Methods, architectures, apparatuses and systems for performing sensing tasks

Abstract

Procedures, methods, architectures, apparatuses, systems, devices, and computer program products for performing a sensing task are described. A wireless transmit / receive unit, WTRU, receives, from a network, information indicative of a sensing task, obtains sensing related measurements according to the information indicative of the sensing task, determines, based on the sensing related measurements, at least one estimated metric, determines, based on the at least one estimated metric, whether an accuracy for the sensing task has been achieved, and transmits, to the network, information indicative of whether or not the accuracy for the sensing task has been achieved.

Description

METHODS, ARCHITECTURES, APPARATUSES AND SYSTEMS FOR PERFORMING SENSING TASKSCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of European Patent Application 24151943.8, filed 15 January 2024, which is incorporated herein by reference in its entirety.BACKGROUND

[0002] The present disclosure is generally directed to the fields of communications, software and encoding, including, for example, to methods, architectures, apparatuses, systems directed to performing sensing tasks.SUMMARY

[0003] In a first aspect, the present principles are directed to a method at a wireless transfer / receive unit, WTRU, the method including receiving, from a network, information indicative of a sensing task, obtaining sensing related measurements according to the information indicative of the sensing task, determining, based on the sensing related measurements, at least one estimated metric, determining, based on the at least one estimated metric, whether an accuracy for the sensing task has been achieved, and transmitting, to the network, information indicative of whether or not the accuracy for the sensing task has been achieved.

[0004] In a second aspect, the present principles are directed to a wireless transfer / receive unit, WTRU, configured to receive, from a network, information indicative of a sensing task, obtain sensing related measurements according to the information indicative of the sensing task, determine, based on the sensing related measurements, at least one estimated metric, determine, based on the at least one estimated metric, whether an accuracy for the sensing task has been achieved, and transmit, to the network, information indicative of whether or not the accuracy for the sensing task has been achieved.

[0005] In a third aspect, the present principles are directed to a method at a wireless transfer / receive unit, WTRU, the method including receiving, from a network, information indicative of a sensing task and information indicative of at least one trigger condition for reporting, obtaining sensing related measurements according to the information indicative of the sensing task, determining, based on the sensing related measurements, at least one estimated metric, determining respective contributions of the at least one estimated metric to an accuracy of the sensing task, and in case at least one trigger condition is met by a contribution, transmitting, to the network, information indicative of the at least one estimated metric.

[0006] In a fourth aspect, the present principles are directed to a wireless transfer / receive unit, WTRU, configured to receive, from a network, information indicative of a sensing task andinformation indicative of at least one trigger condition for reporting, obtain sensing related measurements according to the information indicative of the sensing task, determine, based on the sensing related measurements, at least one estimated metric, determine respective contributions of the at least one estimated metric to an accuracy of the sensing task, and in case at least one trigger condition is met by a contribution, transmit, to the network, information indicative of the at least one estimated metric.

[0007] In a fifth aspect, the present principles are directed to a method at a wireless transfer / receive unit, WTRU, the method including receiving, from a network, information indicative of a sensing task, obtaining sensing related measurements according to the information indicative of the sensing task, determining, based on the sensing related measurements, at least one estimated metric, executing a plurality of functions, each function taking as input the at least one estimated metric, determining the function among the plurality of functions that best fulfils a set of evaluation criteria, and transmitting, to the network, information indicative of the determined function.

[0008] In a sixth aspect, the present principles are directed to a wireless transfer / receive unit, WTRU, configured to receive, from a network, information indicative of a sensing task, obtain sensing related measurements according to the information indicative of the sensing task, determine, based on the sensing related measurements, at least one estimated metric, execute a plurality of functions, each function taking as input the at least one estimated metric, determine the function among the plurality of functions that best fulfils a set of evaluation criteria, and transmit, to the network, information indicative of the determined function.

[0009] In a seventh aspect, the present principles are directed to a method at a wireless transfer / receive unit, WTRU, the method including receiving, from a network, information indicative of a sensing task, obtaining sensing related measurements according to the information indicative of the sensing task, determining, based on the sensing related measurements, at least one estimated metric, determining a first function among a plurality of functions that best fits at least a subset of the measurements according to a first set of evaluation criteria, determining a second function among a plurality of functions that best fits signal-to-noise ratios of at least a subset of the measurements according to a second set of evaluation criteria, and transmitting, to the network, information indicative of the first determined function and the second determined function.

[0010] In an eighth aspect, the present principles are directed to a wireless transfer / receive unit, WTRU, configured to receive, from a network, information indicative of a sensing task, obtain sensing related measurements according to the information indicative of the sensing task,determine, based on the sensing related measurements, at least one estimated metric, determine a first function among a plurality of functions that best fits at least a subset of the measurements according to a first set of evaluation criteria, determine a second function among a plurality of functions that best fits signal-to-noise ratios of at least a subset of the measurements according to a second set of evaluation criteria, and transmit, to the network, information indicative of the first determined function and the second determined function.

[0011] In a ninth aspect, the present principles are directed to a method at a wireless transfer / receive unit, WTRU, the method including receiving, from a network, information indicative of a sensing task and information indicative of at least one trigger condition for reporting, obtaining sensing related measurements according to the information indicative of the sensing task, determining, based on the sensing related measurements, at least one estimated metric, determining whether an accuracy of the at least one estimated metric is not met, determining whether the at least one estimated metric meets the at least one trigger condition for reporting, and, in case at least one accuracy is not met and / or the at least one estimated metric meets the at least one trigger condition for reporting, determining, based on at least one communication requirement and at least one sensing task accuracy requirement, a configuration for the sensing task, and transmitting, to the network, information indicative of the determined configuration.

[0012] In a tenth aspect, the present principles are directed to a wireless transfer / receive unit, WTRU, configured to receive, from a network, information indicative of a sensing task and information indicative of at least one trigger condition for reporting, obtain sensing related measurements according to the information indicative of the sensing task, determine, based on the sensing related measurements, at least one estimated metric, determine whether an accuracy of the at least one estimated metric is not met, determine whether the at least one estimated metric meets the at least one trigger condition for reporting, and, in case at least one accuracy is not met and / or the at least one estimated metric meets the at least one trigger condition for reporting, determine, based on at least one communication requirement and at least one sensing task accuracy requirement, a configuration for the sensing task, and transmit, to the network, information indicative of the determined configuration.

[0013] In an eleventh aspect, the present principles are directed to a method at a wireless transfer / receive unit, WTRU, the method including receiving, from a network, information indicative of a sensing task, obtaining sensing related measurements according to the information indicative of the sensing task, determining, based on the sensing related measurements, at least one estimated metric, determining whether samples of the measurements meet at least one qualitycriterion, predicting, based on whether samples of the measurements meet the at least one quality criterion, a future time window during which samples of the measurements do not meet the at least one quality criterion, estimating whether the sensing task cannot be performed with required accuracy during the future time window, and upon estimating that the sensing task cannot be performed with required accuracy during the future time window, transmitting, to the network, information indicative of the future time window.

[0014] In a twelfth aspect, the present principles are directed to a wireless transfer / receive unit, WTRU, configured to receive, from a network, information indicative of a sensing task, obtain sensing related measurements according to the information indicative of the sensing task, determine, based on the sensing related measurements, at least one estimated metric, determine whether samples of the measurements meet at least one quality criterion, predict, based on whether samples of the measurements meet the at least one quality criterion, a future time window during which samples of the measurements do not meet the at least one quality criterion, estimate whether the sensing task cannot be performed with required accuracy during the future time window, and upon estimating that the sensing task cannot be performed with required accuracy during the future time window, transmit, to the network, information indicative of the future time window.BRIEF DESCRIPTION OF THE DRAWINGS

[0015] A more detailed understanding may be had from the detailed description below, given by way of example in conjunction with drawings appended hereto. Figures in such drawings, like the detailed description, are examples. As such, the Figures (FIGs.) and the detailed description are not to be considered limiting, and other equally effective examples are possible and likely. Furthermore, like reference numerals ("ref.") in the FIGs. indicate like elements, and wherein:

[0016] FIG. 1 A is a system diagram illustrating an example communications system;

[0017] FIG. IB is a system diagram illustrating an example wireless transmit / receive unit (WTRU) that may be used within the communications system illustrated in FIG. 1 A;

[0018] FIG. 1C is a system diagram illustrating an example radio access network (RAN) and an example core network (CN) that may be used within the communications system illustrated in FIG. 1A;

[0019] FIG. ID is a system diagram illustrating a further example RAN and a further example CN that may be used within the communications system illustrated in FIG. 1 A;

[0020] FIG. 2 illustrates a flow chart of a method according to a first embodiment of the present principles;

[0021] FIG. 3 illustrates a flow chart of a method of a second embodiment of the present principles;

[0022] FIG. 4 illustrates a flow chart of a method of a third embodiment of the present principles;

[0023] FIG. 5 illustrates example segmentation and application of three linear piece-wise functions, to a function that maps SNR of sensing-related samples to the RMSE of a target metric;

[0024] FIG. 6 illustrates a Venn diagram with an initial set of functions, and subsets of functions that meet the SNR criteria, the computational delay criteria, or both;

[0025] FIG. 7 illustrates a flow chart of a method of a fourth embodiment of the present principles;

[0026] FIG. 8 depicts three examples of how a function can be fitted to the SNR values over time;

[0027] FIG. 9 illustrates a flow chart of a method according to a fifth embodiment of the present principles;

[0028] FIG. 10 illustrates a flow chart of a method according to a sixth embodiment of the present principles;

[0029] FIG. 11 illustrates an example of time series prediction for SNR;

[0030] FIG. 12 shows the relationship between the CRLB of range and velocity estimation under different SNRs;

[0031] FIG. 13 illustrates requirements provided in 3GPP TS 22.837 Table 5.1.6-1 for intruder detection cases; and

[0032] FIG. 14 illustrates requirements provided in 3GPP TS 22.837 Table 5.10.6-1 for UAV flight trajectory tracing.DETAILED DESCRIPTION

[0033] In the following detailed description, numerous specific details are set forth to provide a thorough understanding of embodiments and / or examples disclosed herein. However, it will be understood that such embodiments and examples may be practiced without some or all of the specific details set forth herein. In other instances, well-known methods, procedures, components and circuits have not been described in detail, so as not to obscure the following description. Further, embodiments and examples not specifically described herein may be practiced in lieu of, or in combination with, the embodiments and other examples described, disclosed or otherwise provided explicitly, implicitly and / or inherently (collectively "provided") herein. Although various embodiments are described and / or claimed herein in which an apparatus, system, device, etc. and / or any element thereof carries out an operation, process, algorithm, function, etc. and / or any portion thereof, it is to be understood that any embodiments described and / or claimed herein assume that any apparatus, system, device, etc. and / or any element thereof is configured to carry out any operation, process, algorithm, function, etc. and / or any portion thereof.

