together with the associated device ID before the additional device leaves the cell of the first device 10 .

[0436] When receiving the synthetic data D S or independent of synthetic data D S Before or before, the second device 20 collects measurement data D via its sensor 22 MB The sensor 22 images the device cross section of the attached device. The measurement data D MB and synthetic data D S can be passed to the matching algorithm 50, which converts the measured data D MB With the generated synthetic data D S The comparison is performed to output a positive or negative match result. A positive match result can be output when the virtual Doppler radar dataset and the real Doppler radar dataset have a similarity that exceeds a numerical threshold. In addition, a match confidence level can be calculated based on the average size of the differences between the datasets. In the case of a positive match result, the second device 20 can (immediately) associate the additional device with its device ID and can inherit any settings or other data related to the additional device from the first device 10.

[0437] A similar use case can be enabled for inter-cell tracking. In this case, non-communicating objects (such as vehicles, people without devices, any drones not connected to the network, etc.) can be tracked as they travel between cells of a cellular network.

[0438] When in the initial cell, such non-communication objects can be sensed and a device ID can be generated for them and stored in the database. Synthetic data D of non-communication objects can be generated for surrounding base stations (e.g., gNBs) S , so that they can effectively identify it once it enters its cell. This can then be repeated when the non-communicating object leaves that cell for the next cell, and so on. In this way, a non-communicating object can be tracked as it travels through the cells of a cellular network without having to communicate with the cellular network at all.

[0439] Note that the above use case process can also be modified to apply the combination of Figure 4 and Figure 5 The matching process of the third and fourth embodiments described above, wherein the two measurement data D of the first device 10 and the second device 20 are MA 、D MB are converted into synthetic datasets and then compared by a matching algorithm 50 .

[0440] The following figures and examples provide additional details on how these mechanisms are used to achieve service continuity.

[0441] Figure 13 The figure schematically shows the architecture of a wireless network with an overlapping sensing structure in which the present invention can be implemented.

[0442] As described above, wireless sensing may require a single wireless device to be able to sense a target when the target is within the sensing range of the single wireless device, and may require components that allow multiple wireless access devices to work together to sense targets in a region of interest (ROI), such as a city or building. Figure 5 Shown, Figure 5 An ROI in the form of a hexagon 024 is shown. The ROI can be defined as the location or area or volume in which a target is to be sensed / detected (i.e., the target location or area or volume or FoV) or the location or area or volume in which sensing is performed (i.e., the sensing location or area or volume or FoV) can be defined as a region of interest (ROI). The target 021 can move anywhere within the ROI. Multiple wireless sensing devices with overlapping sensing areas are used to sense / track / monitor the target, each of which has a sensing area smaller than the ROI. For example, wireless sensing device 022 has sensing area 023. Similarly, device 10 with sensor 12 or device 20 with sensor 22 can have a specific FoV smaller than the ROI.

[0443] Figure 14 The sensing mobility procedure is schematically indicated. This sensing mobility procedure may be required in use cases where the sensing infrastructure is distributed, e.g. Figure 14 The present invention is implemented with multiple sensing devices (e.g., 0401 and 0402) in the embodiment, each device having a given sensing range or area. The sensing devices 0401 and 0402 may correspond to a first device 10 having a sensor 12 and a second device 20 having a sensor 22 as described in the previous embodiment, each having a different FoV.

[0444] In the case of the first device 10, the first sensing device 0401 may include a first sensing receiver S_Rx1 and a first sensing transmitter S_Tx1 or a different sensing modality, such as the sensor 12, as described in the previous embodiment. In the case of the first device 10, the second sensing device 0402 may include a second sensing receiver S_Rx2 and a second sensing transmitter S_Tx2 or a different sensing modality, such as the sensor 12, as described in the previous embodiment. The sensing infrastructure covers the entire area (ROI), which is typically larger than Figure 13 The sensing area of a single sensing device is shown. Sensing devices 0401 and 0402 need to coordinate to sense targets moving through the entire sensing area. For example, such a sensing infrastructure can be based on a base station responsible for tracking and sensing vehicles, UAVs, people, etc.