[0034] Example Communications System

[0035] The methods, apparatuses and systems provided herein are well-suited for communications involving both wired and wireless networks. An overview of various types of wireless devices and infrastructure is provided with respect to FIGs. 1A-1D, where various elements of the network may utilize, perform, be arranged in accordance with and / or be adapted and / or configured for the methods, apparatuses and systems provided herein.

[0036] FIG. 1A is a system diagram illustrating an example communications system 100 in which one or more disclosed embodiments may be implemented. The communications system 100 may be a multiple access system that provides content, such as voice, data, video, messaging, broadcast, etc., to multiple wireless users. The communications system 100 may enable multiple wireless users to access such content through the sharing of system resources, including wireless bandwidth. For example, the communications systems 100 may employ one or more channel access methods, such as code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal FDMA (OFDMA), singlecarrier FDMA (SC-FDMA), zero-tail (ZT) unique-word (UW) discreet Fourier transform (DFT) spread OFDM (ZT UW DTS-s OFDM), unique word OFDM (UW-OFDM), resource block- filtered OFDM, filter bank multicarrier (FBMC), and the like.

[0037] As shown in FIG. 1A, the communications system 100 may include wireless transmit / receive units (WTRUs) 102a, 102b, 102c, 102d, a radio access network (RAN) 104 / 113, a core network (CN) 106 / 115, a public switched telephone network (PSTN) 108, the Internet 110, and other networks 112, though it will be appreciated that the disclosed embodiments contemplate any number of WTRUs, base stations, networks, and / or network elements. Each of the WTRUs 102a, 102b, 102c, 102d may be any type of device configured to operate and / or communicate in a wireless environment. By way of example, the WTRUs 102a, 102b, 102c, 102d, any of which may be referred to as a "station" and / or a "STA", may be configured to transmit and / or receive wireless signals and may include (or be) a user equipment (UE), a mobile station, a fixed or mobile subscriber unit, a subscription-based unit, a pager, a cellular telephone, a personal digital assistant (PDA), a smartphone, a laptop, a netbook, a personal computer, a wireless sensor, a hotspot or Mi- Fi device, an Internet of Things (loT) device, a watch or other wearable, a head-mounted display (HMD), a vehicle, a drone, a medical device and applications (e.g., remote surgery), an industrial device and applications (e.g., a robot and / or other wireless devices operating in an industrial and / or an automated processing chain contexts), a consumer electronics device, a device operating on commercial and / or industrial wireless networks, and the like. Any of the WTRUs 102a, 102b, 102c and 102d may be interchangeably referred to as a UE.

[0038] The communications systems 100 may also include a base station 114a and / or a base station 114b. Each of the base stations 114a, 114b may be any type of device configured to wirelessly interface with at least one of the WTRUs 102a, 102b, 102c, 102d, e.g., to facilitate access to one or more communication networks, such as the CN 106 / 115, the Internet 110, and / or the networks 112. By way of example, the base stations 114a, 114b may be any of a base transceiver station (BTS), a Node-B (NB), an eNode-B (eNB), a Home Node-B (HNB), a Home eNode-B (HeNB), a gNode-B (gNB), a NR Node-B (NR NB), a site controller, an access point (AP), a wireless router, and the like. While the base stations 114a, 114b are each depicted as a single element, it will be appreciated that the base stations 114a, 114b may include any number of interconnected base stations and / or network elements.

[0039] The base station 114a may be part of the RAN 104 / 113, which may also include other base stations and / or network elements (not shown), such as a base station controller (BSC), a radio network controller (RNC), relay nodes, etc. The base station 114a and / or the base station 114b may be configured to transmit and / or receive wireless signals on one or more carrier frequencies, which may be referred to as a cell (not shown). These frequencies may be in licensed spectrum, unlicensed spectrum, or a combination of licensed and unlicensed spectrum. A cell may provide coverage for a wireless service to a specific geographical area that may be relatively fixed or that may change over time. The cell may further be divided into cell sectors. For example, the cell associated with the base station 114a may be divided into three sectors. Thus, in an embodiment, the base station 114a may include three transceivers, i.e., one for each sector of the cell. In an embodiment, the base station 114a may employ multiple-input multiple output (MIMO) technology and may utilize multiple transceivers for each or any sector of the cell. For example, beamforming may be used to transmit and / or receive signals in desired spatial directions.

[0040] The base stations 114a, 114b may communicate with one or more of the WTRUs 102a, 102b, 102c, 102d over an air interface 116, which may be any suitable wireless communication link (e.g., radio frequency (RF), microwave, centimeter wave, micrometer wave, infrared (IR), ultraviolet (UV), visible light, etc.). The air interface 116 may be established using any suitable radio access technology (RAT).

[0041] More specifically, as noted above, the communications system 100 may be a multiple access system and may employ one or more channel access schemes, such as CDMA, TDMA, FDMA, OFDMA, SC-FDMA, and the like. For example, the base station 114a in the RAN 104 / 113 and the WTRUs 102a, 102b, 102c may implement a radio technology such as Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access (UTRA), which may establish the air interface 116 using wideband CDMA (WCDMA). WCDMA may include communicationprotocols such as High-Speed Packet Access (HSPA) and / or Evolved HSPA (HSPA+). HSPA may include High-Speed Downlink Packet Access (HSDPA) and / or High-Speed Uplink Packet Access (HSUPA).

[0042] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement a radio technology such as Evolved UMTS Terrestrial Radio Access (E-UTRA), which may establish the air interface 116 using Long Term Evolution (LTE) and / or LTE- Advanced (LTE-A) and / or LTE-Advanced Pro (LTE-A Pro).

[0043] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement a radio technology such as NR Radio Access, which may establish the air interface 116 using New Radio (NR).

[0044] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement multiple radio access technologies. For example, the base station 114a and the WTRUs 102a, 102b, 102c may implement LTE radio access and NR radio access together, for instance using dual connectivity (DC) principles. Thus, the air interface utilized by WTRUs 102a, 102b, 102c may be characterized by multiple types of radio access technologies and / or transmissions sent to / from multiple types of base stations (e.g., an eNB and a gNB).

[0045] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement radio technologies such as IEEE 802.11 (i.e., Wireless Fidelity (Wi-Fi), IEEE 802.16 (i.e., Worldwide Interoperability for Microwave Access (WiMAX)), CDMA2000, CDMA2000 IX, CDMA2000 EV-DO, Interim Standard 2000 (IS-2000), Interim Standard 95 (IS-95), Interim Standard 856 (IS-856), Global System for Mobile communications (GSM), Enhanced Data rates for GSM Evolution (EDGE), GSM EDGE (GERAN), and the like.

[0046] The base station 114b in FIG. 1 A may be a wireless router, Home Node-B, Home eNode- B, or access point, for example, and may utilize any suitable RAT for facilitating wireless connectivity in a localized area, such as a place of business, a home, a vehicle, a campus, an industrial facility, an air corridor (e.g., for use by drones), a roadway, and the like. In an embodiment, the base station 114b and the WTRUs 102c, 102d may implement a radio technology such as IEEE 802.11 to establish a wireless local area network (WLAN). In an embodiment, the base station 114b and the WTRUs 102c, 102d may implement a radio technology such as IEEE 802.15 to establish a wireless personal area network (WPAN). In an embodiment, the base station 114b and the WTRUs 102c, 102d may utilize a cellular-based RAT (e.g., WCDMA, CDMA2000, GSM, LTE, LTE-A, LTE-A Pro, NR, etc.) to establish any of a small cell, picocell or femtocell. As shown in FIG. 1 A, the base station 114b may have a direct connection to the Internet 110. Thus, the base station 114b may not be required to access the Internet 110 via the CN 106 / 115.

[0047] The RAN 104 / 113 may be in communication with the CN 106 / 115, which may be any type of network configured to provide voice, data, applications, and / or voice over internet protocol (VoIP) services to one or more of the WTRUs 102a, 102b, 102c, 102d. The data may have varying quality of service (QoS) requirements, such as differing throughput requirements, latency requirements, error tolerance requirements, reliability requirements, data throughput requirements, mobility requirements, and the like. The CN 106 / 115 may provide call control, billing services, mobile location-based services, pre-paid calling, Internet connectivity, video distribution, etc., and / or perform high-level security functions, such as user authentication. Although not shown in FIG. 1 A, it will be appreciated that the RAN 104 / 113 and / or the CN 106 / 115 may be in direct or indirect communication with other RANs that employ the same RAT as the RAN 104 / 113 or a different RAT. For example, in addition to being connected to the RAN 104 / 113, which may be utilizing an NR radio technology, the CN 106 / 115 may also be in communication with another RAN (not shown) employing any of a GSM, UMTS, CDMA 2000, WiMAX, E-UTRA, or Wi-Fi radio technology.

[0048] The CN 106 / 115 may also serve as a gateway for the WTRUs 102a, 102b, 102c, 102d to access the PSTN 108, the Internet 110, and / or other networks 112. The PSTN 108 may include circuit-switched telephone networks that provide plain old telephone service (POTS). The Internet 110 may include a global system of interconnected computer networks and devices that use common communication protocols, such as the transmission control protocol (TCP), user datagram protocol (UDP) and / or the internet protocol (IP) in the TCP / IP internet protocol suite. The networks 112 may include wired and / or wireless communications networks owned and / or operated by other service providers. For example, the networks 112 may include another CN connected to one or more RANs, which may employ the same RAT as the RAN 104 / 114 or a different RAT.

[0049] Some or all of the WTRUs 102a, 102b, 102c, 102d in the communications system 100 may include multi-mode capabilities (e.g., the WTRUs 102a, 102b, 102c, 102d may include multiple transceivers for communicating with different wireless networks over different wireless links). For example, the WTRU 102c shown in FIG. 1A may be configured to communicate with the base station 114a, which may employ a cellular-based radio technology, and with the base station 114b, which may employ an IEEE 802 radio technology.

[0050] FIG. IB is a system diagram illustrating an example WTRU 102. As shown in FIG. IB, the WTRU 102 may include a processor 118, a transceiver 120, a transmit / receive element 122, a speaker / microphone 124, a keypad 126, a display / touchpad 128, non-removable memory 130, removable memory 132, a power source 134, a global positioning system (GPS) chipset 136,and / or other elements / peripherals 138, among others. It will be appreciated that the WTRU 102 may include any sub-combination of the foregoing elements while remaining consistent with an embodiment.

[0051] The processor 118 may be a general purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) circuits, any other type of integrated circuit (IC), a state machine, and the like. The processor 118 may perform signal coding, data processing, power control, input / output processing, and / or any other functionality that enables the WTRU 102 to operate in a wireless environment. The processor 118 may be coupled to the transceiver 120, which may be coupled to the transmit / receive element 122. While FIG. IB depicts the processor 118 and the transceiver 120 as separate components, it will be appreciated that the processor 118 and the transceiver 120 may be integrated together, e.g., in an electronic package or chip.

[0052] The transmit / receive element 122 may be configured to transmit signals to, or receive signals from, a base station (e.g., the base station 114a) over the air interface 116. For example, in an embodiment, the transmit / receive element 122 may be an antenna configured to transmit and / or receive RF signals. In an embodiment, the transmit / receive element 122 may be an emitter / detector configured to transmit and / or receive IR, UV, or visible light signals, for example. In an embodiment, the transmit / receive element 122 may be configured to transmit and / or receive both RF and light signals. It will be appreciated that the transmit / receive element 122 may be configured to transmit and / or receive any combination of wireless signals.

[0053] Although the transmit / receive element 122 is depicted in FIG. IB as a single element, the WTRU 102 may include any number of transmit / receive elements 122. For example, the WTRU 102 may employ MIMO technology. Thus, in an embodiment, the WTRU 102 may include two or more transmit / receive elements 122 (e.g., multiple antennas) for transmitting and receiving wireless signals over the air interface 116.

[0054] The transceiver 120 may be configured to modulate the signals that are to be transmitted by the transmit / receive element 122 and to demodulate the signals that are received by the transmit / receive element 122. As noted above, the WTRU 102 may have multi-mode capabilities. Thus, the transceiver 120 may include multiple transceivers for enabling the WTRU 102 to communicate via multiple RATs, such as NR and IEEE 802.11, for example.

[0055] The processor 118 of the WTRU 102 may be coupled to, and may receive user input data from, the speaker / microphone 124, the keypad 126, and / or the display / touchpad 128 (e.g., a liquidcrystal display (LCD) display unit or organic light-emitting diode (OLED) display unit). The processor 118 may also output user data to the speaker / microphone 124, the keypad 126, and / or the display / touchpad 128. In addition, the processor 118 may access information from, and store data in, any type of suitable memory, such as the non-removable memory 130 and / or the removable memory 132. The non-removable memory 130 may include random-access memory (RAM), readonly memory (ROM), a hard disk, or any other type of memory storage device. The removable memory 132 may include a subscriber identity module (SIM) card, a memory stick, a secure digital (SD) memory card, and the like. In other embodiments, the processor 118 may access information from, and store data in, memory that is not physically located on the WTRU 102, such as on a server or a home computer (not shown).

[0056] The processor 118 may receive power from the power source 134, and may be configured to distribute and / or control the power to the other components in the WTRU 102. The power source 134 may be any suitable device for powering the WTRU 102. For example, the power source 134 may include one or more dry cell batteries (e.g., nickel-cadmium (NiCd), nickel-zinc (NiZn), nickel metal hydride (NiMH), lithium-ion (Li-ion), etc.), solar cells, fuel cells, and the like.

[0057] The processor 118 may also be coupled to the GPS chipset 136, which may be configured to provide location information (e.g., longitude and latitude) regarding the current location of the WTRU 102. In addition to, or in lieu of, the information from the GPS chipset 136, the WTRU 102 may receive location information over the air interface 116 from a base station (e.g., base stations 114a, 114b) and / or determine its location based on the timing of the signals being received from two or more nearby base stations. It will be appreciated that the WTRU 102 may acquire location information by way of any suitable location-determination method while remaining consistent with an embodiment.

[0058] The processor 118 may further be coupled to other elements / peripherals 138, which may include one or more software and / or hardware modules / units that provide additional features, functionality and / or wired or wireless connectivity. For example, the elements / peripherals 138 may include an accelerometer, an e-compass, a satellite transceiver, a digital camera (e.g., for photographs and / or video), a universal serial bus (USB) port, a vibration device, a television transceiver, a hands free headset, a Bluetooth® module, a frequency modulated (FM) radio unit, a digital music player, a media player, a video game player module, an Internet browser, a virtual reality and / or augmented reality (VR / AR) device, an activity tracker, and the like. The elements / peripherals 138 may include one or more sensors, the sensors may be one or more of a gyroscope, an accelerometer, a hall effect sensor, a magnetometer, an orientation sensor, a proximity sensor, a temperature sensor, a time sensor; a geolocation sensor; an altimeter, a lightsensor, a touch sensor, a magnetometer, a barometer, a gesture sensor, a biometric sensor, and / or a humidity sensor.

[0059] The WTRU 102 may include a full duplex radio for which transmission and reception of some or all of the signals (e.g., associated with particular subframes for both the uplink (e.g., for transmission) and downlink (e.g., for reception) may be concurrent and / or simultaneous. The full duplex radio may include an interference management unit to reduce and or substantially eliminate self-interference via either hardware (e.g., a choke) or signal processing via a processor (e.g., a separate processor (not shown) or via processor 118). In an embodiment, the WTRU 102 may include a half-duplex radio for which transmission and reception of some or all of the signals (e.g., associated with particular subframes for either the uplink (e.g., for transmission) or the downlink (e.g., for reception)).

[0060] FIG. 1C is a system diagram illustrating the RAN 104 and the CN 106 according to an embodiment. As noted above, the RAN 104 may employ an E-UTRA radio technology to communicate with the WTRUs 102a, 102b, and 102c over the air interface 116. The RAN 104 may also be in communication with the CN 106.

[0061] The RAN 104 may include eNode-Bs 160a, 160b, 160c, though it will be appreciated that the RAN 104 may include any number of eNode-Bs while remaining consistent with an embodiment. The eNode-Bs 160a, 160b, 160c may each include one or more transceivers for communicating with the WTRUs 102a, 102b, 102c over the air interface 116. In an embodiment, the eNode-Bs 160a, 160b, 160c may implement MIMO technology. Thus, the eNode-B 160a, for example, may use multiple antennas to transmit wireless signals to, and receive wireless signals from, the WTRU 102a.

[0062] Each of the eNode-Bs 160a, 160b, and 160c may be associated with a particular cell (not shown) and may be configured to handle radio resource management decisions, handover decisions, scheduling of users in the uplink (UL) and / or downlink (DL), and the like. As shown in FIG. 1C, the eNode-Bs 160a, 160b, 160c may communicate with one another over an X2 interface.

[0063] The CN 106 shown in FIG. 1C may include a mobility management entity (MME) 162, a serving gateway (SGW) 164, and a packet data network (PDN) gateway (PGW) 166. While each of the foregoing elements are depicted as part of the CN 106, it will be appreciated that any one of these elements may be owned and / or operated by an entity other than the CN operator.

[0064] The MME 162 may be connected to each of the eNode-Bs 160a, 160b, and 160c in the RAN 104 via an SI interface and may serve as a control node. For example, the MME 162 may be responsible for authenticating users of the WTRUs 102a, 102b, 102c, bearer activation / deactivation, selecting a particular serving gateway during an initial attach of theWTRUs 102a, 102b, 102c, and the like. The MME 162 may provide a control plane function for switching between the RAN 104 and other RANs (not shown) that employ other radio technologies, such as GSM and / or WCDMA.

[0065] The SGW 164 may be connected to each of the eNode-Bs 160a, 160b, 160c in the RAN 104 via the SI interface. The SGW 164 may generally route and forward user data packets to / from the WTRUs 102a, 102b, 102c. The SGW 164 may perform other functions, such as anchoring user planes during inter-eNode-B handovers, triggering paging when DL data is available for the WTRUs 102a, 102b, 102c, managing and storing contexts of the WTRUs 102a, 102b, 102c, and the like.

[0066] The SGW 164 may be connected to the PGW 166, which may provide the WTRUs 102a, 102b, 102c with access to packet-switched networks, such as the Internet 110, to facilitate communications between the WTRUs 102a, 102b, 102c and IP-enabled devices.

[0067] The CN 106 may facilitate communications with other networks. For example, the CN 106 may provide the WTRUs 102a, 102b, 102c with access to circuit-switched networks, such as the PSTN 108, to facilitate communications between the WTRUs 102a, 102b, 102c and traditional land-line communications devices. For example, the CN 106 may include, or may communicate with, an IP gateway (e.g., an IP multimedia subsystem (IMS) server) that serves as an interface between the CN 106 and the PSTN 108. In addition, the CN 106 may provide the WTRUs 102a, 102b, 102c with access to the other networks 112, which may include other wired and / or wireless networks that are owned and / or operated by other service providers.

[0068] Although the WTRU is described in FIGs. 1A-1D as a wireless terminal, it is contemplated that in certain representative embodiments that such a terminal may use (e.g., temporarily or permanently) wired communication interfaces with the communication network.

[0069] In representative embodiments, the other network 112 may be a WLAN.

[0070] A WLAN in infrastructure basic service set (BSS) mode may have an access point (AP) for the BSS and one or more stations (STAs) associated with the AP. The AP may have an access or an interface to a distribution system (DS) or another type of wired / wireless network that carries traffic into and / or out of the BSS. Traffic to STAs that originates from outside the BSS may arrive through the AP and may be delivered to the STAs. Traffic originating from STAs to destinations outside the BSS may be sent to the AP to be delivered to respective destinations. Traffic between STAs within the BSS may be sent through the AP, for example, where the source STA may send traffic to the AP and the AP may deliver the traffic to the destination STA. The traffic between STAs within a BSS may be considered and / or referred to as peer-to-peer traffic. The peer-to-peer traffic may be sent between (e.g., directly between) the source and destination STAs with a directlink setup (DLS). In certain representative embodiments, the DLS may use an 802. l ie DLS or an 802.1 Iz tunneled DLS (TDLS). A WLAN using an Independent BSS (IBSS) mode may not have an AP, and the STAs (e.g., all of the STAs) within or using the IBSS may communicate directly with each other. The IBSS mode of communication may sometimes be referred to herein as an "ad-hoc" mode of communication.