[0445] exist Figure 14 , a first sensing device 0401 and a second sensing device 0402 collaborate to track a target 0400 moving from a first target location 0403 toward a second target location 0404. During this mobility, the first sensing device 0401 and the second sensing device 0402 have a limited sensing range or FoV and desire to maintain tracking of the moving target 0400 (e.g., a car, a UAV, a person, etc.). The first sensing device 0401 and the second sensing device 0402 may use a variety of sensing technologies as described above. For example, the first sensing device 0401 may transmit a sensing signal 0405 at the first target location 0403 toward the target 0400 and receive a message / signal 0406 that may be, for example, (i) a set of CSI measurements collected by the target 0400 at the first location 0403 and / or (ii) a reflected component of the (radar) sensing signal 0405. In either case, message / signal 0406 allows first sensing device 0401 to determine certain aspects of target 0400 at first location 0403 (e.g., position, velocity, acceleration, beam alignment, heart rate, etc.). Similarly, if first sensing device 0401 uses other sensing modalities, first sensing device 0401 can determine that target 0400 is moving away from its sensing area by monitoring certain aspects (e.g., signal strength, frequency shift, or measurements performed by the target and contained in received signal 0406). If this event occurs, first sensing device 0401 notifies second sensing device 0702 of the proximity to target 0400. In fact, the first sensing device can look up which sensing devices in a list of neighboring sensing devices are most likely to be the sensing devices closest to target (device) 0400 and initiate a handover based on this.