[0071] When using the 802.1 lac infrastructure mode of operation or a similar mode of operations, the AP may transmit a beacon on a fixed channel, such as a primary channel. The primary channel may be a fixed width (e.g., 20 MHz wide bandwidth) or a dynamically set width via signaling. The primary channel may be the operating channel of the BSS and may be used by the STAs to establish a connection with the AP. In certain representative embodiments, Carrier sense multiple access with collision avoidance (CSMA / CA) may be implemented, for example in in 802.11 systems. For CSMA / CA, the STAs (e.g., every STA), including the AP, may sense the primary channel. If the primary channel is sensed / detected and / or determined to be busy by a particular STA, the particular STA may back off. One STA (e.g., only one station) may transmit at any given time in a given BSS.

[0072] High throughput (HT) STAs may use a 40 MHz wide channel for communication, for example, via a combination of the primary 20 MHz channel with an adjacent or nonadj acent 20 MHz channel to form a 40 MHz wide channel.

[0073] Very high throughput (VHT) STAs may support 20 MHz, 40 MHz, 80 MHz, and / or 160 MHz wide channels. The 40 MHz, and / or 80 MHz, channels may be formed by combining contiguous 20 MHz channels. A 160 MHz channel may be formed by combining 8 contiguous 20 MHz channels, or by combining two non-contiguous 80 MHz channels, which may be referred to as an 80+80 configuration. For the 80+80 configuration, the data, after channel encoding, may be passed through a segment parser that may divide the data into two streams. Inverse fast fourier transform (IFFT) processing, and time domain processing, may be done on each stream separately. The streams may be mapped on to the two 80 MHz channels, and the data may be transmitted by a transmitting STA. At the receiver of the receiving STA, the above-described operation for the 80+80 configuration may be reversed, and the combined data may be sent to a medium access control (MAC) layer, entity, etc.

[0074] Sub 1 GHz modes of operation are supported by 802.1 laf and 802.11 ah. The channel operating bandwidths, and carriers, are reduced in 802.1 laf and 802.1 lah relative to those used in 802.1 In, and 802.1 lac. 802.1 laf supports 5 MHz, 10 MHz and 20 MHz bandwidths in the TV white space (TVWS) spectrum, and 802.1 lah supports 1 MHz, 2 MHz, 4 MHz, 8 MHz, and 16 MHz bandwidths using non-TVWS spectrum. According to a representative embodiment,802.11ah may support meter type control / machine-type communications (MTC), such as MTC devices in a macro coverage area. MTC devices may have certain capabilities, for example, limited capabilities including support for (e.g., only support for) certain and / or limited bandwidths. The MTC devices may include a battery with a battery life above a threshold (e.g., to maintain a very long battery life).

[0075] WLAN systems, which may support multiple channels, and channel bandwidths, such as 802.1 In, 802.1 lac, 802.11af, and 802.1 lah, include a channel which may be designated as the primary channel. The primary channel may have a bandwidth equal to the largest common operating bandwidth supported by all STAs in the BSS. The bandwidth of the primary channel may be set and / or limited by a STA, from among all STAs in operating in a BSS, which supports the smallest bandwidth operating mode. In the example of 802.1 lah, the primary channel may be 1 MHz wide for STAs (e.g., MTC type devices) that support (e.g., only support) a 1 MHz mode, even if the AP, and other STAs in the BSS support 2 MHz, 4 MHz, 8 MHz, 16 MHz, and / or other channel bandwidth operating modes. Carrier sensing and / or network allocation vector (NAV) settings may depend on the status of the primary channel. If the primary channel is busy, for example, due to a STA (which supports only a 1 MHz operating mode), transmitting to the AP, the entire available frequency bands may be considered busy even though a majority of the frequency bands remains idle and may be available.

[0076] In the United States, the available frequency bands, which may be used by 802.1 lah, are from 902 MHz to 928 MHz. In Korea, the available frequency bands are from 917.5 MHz to 923.5 MHz. In Japan, the available frequency bands are from 916.5 MHz to 927.5 MHz. The total bandwidth available for 802.1 lah is 6 MHz to 26 MHz depending on the country code.

[0077] FIG. ID is a system diagram illustrating the RAN 113 and the CN 115 according to an embodiment. As noted above, the RAN 113 may employ an NR radio technology to communicate with the WTRUs 102a, 102b, 102c over the air interface 116. The RAN 113 may also be in communication with the CN 115.

[0078] The RAN 113 may include gNBs 180a, 180b, 180c, though it will be appreciated that the RAN 113 may include any number of gNBs while remaining consistent with an embodiment. The gNBs 180a, 180b, 180c may each include one or more transceivers for communicating with the WTRUs 102a, 102b, 102c over the air interface 116. In an embodiment, the gNBs 180a, 180b, 180c may implement MIMO technology. For example, gNBs 180a, 180b may utilize beamforming to transmit signals to and / or receive signals from the WTRUs 102a, 102b, 102c. Thus, the gNB 180a, for example, may use multiple antennas to transmit wireless signals to, and / or receive wireless signals from, the WTRU 102a. In an embodiment, the gNBs 180a, 180b, 180c mayimplement carrier aggregation technology. For example, the gNB 180a may transmit multiple component carriers to the WTRU 102a (not shown). A subset of these component carriers may be on unlicensed spectrum while the remaining component carriers may be on licensed spectrum. In an embodiment, the gNBs 180a, 180b, 180c may implement Coordinated Multi-Point (CoMP) technology. For example, WTRU 102a may receive coordinated transmissions from gNB 180a and gNB 180b (and / or gNB 180c).

[0079] The WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c using transmissions associated with a scalable numerology. For example, OFDM symbol spacing and / or OFDM subcarrier spacing may vary for different transmissions, different cells, and / or different portions of the wireless transmission spectrum. The WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c using subframe or transmission time intervals (TTIs) of various or scalable lengths (e.g., including a varying number of OFDM symbols and / or lasting varying lengths of absolute time).

[0080] The gNBs 180a, 180b, 180c may be configured to communicate with the WTRUs 102a, 102b, 102c in a standalone configuration and / or a non- standalone configuration. In the standalone configuration, WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c without also accessing other RANs (e.g., such as eNode-Bs 160a, 160b, 160c). In the standalone configuration, WTRUs 102a, 102b, 102c may utilize one or more of gNBs 180a, 180b, 180c as a mobility anchor point. In the standalone configuration, WTRUs 102a, 102b, 102c may communicate with gNBs 180a, 180b, 180c using signals in an unlicensed band. In a non- standalone configuration WTRUs 102a, 102b, 102c may communicate with / connect to gNBs 180a, 180b, 180c while also communicating with / connecting to another RAN such as eNode-Bs 160a, 160b, 160c. For example, WTRUs 102a, 102b, 102c may implement DC principles to communicate with one or more gNBs 180a, 180b, 180c and one or more eNode-Bs 160a, 160b, 160c substantially simultaneously. In the non- standalone configuration, eNode-Bs 160a, 160b, 160c may serve as a mobility anchor for WTRUs 102a, 102b, 102c and gNBs 180a, 180b, 180c may provide additional coverage and / or throughput for servicing WTRUs 102a, 102b, 102c.

[0081] Each of the gNBs 180a, 180b, 180c may be associated with a particular cell (not shown) and may be configured to handle radio resource management decisions, handover decisions, scheduling of users in the UL and / or DL, support of network slicing, dual connectivity, interworking between NR and E-UTRA, routing of user plane data towards user plane functions (UPFs) 184a, 184b, routing of control plane information towards access and mobility management functions (AMFs) 182a, 182b, and the like. As shown in FIG. ID, the gNBs 180a, 180b, 180c may communicate with one another over an Xn interface.

[0082] The CN 115 shown in FIG. ID may include at least one AMF 182a, 182b, at least one UPF 184a, 184b, at least one session management function (SMF) 183a, 183b, and at least one Data Network (DN) 185a, 185b. While each of the foregoing elements are depicted as part of the CN 115, it will be appreciated that any of these elements may be owned and / or operated by an entity other than the CN operator.

[0083] The AMF 182a, 182b may be connected to one or more of the gNBs 180a, 180b, 180c in the RAN 113 via an N2 interface and may serve as a control node. For example, the AMF 182a, 182b may be responsible for authenticating users of the WTRUs 102a, 102b, 102c, support for network slicing (e.g., handling of different protocol data unit (PDU) sessions with different requirements), selecting a particular SMF 183a, 183b, management of the registration area, termination of NAS signaling, mobility management, and the like. Network slicing may be used by the AMF 182a, 182b, e.g., to customize CN support for WTRUs 102a, 102b, 102c based on the types of services being utilized WTRUs 102a, 102b, 102c. For example, different network slices may be established for different use cases such as services relying on ultra-reliable low latency (URLLC) access, services relying on enhanced massive mobile broadband (eMBB) access, services for MTC access, and / or the like. The AMF 162 may provide a control plane function for switching between the RAN 113 and other RANs (not shown) that employ other radio technologies, such as LTE, LTE-A, LTE-A Pro, and / or non-3GPP access technologies such as WiFi.

[0084] The SMF 183a, 183b may be connected to an AMF 182a, 182b in the CN 115 via an N11 interface. The SMF 183a, 183b may also be connected to a UPF 184a, 184b in the CN 115 via an N4 interface. The SMF 183a, 183b may select and control the UPF 184a, 184b and configure the routing of traffic through the UPF 184a, 184b. The SMF 183a, 183b may perform other functions, such as managing and allocating UE IP address, managing PDU sessions, controlling policy enforcement and QoS, providing downlink data notifications, and the like. A PDU session type may be IP -based, non-IP based, Ethernet-based, and the like.

[0085] The UPF 184a, 184b may be connected to one or more of the gNBs 180a, 180b, 180c in the RAN 113 via an N3 interface, which may provide the WTRUs 102a, 102b, 102c with access to packet-switched networks, such as the Internet 110, e.g., to facilitate communications between the WTRUs 102a, 102b, 102c and IP-enabled devices. The UPF 184, 184b may perform other functions, such as routing and forwarding packets, enforcing user plane policies, supporting multihomed PDU sessions, handling user plane QoS, buffering downlink packets, providing mobility anchoring, and the like.

[0086] The CN 115 may facilitate communications with other networks. For example, the CN 115 may include, or may communicate with, an IP gateway (e.g., an IP multimedia subsystem (IMS) server) that serves as an interface between the CN 115 and the PSTN 108. In addition, the CN 115 may provide the WTRUs 102a, 102b, 102c with access to the other networks 112, which may include other wired and / or wireless networks that are owned and / or operated by other service providers. In an embodiment, the WTRUs 102a, 102b, 102c may be connected to a local Data Network (DN) 185a, 185b through the UPF 184a, 184b via the N3 interface to the UPF 184a, 184b and an N6 interface between the UPF 184a, 184b and the DN 185a, 185b.

[0087] In view of FIGs. 1 A-1D, and the corresponding description of FIGs. 1 A-1D, one or more, or all, of the functions described herein with regard to any of: WTRUs 102a-d, base stations 114a- b, eNode-Bs 160a-c, MME 162, SGW 164, PGW 166, gNBs 180a-c, AMFs 182a-b, UPFs 184a- b, SMFs 183a-b, DNs 185a-b, and / or any other element(s) / device(s) described herein, may be performed by one or more emulation elements / devices (not shown). The emulation devices may be one or more devices configured to emulate one or more, or all, of the functions described herein. For example, the emulation devices may be used to test other devices and / or to simulate network and / or WTRU functions.

[0088] The emulation devices may be designed to implement one or more tests of other devices in a lab environment and / or in an operator network environment. For example, the one or more emulation devices may perform the one or more, or all, functions while being fully or partially implemented and / or deployed as part of a wired and / or wireless communication network in order to test other devices within the communication network. The one or more emulation devices may perform the one or more, or all, functions while being temporarily implemented / deployed as part of a wired and / or wireless communication network. The emulation device may be directly coupled to another device for purposes of testing and / or may performing testing using over-the-air wireless communications.

[0089] The one or more emulation devices may perform the one or more, including all, functions while not being implemented / deployed as part of a wired and / or wireless communication network. For example, the emulation devices may be utilized in a testing scenario in a testing laboratory and / or a non-deployed (e.g., testing) wired and / or wireless communication network in order to implement testing of one or more components. The one or more emulation devices may be test equipment. Direct RF coupling and / or wireless communications via RF circuitry (e.g., which may include one or more antennas) may be used by the emulation devices to transmit and / or receive data.

[0090] Introduction

[0091] In integrated sensing and communications (ISAC), the goal of sensing is different than that of conventional communication. The focus of communication is retrieving the information message (bits or packets) received by the receiver. Bit / block error rate (BLER) or packet error rate (PER) are typical metrics used to evaluate the communication performance. Sensing, on the other hand, is related to the estimation of metrics extracted from characteristics impacting the signal itself, such as delay, Doppler (including micro-Doppler) or angle (A-AOA, Z-AOA) etc. These metrics may contribute differently to the sensing performance and hence various error sources may exist. Therefore, different metrics may require different changes in radio resource allocation to improve the performance or to achieve a successful sensing task performance. For instance, when highly unambiguous estimation of velocity is needed, measurement over more, for example OFDM, symbols (which requires more time allocation for the sensing task) can provide better velocity resolution and accuracy [see for example Henk Wymeersch et al. “Final Models and Measurements for Localisation and Sensing,” Hexa-X Deliverable D3.3], Similarly, it is verified from “5G PRS-Based Sensing: A Sensing Reference Signal Approach for Joint Sensing and Communication System” [Z. Wei et al., in IEEE Transactions n Vehicular Technology, vol. 72, no. 3, pp. 3250-3263, March 2023] that by increasing the length of the OFDM symbols used in sensing, the Cramer-Rao lower bound (CRLB) of range estimation decreases, while the CRLB of velocity estimation increases. As can be seen, there is a sensing performance trade-off that needs to be considered to satisfy the accuracy requirements for both range and velocity estimation in radar sensing. Furthermore, these metrics (i.e., delay, doppler, angles), may have different Signal- to-Noise Ratio (SNR) requirements to contribute positively to a sensing task. These aspects are not considered in conventional solutions such as 3GPP standards. It will be appreciated that it is important to make consider this trade-off when deciding on resource configuration for a sensing task. Furthermore, certain metrics, for example micro-Doppler and single bounce versus multiple bounce identification, are unique to sensing that may be useful to achieve the desired overall sensing performance.

[0092] It follows that identification and characterization of metrics and corresponding errors are important for sensing, in particular when a device (e.g. a receiver) is to perform a sensing task that requires a certain level of accuracy, resolution or integrity.

[0093] To understand the effect of reference signal parameters on sensing capabilities, a brief description of the bandwidth part and positioning reference signals (PRS) is presented in the Annex. Different sensing metrics mapped to the reference signal parameters are also presented in the Annex.

[0094] Sensing will coexist with communication, but will, as mentioned have different requirements and resource demands. Currently, in 3GPP systems such as 5G, there is no mechanism to allocate resources to or to enable sensing tasks in ISAC. Sensing is a task-oriented mechanism, where many use cases require (re)adjustment of resource allocation during an ongoing sensing task to increase the probability of achieving the required sensing performance. Moreover, the sensing task will have a certain latency budget (time required to achieve the required sensing performance), which that a receiver will have a certain time limit to achieve the desired performance, possibly communicating at the same time. This creates another difficulty when determining the resource allocation or reconfiguration, that needs to be determined considering both the accuracy / resolution of sensing metrics, and the sensing latency budget.

[0095] One problem addressed is how to enable the terminal / receiver side to help optimize the radio resource allocation for sensing in an ISAC context provided the aforementioned difficulties and limitations. Herein, a bi-static sensing mode is assumed, where a transmitter (e.g., a Base Station) emits the sensing signal, and a separate node (receiver, e.g. UE) receives the sensing signal. However, the present principles also extent to other sensing modes such as monostatic mode where the same node transmits and receives the sensing signal.

[0096] Aspects common to embodiments

[0097] A number of embodiments of the present principles are presented herein. Aspects common to at least some of these embodiments are described here, before the embodiments themselves.

[0098] Common Terminology

[0099] The terms AI / ML and AIML are used interchangeably.

[0100] The terms “prediction”, “projection”, “expectation”, and “estimation” are used interchangeably.

[0101] The terms “predicted”, “projected”, “expected”, and “estimated” are used interchangeably.

[0102] The terms “report” and “indication” are used interchangeably.

[0103] Estimators

[0104] In statistics, an estimator is a rule / function / algorithm for calculating an estimate of a given quantity based on observed data. It is typically used when the observed data is prone to error(s), like with sensing related samples. The estimator takes one or more samples of observed data and estimates an approximate value from the samples.

[0105] Accuracy of sensing metrics

[0106] The term “accuracy” is used herein as a key parameter to measure the performance of sensing-related metrics, e.g., delay, Doppler, and angles. The accuracy of these metrics may be determined using measurements defined in the “Measurements” section of the Annex or by measuring the metric itself (e.g., delay measurements) directly from the sensing signal. The overall performance of a sensing task for different uses cases of sensing depends on the accuracy of one or more of the metrics (directly) or (indirectly) using measurements in the abovementioned “Measurements” section. The terms “resolution,” “accuracy,” and “integrity” may be used interchangeably as, in certain cases, the performance may be determined in terms of resolution or accuracy. Moreover, accuracy is also used in a broader sense, and it is different from the term “accuracy” used in positioning in 3GPP standards, even though there are similarities. As an example, the accuracy of Doppler may be a measure of confidence about the estimated value of the Doppler from the receiver sensing signal. This estimated value may be related to the resolution of the velocity of a target, e.g., a moving object, that is based on threshold values provided to the receiver by the network. In this example case, accuracy may also mean accuracy of the resolution of the velocity of a target.

[0107] The overall accuracy or the performance of the entire sensing task is a function of individual accuracies of sensing-related metrics along with SNR or other side information that may be provided to the function that calculates accuracy.

[0108] In some embodiments, it is assumed that the UE has a function that can measure the accuracy of each metric and that it can also measure how much each metric is contributing to the overall accuracy of the sensing task.

[0109] The overall accuracy is met when the objective of each task is achieved. 3GPP TS 22.837, Feasibility Study on Integrated Sensing and Communication (Release 19), in which a number of ISAC use cases are defined, provides some examples. The requirements for each use case are different and therefore overall accuracy may be achieved when all the requirements are met. FIG. 13 illustrates requirements provided in 3GPP TS 22.837 Table 5.1.6-1 for intruder detection cases and FIG. 14 illustrates requirements provided in Table 5.10.6-1 for UAV flight trajectory tracing. As can be seen, the requirements are significantly different. For example, for intruder detection, the accuracy of the positioning estimate is 10 m (both horizontal and vertical) and there is no requirement for the velocity estimate; for flight trajectory tracing, the accuracy of the position estimate is 1-2 m (both horizontal and vertical) and the accuracy of the velocity estimate is 1-2 m / s.

[0110] Therefore, overall accuracy is dependent on the satisfaction of requirements in each use case. Put another way, overall accuracy is dependent on meeting the performance requirements of one or more parameters mentioned in each use case.

[0111] The performance of sensing may also be determined in terms of resolution / integrity of Doppler, delay and angles and in this case, accuracy of resolution or integrity can be defined; these terms may be used interchangeably.

[0112] Metrics in sensing

[0113] The terms “metrics” and “estimates of sensing-related metrics” may be used interchangeably. In sensing, estimates of different metrics such as delay, Doppler, range and classification of single vs multiple bounce contribute to the desired performance of the sensing task (because they are only estimates, not true values). Another error that may occur in sensing is characterization of different objects based on their material properties or based on the reflective properties of the object. Therefore, all these metrices are sources of error for any sensing task. The contribution of each metric to the overall performance of the sensing task may be different. There may be a subset of errors contributing to the performance and it may vary from one use case to another. For example, a use case interested in velocity resolution might not be interested in classifying angular or delay errors, or the use case may have relaxed thresholds for delay and angles. However, for use cases where high unambiguous velocity or high velocity resolution is required, all of these errors may be important.

[0114] As already explained, there exist various sources of error in sensing, at least some of which will now be described. It will be appreciated that while certain metrics - for example delay, Doppler and angles - are used herein as examples, the embodiments of the present principles are not limited to these metrics; the metric(s) used will depend on the use case.

[0115] Timing errors (delay errors): Time of Arrival (TO A) measurements can change due to time synchronization errors and hence affect range estimation. The estimated value of range and timing error may help the transmitter to timely adjust the configuration. The timing errors can directly cause ambiguity in range and speed estimation [see TS 38.215],

[0116] Doppler shift and velocity errors: due to mobility (of either target or the receiver), estimated Doppler shift may lead to errors in velocity resolution. Wider BW may help to mitigate along with Doppler estimation techniques.