[0446] The first sensing device 0401 can be based on, for example, the following Figure 15The second process described in the context of , or a predetermined map of sensing devices, or based on other embodiments in the present application, determines which sensing device to notify. The first sensing device 0401 then notifies the second sensing device 0402 (e.g., a base station) of the identity of the target 0400 and / or its current location (e.g., first location 0403) and / or other parameters related to the target (e.g., the monitoring status of the target) by sending a message 0407 to the second sensing device 0402 (e.g., a base station) (e.g., via a communication interface (e.g., an Xn interface)) and / or a data set of measurements or segmentation from the sensor 12 or calculations for the viewpoint, sensor heading, and / or FoV (e.g., radar cross section) or the resulting information about the detected object or FoV information (as well as other information that may be related to the sensor 12, such as viewpoint and / or sensing heading and / or sensing capabilities). Note that the second sensing device 0402 may also be a UE, and in this case, the message may be, for example, an RRC message exchanged via a Uu interface. Note that the first sensing device and the second sensing device may also be UEs, and in this case, messages may be exchanged via a PC5 interface. For example, if the sensing device knows the location, sensing area, or Field of View (FoV) of surrounding sensing devices, first sensing device 0401 can know which sensing device to notify. Note that first sensing device 0401 can also notify other sensing devices, for example, proactively or based on a policy. Upon receiving message 0407, second sensing device 0402 can initiate sensing of the target. For example, it can continue to transmit sensing signal(s) 0409. Second sensing device 0402 can also monitor whether it detects sensing signal 0408 from first sensing device 0401 reflected from target 0400 at location 0403. If first sensing device 0401 uses a specific sensing signal (e.g., including an identifier that identifies the sensing signal or using any signal that is identifiable at least within the area, such as using a very specific radar signal, such as a very specific chirp timing / frequency), second sensing device 0402 can discern whether signal 0408 is from target 0400. This identity of the sensing signal (and / or signal characteristics of the sensing signal and / or other information related to sensing, such as sensing measurements received so far, sensing results, predicted / estimated trajectory / speed / direction of the intended target, target application ID / URL, identity of the core network function involved (e.g., sensing service), identity or location of the first sensing device, information about surrounding sensor / receiver devices that may participate in the measurement (e.g., their locations), synchronization information, a set of target identification information from the first sensing device 0401 (e.g., matching criteria for the target) or a sensing session identifier) can be transmitted to the second sensing device 0402 in message 0407.The second sensing device 0402 may also use the measured or segmented data from the sensor 12 or a calculated dataset for viewpoint, sensor heading and / or FoV (e.g., radar cross section) or information about detected objects or FoV information received from the first sensing device 0401 (and possibly other information related to the sensor 12, such as the resulting viewpoint and / or sensor heading and / or sensing capabilities) to match the sensing output of its sensor 22 with the received information, possibly compensating for different FoVs, as described in other embodiments of the present disclosure. Note that the location of the target and the location of the first sensing device can be specified as an absolute location (e.g., geographic coordinates) or a relative location (e.g., distance / angle from a receiver or other reference device or reference coordinates) or as an area / volume (e.g., an area / volume in which the target is expected to reside or in which it appears to have small fluctuations, e.g., due to measurement errors or signal variations), possibly formatted as a collection of Generalized Geographic Area Description (GAD) shapes (as specified in 3GPP TS 23.032). Upon receiving signal 0408, second sensing device 0402 may initiate sensing of the target. For example, it may begin transmitting its own sensing signal 0409, which may also be identifiable, for example, by having an embedded identifier or any other means. Second sensing device 0402 may then receive signal 0410 (e.g., a reflected component of sensing signal 0409 or any other information), which allows second sensing device 0402 to sense / monitor / track target 0400. Second sensing device 0402 may use the information (i.e., parameters) about the target it has received (from first sensing device 0401) (e.g., the latest value of the monitoring status of target 0400, or a set of target identification information) to identify target 0400 in its sensing data and / or verify whether the detected object matches target 0400 (e.g., by verifying whether the sensing result corresponds to the received information about the target within a (pre-)configured error tolerance). The second sensing device 0402 may also use measured or segmented data from the sensor 12 or a calculated data set (e.g., radar cross section) for viewpoint, sensor heading, and / or FoV, or derived information about detected objects or FoV information received from the first sensing device 0401 (and possibly other information related to the sensor 12, such as viewpoint and / or sensing heading and / or sensing capabilities) to match the sensing output of its sensor 22 with the received information, possibly compensating for different FoVs, as described in other embodiments of the present disclosure.Because the sensing measurement of target 0400 by second sensing device 0402 can be initiated after a specific delay, first sensing device 0401 can include a timestamp in the message or in information within the message regarding target 0400 (e.g., the absolute or relative time at which the value of the monitored state was determined before being sent to second sensing device 0402). Second sensing device 0402 can calculate the delay between such a timestamp (or, if no timestamp is included, the time it received the message) and the time it initiated sensing of target 0400 or the time it calculated (or had calculated) the first sensing result regarding target 0400. This delay can be used to compensate for shifts / discrepancies that may have occurred during the sensing of target 0400. For example, if the target is moving in a specific direction at a specific speed, the position of target 0400 determined by second sensing device 0402 can be expected to shift. Second sensing device 0402 can use the time delay to estimate / predict (e.g., by extrapolating) the new position of the target or the value of the monitored state of the target, and can use the information about target 0400 received from first sensing device 0401 to utilize the expected difference in position or state when identifying, matching, or verifying target 0400. Alternatively or additionally, the time delay can be used to estimate / predict the new position of target 0400 and use this new position to beamform target 0400 or to sense target 0400 (e.g., to change the Field of View (FoV) or other parameters of sensor 12 or sensor 22). At this point, second sensing device 0402 can communicate to first sensing device 0701 via message 0412 that it has sensed target 0400, e.g., at second target location 0404. This message can include the identity of sensing signal 0409 used by second sensing device 0402 and information regarding sensing quality. Sensing quality can refer to, for example, position accuracy, velocity accuracy, target frequency (e.g., breathing or heart rate in the case of a person), signal strength of the received signal, etc. At this point, first sensing device 0401 may measure sensing signal 0411 from second sensing device (e.g., the component of sensing signal 0409 reflected by target 0400 at second location 0404, or a set of measurement values transmitted by target 0400 to 0401 on signal 0409). First sensing device 0401 may release tracking of target 0400 and notify second sensing device 042 via message 0413 that it is stopping tracking. Alternatively, first sensing device...

Claims

1. A device for processing data from at least one first sensor (12), the at least one first sensor (12) being characterized by at least one sensing parameter, the at least one sensing parameter being specifically at least one of a point or a direction or a field of view and a sensor type, wherein The apparatus is configured to: Obtain first measurement data (D) of a target object (60) MA ); receiving second measurement data (D) associated with the target object (60) from a second sensor (22) MB ); Based on the at least one sensing parameter of the first sensor (12) and / or the second measurement data (D MB ) related to at least one sensing parameter, obtaining the second measurement data (D MB ) and / or the first measurement data (D MA ) of synthetic data (D S ), and the second measurement data (D MB ) is specifically at least one of a point, a direction, a field of view, and a sensor type, and Based on the synthetic data obtained (D S ) to determine the first measurement data (D MA ) and the second measurement data (D MB ) to see if there is a match between them.