[0117] Antenna directivity and gains errors: poor directivity of the antenna and / or low gain may lead to angular resolution errors. Better beamforming techniques and more antenna arrays may help to gain directivity and gains.

[0118] Angle estimation errors: these are due to the geometry of the environment; having a suboptimal position of the receiver or target may lead to these errors. These errors may be mitigated by, for example, having more antenna arrays at the receiver to enable more measurements.

[0119] SNR issues: low SNR is directly linked to inaccurate estimation of range and velocity. Moreover, interference can also influence SNR. SNR can be linked to Key Performance Indicators (KPIs) such that higher SNR means higher confidence, but the threshold may be different for TOA and Angle of Arrival (AOA) measurements.

[0120] Propagation and attenuation effects: multipath fading can affect the availability, i.e., percentage of time the system is able to provide sensing services according to the service requirements. Moreover, they can lead to range and velocity resolution errors.

[0121] A number of metrics are unique to sensing.

[0122] Micro-Doppler errors: micro-Doppler is linked to micro movements within an object. For instance, the motion of propellers in machinery or in a UAV, or motion of lips or hands in a human body may be characterized as being micro-Doppler.

[0123] Single bounce vs multiple bounce signals: a signal may be received at the receiver from different positions, and it may have bounced off objects once or multiple times. It is an important distinction in ISAC.

[0124] Characterization of objects with different material: material properties may be characterized at the receiver based on their reflection properties or Radar Cross Section (RCS). Different objects may be distinguished based on their material properties such as reflectivity or permeability.

[0125] Common principles and observations

[0126] In ISAC, sensing is performed using radio signals transmitted, received, scattered, and reflected by different network elements. Therefore, sensing may be performed using existing communication signals such as pilot signals or reference signals (RS) in OFDM or tailored sensing signals of any other waveform. Different reference signals may be used from legacy communication systems such as PRS, Sounding Reference Signal (SRS), Channel State Information Reference Signal (CSI-RS) etc., and other reference signals dedicated only to sensing may also be used.

[0127] Common benefits

[0128] Metrics and corresponding errors may be characterised and detected in different ways. Each sensing metric may contribute differently to the overall performance of the sensing task and,hence, various error sources may exist. The different metrics may require different changes in radio resource allocation for better performance.

[0129] Furthermore, the term sensing is used herein in a broad sense, with positioning as one example application of sensing. Therefore, the present principles are applicable to the positioning framework in 3 GPP, as well as to other wireless technologies. This does not preclude sidelinkbased positioning and / or sidelink-based sensing.

[0130] Applicability of the present principles includes different kinds of reference signals or pilot signals including but not limited to PRS, SRS, Sidelink Position Reference Signal (SL-PRS), CSI- RS, Synchronization Signal Block (SSB) or other signals that are used for radio-based sensing.

[0131] The present principles cover the bistatic case where a UE is the receiver and a gNB is the transmitter, but they are also applicable to when the UE is the transmitter and the gNB is the receiver. Similarly, they are also applicable to UE-UE sensing.

[0132] As already mentioned, the present principles are mainly described with reference to the bi-static sensing mode, where a transmitter (e.g., a Base Station or a UE) emits the sensing signal, and a terminal (UE, BS) receives it. However, they do not preclude other sensing modes, e.g., monostatic. The applications of the present principles are not limited to 3 GPP wireless communication devices but can also be used in other wireless networks, e.g., 802.11 WLAN, Bluetooth, LoRa. Zigbee etc.

[0133] A UE may use AI / ML-based methods to determine the accuracy and / or to determine the contribution of each metric and / or to determine the recommended configuration or to predict the time window in which SNR is going to be above / below a certain SNR threshold or other determinations in all the embodiments herein. Details on AI / ML operation may be found in the Annex.

[0134] Initial common solution components

[0135] In the present embodiments, the UE is configured to perform a sensing task (e.g., step 2a in embodiment 3, step la for the other embodiments). What a sensing task could be and what the corresponding configuration could look like will now be described.

[0136] A plurality of error sources corresponding to each metric such as delay, Doppler and angles may exist in sensing and, as mentioned, there are certain metrics that are particular to sensing such as micro-Doppler, object identification and characterization (e.g., via RCS). Usually, SNR is a good metric that is linked to the performance of each metric. For instance, higher SNR typically provides higher Doppler, delay and angle estimates. However, requirements of SNR for each metric may be different. There are several measurements that already exist in current wireless standards such as 3 GPP and some measurements that do not. Some 3 GPP measurements aredetailed in the “Measurements” section of the Annex. Error in delay, Doppler and angles, for instance, may be measured using TDOA, DL-TOA, RTT, or AoA (DL AoA is not yet part of standards, but may be estimated from a Precoding Matrix Indicator (PMI) of the beams). Similarly, DL timing drift is measured from Doppler estimation. Therefore, metrics may be directly or indirectly estimated from these measurements. Some errors may occur due to propagation and attenuation effects, hence lowering the received SNR. The performance of a sensing task may depend on one or more of these errors or on measurements of these metrices. For instance, velocity of a target may be estimated using TDOA or by measuring Doppler etc. Therefore, even if a metric is not directly estimated, it may in cases be estimated using other measurements. For example, TDOA or DL-TOA, RTT, etc. may be used for range estimation and hence any errors in time difference will impact range accuracy / resolution and therefore, measured delay is a source of error.

[0137] Current 3GPP standards support configuration of PRS signals. PRS resources follow a certain format: periodicity, BW, etc. Any RS can follow similar principles, where specific RS characteristics are configured, such as Transmission Reception Point (TRP) ID, BW, periodicity, number of slots occupied by the sensing signal, number of frames occupied by the sensing signal, etc.

[0138] The sensing task can be described as being service oriented and may comprise different configurable aspects to suit the desired sensing task outcome. In some embodiments, the sensing task may be concerned with single measurements (e.g., Doppler, delay, angles) or measurements described in the “Measurements” section of the Annex. In other embodiments, the sensing task may be a combination of one or more measurements. Following are examples of single measurements that can be combined and configured simultaneously or separately.

[0139] In different embodiments, the sensing task may include performing measurements of Doppler, including Doppler samples of the received RS over time, creating Doppler-delay maps, measuring Doppler shift, measuring resulting speed of e.g., a moving object or a moving UE in relation to an object, etc. These measurements can be performed once, for a short time period, for a longer time period. The measurements may also be further confined by certain SNR thresholds or ranges and may be associated with the measurement capabilities that the UE has. A number of examples will now be given. The UE may be configured with a sensing task that includes the creation of a Doppler-delay map over a period of time, where the measurements of Doppler are considered for the map if they are within a certain SNR range. The sensing task may be measuring Doppler shift until a certain threshold is reached. The sensing task may include determining a speed value from the Doppler shift measurements, where the UE is further instructed to consider Doppler shift measurements within a certain range only.

[0140] The measurement of Doppler may also be extended to micro-Doppler measurements. UE may take samples for micro-Doppler measurements based on another threshold values of SNR configured by the NW. The micro-Doppler measurements may be taken (performed) until the desired accuracy / resolution is achieved or the UE may take measurements until a specified time.

[0141] Performing measurements of delay from the sensing signal (or RS) or samples of RS may for example relate to locating an object and / or to distinguishing between one or more objects (object resolution task) and / or to measuring the distance of one or more object from the receiver. There are many ways this may be performed using existing techniques in 3GPP, including timing advance (TA), reference signal time difference (RSTD), round trip time (RTT), time different of arrival (TDOA) of two or more multipath components or two or more reference signals originating from different TRPs. The delay estimation may also be used for velocity estimation along with Doppler estimation of a particular target such as vehicle or a UAV. Delay estimation by the UE may also be used to detect and track moving objects. The measurements of delay estimation may be linked to certain SNR thresholds or pre-configured ranges depending on the task. The threshold values for localization and tracking of a vehicle might be different than for detection of a building, for instance. The UE may perform measurements of delay estimation until a certain value of SNR or range or delay is achieved or until a specific time. The UE may take only the samples that are above a certain SNR or associated threshold values of range etc. for a particular sensing task.

[0142] Performing measurements of angles, including AoA, A-AoA, may be specific to one or more RS, may be associated with one or more TRP, may relate to a RS that is received Line-of- Sight (LOS), may relate to a reflected RS from a particular one or more objects, may relate to one or more bounces of the reflected signals, etc. The task may further include detecting when e.g., an AoA, A-AoA falls within a certain range and / or is above / below certain thresholds, etc.

[0143] To perform measurements of single bounce and / or multiple bounce, the UE may be configured with a certain number of bounces and may be instructed to detect and / or record SNR, RSRP, etc. for those bounces. The UE may be configured to measure characteristics of each bounce separately and make comparisons between those characteristics. Examples of comparisons include measuring SNR, time of arrival, etc. of each bounce and determining the number of bounces that meet a certain SNR and / or time of arrival interval and / or that fall above / below certain thresholds.

[0144] Furthermore, errors may occur for Doppler, delay (micro-Doppler), angles or object characterization, if the propagation conditions or channel conditions are not favourable. LOS connection may or may not exist in Tx-Obj-Tx links or it may exist in one link but not the other, and attenuation and propagation loss may also be factors affecting sensing performance. This isalso linked to received SNR; SNR may be low for different reasons but received SNR will be lower due to propagation losses.

[0145] In all embodiments, the UE may be configured with a sensing task interruption timer, during which it should refrain from performing measurements over the received RS. The sensing task may have a start time and / or a stop time associated with it, under the form of an expiry timer, an explicit time indication, etc., explicitly, or implicitly signalled.

[0146] The UE may further be configured with latency requirements for the task. These can be indicated as, e.g., a specific maximum time to successfully complete the sensing task. The latency requirements may also include a plurality of maximum times to complete the sensing task, e.g., a first maximum completion time for angle related measurements, a second maximum completion time for Doppler related measurements, a third maximum completion time for delay related measurements, and so on. The latency requirements may be configured as absolute and / or interval values, to account for more complex sensing tasks. As an example, the latency requirement for angle related measurements may be x if the accuracy of Doppler related measurements has been achieved and y otherwise. Similarly, the latency requirement for angle-related measurements may be x if the SNR of the RS(s) is within a certain interval and y if the SNR lies outside of the interval, and z if the time difference of arrival of above / under certain thresholds.

[0147] The timing aspects may remain fixed during the sensing task or may be adjusted during an ongoing sensing task. The sensing task may also start by specific indication from the NW, or may be triggered by another condition such as, e.g., a SNR threshold for the sensing RS has been met, and / or the UE enters a certain geographical area, and / or the UL buffer at the UE falls under / above certain thresholds, and / or one or more measurements (e.g., LI and / or L3 measurements lie above / below a certain threshold), and / or a certain L2 related measurements lie above / below a certain threshold (e.g., number of re-transmissions), etc.

[0148] Sensing related measurements

[0149] In embodiments of the present principles, the UE performs sensing related measurements (e.g., Doppler, delay, angles, differentiation single vs multiple bounce from multipath components).

[0150] In the context of this present principles, a UE has the capability to perform sensing tasks, either as a receiver or a transmitter. The UE may be connected to one or more TRPs to perform sensing tasks. The UE is able to receive signals (for sensing purposes, e.g., reference signals such as PRS) and perform sensing-related measurements such as measuring delay, angles, TOA, Doppler, DL timing drift etc. and save these measurements, for example in an internal buffer.

[0151] The term ‘measurement’ may include direct and / or indirect measurements. This is because certain measurements are specific for sensing (e.g., Doppler shift), and others are derived from the sensing related measurements. As an example, DL Timing Drift measurement is specified in TS 38.215 that defines it as the DL timing estimated to be shifted due to Doppler over the service link associated with the UE Rx-Tx time difference measurement period.

[0152] Using this measurement as an example, the UE measures the Doppler of one or more RSs, estimates the Doppler shift, and finally estimates the DL Timing Drift, a measurement that derives from sensing related measurements.

[0153] Sensing related estimates

[0154] In the embodiments of the present principles, the UE determines, based on the above measurements, the estimates of delay, Doppler (and micro-Doppler), angles (AoA etc.) and / or single bounce vs multiple bounce from the sensing signals.

[0155] The estimates of each sensing metric such as Doppler, delay and angles may be performed by one of more estimators either provided to the UE by the NW or already implemented at the UE. For each metric, there may be one or more estimators to estimate the values of each metric. The estimator takes the channel impulse response of the sensing signal and passes through an estimator(s) for each metric.

[0156] UE measures the estimates of each metric such as Doppler, delay, angles, differentiation between single vs multiple bounce, or differentiation between objects based on their reflective properties. These estimates are measured from the sensing signals and sensing signal may be reference or pilot signals or any other signal for sensing purposes. This may be performed by the UE collecting samples from reference signals or any signal being used for sensing purposed, and using those samples, estimating the values of each metric. The estimated values may be passed through a function (the estimator(s)), either an individual function for each sensing metric or a single function that may differ from one metric to another. UE is able to determine the estimates of each of these metrics. The estimator(s) are assumed to be located at the UE for the performing of the estimation task. The estimator(s) may be UE vendor specific and left for UE implementation. The estimator(s) may be delivered to the UE by the NW, either upon request before and / or during an ongoing sensing task. The estimator(s) may be configured in the UE by the NW during the initial sensing task configuration. The estimator(s) may be delivered to the UE via UE assistance information. The estimator(s) may be delivered to the UE via an external OTT server, etc.

[0157] The usage of different estimators can be considered for the same and / or different metrics. For examples, the UE may use different estimators for one metric, where additional conditions may apply for estimator selection. For example, the UE may use estimatorl if the SNR is within acertain interval, and estimator2 otherwise. As another example, the UE may be configured to use estimatorl during a certain time period pertaining to the sensing task, and estimator2 otherwise. As another example, the UE may be configured to use estimatorl for AoA, and estimator2 for Doppler. As another example, the UE may be configured to use both estimators 1 and 2 for one or more of the observed sensing related samples, and choose the result obtained by the estimator that is closer in terms of its value to a ground truth value. The ground truth value is typically not available, and therefore can be an estimation in itself. This value may be computed by the UE and / or by the NW via its implementation and delivered to the UE in the latter case using any implicit and / explicit signalling. (It is noted that estimatorl and estimator2 are not necessarily the same between different examples.)

[0158] Reporting of sensing measurements

[0159] In addition to what the UE reports in the different embodiments, during and / or after the sensing task, the UE may be configured to report on sensing related measurements. For this purpose, the UE may be configured with different conditions to trigger a report on sensing related measurements. The report may be sent upon reception of an explicit indication from the NW, may be periodic, and / or may be based on certain events. The report may contain sensing related measurements, that can be further filtered by a certain past time window, current values, thresholds / intervals for SNR, time of arrival, specific bounce, reflections from a specific object, etc. All configuration aspects, e.g., thresholds / interval for different sensing related measurements can be considered for the definition of criteria to trigger this reporting. The triggering of this reporting is applicable to all embodiments of the present principles.

[0160] FIG. 2 illustrates a flow chart of a method of a first embodiment of the present principles, in which a UE reports to the network (NW) whether the accuracy of one or more sensing metrics is met.

[0161] In brief, the UE receives configuration information for an initial configuration for the sampling of sensing signals, receives information indicative of the sensing task requirements and thresholds of the metrics such as delay, Doppler and angles to measure and the accuracy of each metric, performs the sensing task and reports to the NW whether the accuracy of each metric is met or not.

[0162] In step S210, the UE receives from the NW configuration information and information indicative of trigger conditions. It is noted that the information can be received separately, for example at different times.

[0163] The configuration information is indicative of how to perform the sensing task, e.g., indication of a specific pilot signal, its time, frequency domain resources and the format of sensingsignals, etc. UE also receives time related configuration, e.g., for how long to perform a sensing task, etc. A more detailed description has already been provided in “Initial common solution components”.

[0164] The trigger conditions indicate when a report is to be generated and provided, for example when the desired accuracy is met. They can for example include thresholds for different sources of errors such as delay, Doppler, angles and single bounce vs multiple bounce, SNR mapping, etc. and / or time related criteria for the trigger, e.g., an observance time (“time to trigger”) during which the conditions must be observed and during which sensing will be available, which can further be associated with a confidence level of the observed samples. A more detailed description is provided hereinafter.

[0165] In step S220, the UE performs sensing related measurements, e.g., Doppler, delay, angles, differentiation single vs multiple bounce from multipath components. A more detailed description has already been provided in “Initial common solution components”.

[0166] In step S230, the UE determines, based on the above measurements, the estimates of the metrics, for example delay, Doppler (and micro-Doppler), angles (AoA etc.) and single bounce vs multiple bounce from the sensing signals. A more detailed description has already been provided in “Initial common solution components”.

[0167] In step S240, the UE determines whether the desired accuracy of one or more sensing- related metric(s) has been met, e.g., based on the above measurements, received SNR, and the configuration. A more detailed description is provided hereinafter.

[0168] The accuracy of delay, Doppler (micro-Doppler), angles (A-AoA, Z-AoA) may be determined from the confidence level for each metric against pre-configured threshold values for each metric. As an example, a threshold for the delay can be 10% of the OFDM symbol length, and if the delay measured by the UE falls below this threshold, during a certain time to trigger, with a certain associated confidence, then e.g., the resolution for range (in this example the accuracy of the overall sensing task) may be considered fulfilled. The accuracy may also be measured, e.g., from the Root Mean Square Error (RMSE) values for each metric. The accuracy may also be measured, e.g., from the CRLB (known to the receiver) for each metric vs SNR.

[0169] When at least one trigger condition is met, in step S250, the UE transmits an indication to the NW on whether the desired accuracy of one or more measurement(s) has been met or not (or e.g., an accuracy percentile has been achieved), where the specific target metric (e.g., Doppler, DL Timing Drift) may be included. A more detailed description is provided hereinafter.

[0170] Turning back to the trigger information mentioned with reference to step S210, in this step, the UE is configured with thresholds that account for the metrics that could negativelyinfluence the sensing task. The objective is for the UE to trigger transmission of an indication to the NW (in step S250), to make the NW aware that the accuracy of the overall sensing task has been achieved. The indication may however be sent as well if the accuracy of only one or more metrics configurated (i.e., a subset) has been achieved. Additional information may be added to this indication, as will be further described with reference to step S250.

[0171] A number of different error sources (at least some of which have already been described) are identified and commonly recognized and addressed in the research community that may contribute negatively to a sensing task: timing and frequency errors (delay errors), Doppler shift and velocity errors, antenna directivity and gains errors, angle estimation errors, SNR issues, propagation and attenuation effects, micro-Doppler errors, errors in identification of single bounce vs multiple bounce signals, characterization of objects with different material, e.g. with RCS or reflection properties. These errors sources / metrics are addressed hereafter, but it will be appreciated that that additional metrics may be identified in the future and / or measured with different metrics, where in that case the configuration examples below should follow similar principles.

[0172] As already mentioned, the overall sensing task may be comprised of a combination of different measurements. The UE may report on the accuracy of the overall sensing task being met, or it can report on the accuracy being met for one or more of the configured metrics and corresponding error that negatively impact the sensing task. The conditions configured at the UE are applicable to sensing related samples measured from one or more sensing signals, and / or to estimates of the observed samples.

[0173] The reporting of an individual accuracy or of more than one accuracy for the metrics may be associated with a “time to trigger” or an observation period, where the accuracy of the one or more metrics is only considered met if the accuracy thresholds of the one or more metrics are observed during the “time to trigger”. In different embodiments, the “time to trigger” may be an implicit or explicit time indication during which another L1 / L2 / L3 measurement threshold and / or range criterion is met (e g., a Ll-RSRP, a DL PRS-RSRP, a DL Timing Drift, a DL RSTD, a SL- AoA, a number of retransmissions or an UL buffer threshold / range, a L3-RSRP, a L3-SNR, etc., where these measurements may relate to the one or more sensing signals emitted for the purpose of the sensing task, or may relate to other pilot signals, e.g., RSRP from another CSI-RS that is not being used for the purpose of sensing, etc.). In other embodiments, the UE may determine that the reporting criteria is met if one sample of any sensing related measurement meets the defined thresholds / interval. In other embodiments, a plurality of samples may be considered for the determination. In other embodiments, one or more samples are considered when assessed togetherwith other conditions, e.g., the SNR of those samples being above / under thresholds, and / or within a certain interval, and / or the TDoA of those samples, and / or the AoA of those samples, etc. In other embodiments, the UE may be configured with a prohibit timer, that can be used in the same manner as a time to trigger, but in this case the timer would start counting once one or more sensing related samples meet the configured criteria, and would trigger the report on expiry, since one or more samples meet the configured thresholds / interval.

[0174] The reporting of an individual accuracy or more than one accuracy for the metrics may further be associated with a confidence and / or error value(s). The confidence / error relates to sensing related samples and may be applicable to sensing samples and / or estimated samples, and / or a sensing result, e.g., DL Timing Drift. Because sensing is, at its core, an estimation problem, the confidence / error of sensing related measurements may also be determined in different ways.