2. The device according to claim 1, wherein With the second measurement data (D MB ) is at least one sensing parameter of the second sensor (22), and wherein the apparatus is configured to obtain the at least one sensing parameter of the second sensor (22) from another device.

3. The device according to claim 1, wherein: The apparatus is further configured to: Determine the first measurement data (D MA ) of the obtained synthetic data (D S ) and the second measurement data (D MB ) of the obtained synthetic data (D S ) ; or Determine the first measurement data (D MA ) and the second measurement data (D MB ) of the obtained synthetic data (D S ) ; or Determine the second measurement data (D MB ) and the first measurement data (D MA ) of the obtained synthetic data (D S ) to see if there is a match between them.

4. The device according to any one of claims 1 to 3, wherein The apparatus is configured to determine whether a match exists by using at least one of: - for converting the first measurement data (D MA ) and the second measurement data (D MB ) is divided into first object related data (D MAS ) and the second object related data (D MBS )'s first algorithm (40), - for collecting the first object related data (D MAS ) or the second object related data (D MBS ) or one of the previous inputs generates the synthetic data (D S )’s second algorithm (30), - for transmitting the first object-related data (D MAS ) or the second object related data (D MBS ) or one of the previous inputs is converted into a first intermediate form (D MAM ) or the second intermediate form (D MBM ) of the third algorithm (32), the first intermediate form (D MAM ) or the second intermediate form (D MBM ) specifically represents the first object related data (D MAS ) and the second object related data (D MBS ) describes a multidimensional representation of the object, - for converting the first intermediate form or the second intermediate form or one of the previous inputs into the synthesized data (D S ), and - for aligning the first intermediate form (D MAML ) and the second intermediate form (D MBML )'s fifth algorithm (76).

5. The device according to any one of the preceding claims, wherein The device is configured to obtain synthetic data (D S ) and the first measurement data (D MA ) to determine the identity of the target object (60).

6. A device according to any one of the preceding claims, wherein The device is configured to retrieve the first measurement data (D MA ) and / or the second measurement data (D MB ).

7. A device according to any one of the preceding claims, wherein The apparatus is configured to retrieve additional data related to the target object (60) from a virtual reality or mixed reality service provider and provide the additional data to the second sensor (22).

8. The device according to any one of claims 1 to 6, wherein: The apparatus is configured to perform asset tracking of the target object (60).

9. The device according to any one of claims 1 to 6, wherein: The apparatus is configured to request the target object (60) to accept network-assisted identification.

10. The device according to any one of claims 1 to 6, wherein The apparatus is configured to authorize the target object (60) if a match is determined.

11. The device according to any one of claims 1 to 6, wherein The apparatus is configured to provide support for service continuity, in particular when the target object (60) moves out of the coverage area of the second sensor (22).

12. A terminal device (10) comprising the apparatus according to any one of claims 1 to 6, 8 and 9.

13. An access device (10) comprising the apparatus according to any one of claims 1 to 11.

14. A wireless communication system comprising at least one of the terminal device (10) according to claim 12 and the access device (10) according to claim 13.

15. A method for matching a target object in a wireless network, the method comprising: obtain (S310; S510) First measurement data (D) of the target object (60) MA ); Second measurement data (D) related to the target object (60) is received (S320; S520) from a second sensor (22). MB ); Based on at least one sensing parameter of the first sensor (12) and / or the second measurement data (D MB ) related to at least one sensing parameter, obtaining (S340; S550) from the second measurement data (D MB ) and / or the first measurement data (D MA ) of synthetic data (D S ;D MAML , D MBML ), and the second measurement data (D MB ) is specifically at least one of a point, a direction, a field of view, and a sensor type, and Based on the synthetic data obtained (D S ;D MAML , D MBML ) to determine (S350; S560) the first measurement data (D MA ) and the second measurement data (D MB ) to see if there is a match between them.

16. A computer program product comprising code means for producing the steps of claim 15 when run on a processor of a network device (10).

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