[0175] Examples of errors include timing and frequency errors (delay errors), Doppler shift and velocity errors, antenna directivity and gains errors, angle estimation errors, SNR issues, propagation and attenuation effects, micro-Doppler errors, single bounce vs multiple bounce signals, and characterization of objects with different material or shape.

[0176] For example, a threshold for the delay might be 10% of OFDM symbol length, and if the UE measured delay falls below that threshold, during a certain time to trigger, with a certain associated confidence or integrity, then the accuracy / re solution for range may be considered fulfilled. The threshold for range may also be an absolute threshold. In this case, a delay threshold of X nanoseconds, for example, could be defined to achieve a certain resolution (e.g., 100 meters) required for the ongoing sensing task. As an example, another threshold for range could be spatial resolution threshold. The system can distinguish between targets separated by a distance equal to or greater than the specified spatial resolution. Spatial resolution is related to the ability to separate two targets along the radar line of sight. The delay threshold may be defined in terms of maximum expected propagation time. This means that targets with delays less than a specified threshold are considered to be resolvable with a certain confidence or integrity value(s).

[0177] Similarly, velocity thresholds are related to Doppler estimation, and velocity threshold may be defined in terms of an absolute Doppler frequency threshold. For example, a Doppler threshold of 100 Hz means that targets with Doppler frequencies less than 100 Hz can be reliably detected and resolved. Accuracy will be measured in terms of reliability and resolution. As another example, a radar system with dynamic range of 50 dB means that the system can detect and resolve targets with Doppler frequencies differing by 50 dB. Moreover, a threshold may be defined in terms of Doppler resolution. For example, 2 Hz of Doppler resolution threshold would mean thatthe system can distinguish targets whose Doppler frequencies differ by 2 Hz. The Doppler threshold may also be defined corresponding to system’s frequency spread; for example, 50 Hz means that targets with Doppler separation of at least 50 Hz can be resolved with good accuracy. In the same way, micro-Doppler thresholds may be defined differently than Doppler and they may be more or less strict than Doppler depending on the use case. Micro-Doppler, unlike Doppler, focuses on modulation caused by micro movements at a finer scale of target components and movement within the target. Therefore, this frequency modulation threshold may be defined for micro-Doppler, for instance 10 Hz. Moreover, as an example, another threshold may be defined for modulation BW threshold, for instance 30 Hz, which means that the system can distinguish between micro-Doppler signatures with modulation BW wider than 30 Hz. In terms of reporting, micro-Doppler signatures may be reported to the NW in step S250.

[0178] In the same way, angular thresholds may also be defined in different ways. For example, a beam width threshold may be defined with a 1 -degree angular resolution. This means that targets located in different directions separated by at least 1 degree can be resolved or distinguished. In the same way, angular resolution could be a percentage of the beamwidth. Angular resolution thresholds may also be defined in terms of azimuth and elevation. For example, a 1 -degree threshold in this case means that the system can resolve targets with angular difference in azimuth or elevation of at least 1 degree. Moreover, angular resolution may be defined relative to the system’s field of view (FOV). For example, a 3-degree threshold here means that targets outside the FOV or separated by angles greater than 3 degrees may be resolved with a certain confidence or integrity.

[0179] An important parameter to characterize an object is RCS. The RCS depends on one or more of the shape, material properties and orientation of an object. Therefore, different threshold values or configurations may be determined. Object orientation may be unimportant in some cases, and it may then be ignored. A RCS threshold may be defined, e.g., in terms of dB square meter (dBsm), and this value can be configured as threshold for accuracy of the object characterization. For example, with a 15 dBsm threshold value, objects below this threshold may be considered not observable or stealthy. Objects outside the configured shape and size may be ignored, and the NW can define those threshold values. The RCS threshold may be a combination of different RCS characteristics and a combination of those characteristics may be classified as a different object. For example, RCS of a traffic signal on a road may be the combination of RCS of circles and RCS of a cylindrical pole.

[0180] Similarly, errors may occur due to a single bounce off the target or due to multiple bounces off the target, or any other surface for example. The UE may be able to determine whetherthe multipath component results from single bounce or multiple bounce. This determination may be important for certain use cases and may affect the accuracy of the sensing metrics and overall sensing task accuracy. Whether this is important for a particular sensing task or not may be configured by the NW or the UE may consider such a determination on its own to calculate the accuracy of each metric. The UE may report this determination to the NW in step S250.

[0181] In step S240, the UE determines for one or more of the metrics if the accuracy has been met. The UE may also determine additional information that can be useful to report to the NW related to individual and / or more metrics. Examples of this information include sensing related samples, estimated samples, and sensing results.

[0182] In one embodiment, the UE may determine the number of samples that met the configured criteria for one or more metric such as delay, Doppler, angles, etc. The determination may consider a specific time window, samples with an SNR and / or aggregate SNR (power density) above / under thresholds. As an example, the UE may determine the number of samples that met the configured criteria from the moment when the first sample met the configured criteria and adding only samples that had their recorded SNR higher than a threshold, while excluding samples whose SNR was below the threshold.

[0183] In one embodiment, the UE determines statistical properties of the samples that met the configured criteria. This can include averaging of the samples and / or their recorded SNR, max / min values, increase / decrease rates of the samples, etc. These determinations can also be segmented to consider a specific time window only, specific SNR thresholds / intervals for the considered samples, etc. As an example, the UE may determine that during the sensing task, a number x of samples / estimates of Doppler shift have recorded a max increase rate of r during time window [e;i], that a total of y samples were considered during that period, and that z samples were considered to determine the max increase rate, due to z being the number of estimates that recorded above / below a certain SNR threshold, or were within an SNR interval. The rate of change of Doppler shift may be defined relative to Doppler thresholds examples given in step S210.

[0184] In one embodiment, the UE determines time-related aspects for the metrics and their status during the sensing task. This can include determining a plurality of time windows where the sensing related samples / estimates / results have performed according to the received configuration. Examples include time windows were e.g., the angular samples have been determined to be within a certain interval and / or above / under certain thresholds. It can include time windows were e.g., the angular samples recorded an increase rate above / below a certain threshold. The same applies to all sensing related samples, estimated samples, and sensing results. The UE may be configured tomake this determination for one or more of the metrics. The UE may determine the average time a metric performs above / under certain thresholds.

[0185] In one embodiment, the UE determines aspects related to CRLB. This can include the UE being configured with CRLB for a metric and determining based on all and / or a subset of the sensing measurements that a new CRLB is more adequate. The UE may determine the difference between the initial and the newly determined CRLB. The UE may also make these determinations based on further filtering of sensing related samples based on SNR thresholds / interval, and / or time intervals, as in previous examples. The UE may determine a new CRLB that represents a lower performance than the currently available CRLB. In this case, the UE may further determine an error indication related to the fact that the initial CRLB boundaries may not be met. The UE may make these determinations via assessment of the SNR of one or more of the samples / estimates / results, via power density (e.g., aggregated SNR), etc.

[0186] In one embodiment, the UE determines information related to the status of the ongoing sensing task and that may pertain to one or more of the metrics. This may include determining a percentage of the estimated completion of the accuracy of one or more metrics. In another embodiment, the UE determines information related to the status of an ongoing sensing metric. In another embodiment, the UE determines information related to the status of a metric. In another embodiment, the UE determines information related to the status of a plurality of metrics.

[0187] In step S250, when the reporting criteria are met, the UE sends an indication to the NW on whether the desired accuracy of one or more measurement(s) has been met or not. The indication may include any of the additional information detailed with reference to step S240. The indication / report may be sent using signaling pertaining to any layer, e.g., RRC, MAC CE, UCI, etc.

[0188] FIG. 3 illustrates a flow chart of a method of a first embodiment of the present principles, in which the UE reports on the contribution of metrics for a sensing task.

[0189] In brief, the UE receives information for an initial configuration for sampling of sensing signals, sensing task requirements and thresholds of delay, Doppler and angles to measure accuracy of each metric. While the sensing task is ongoing, the UE reports to the NW on metrics and values related to the metrics, and their contributions to the overall sensing task.

[0190] In step S310, the UE receives from the network configuration information and information indicative of trigger conditions. It is noted that the information can be received separately, for example at different times.

[0191] The configuration information is indicative of how to perform the sensing task, e.g., indication of a specific pilot signal, its time, frequency domain resources and the format of sensingsignals, etc. UE also receives time related configuration, e.g., for how long to perform a sensing task, when to report sensing related measurements, etc. A more detailed description has already been provided in “Initial common solution components”.

[0192] The trigger conditions indicate in what circumstances a failure report (e.g., the NW configures threshold values for one or more metrices, i.e., Doppler, delay, angles, and / or weightage of each metric to the overall accuracy of the sensing task) is to be sent by the UE to the network.

[0193] In step S320, the UE performs sensing related measurements (e.g., Doppler, delay, angles, differentiation single vs multiple bounce from multipath components). A more detailed description has already been provided in “Initial common solution components”.

[0194] In step S330, the UE determines, based on the above measurements, the estimates of delay, Doppler (and micro-Doppler), angles (AoA) and single bounce vs multiple bounce from the sensing signals. A more detailed description has already been provided in “Initial common solution components”.

[0195] In step S340, the UE determines the contributions of each metric to the overall accuracy of the sensing task, based on past / current sensing measurements and the received configuration.

[0196] The contribution of Doppler / angular / delay metrics is computed by executing a function that can reside on the UE and that requires Doppler / angular / delay samples over time as input. If this function resides at the UE, this embodiment serves to indicate to the NW the contributions of each metric to the overall accuracy of the sensing task.

[0197] The function may be a single function with estimates of each metric as input along with SNR or any other parameter, or, in the case of the third embodiment (as will be seen) a set of functions, including one or more functions for each metric.

[0198] When at least one trigger condition is met, in step S350, the UE transmits information indicative of a failure report to the NW, including one or more contributions of one or more metrics, that can include one or more measurements, i.e., estimates of delay, Doppler (including micro-Doppler), angles, single bounce vs multiple bounce differentiation and SNR.

[0199] Turning back to the trigger information mentioned with reference to step S310, the UE receives information indicative of a configuration that may enable the UE to send a failure report to the NW. The purpose of the failure report is to help the NW better to understand underlying problems with an ongoing sensing task. This can be particularly important if the sensing task includes a configuration on several metrics, and at least one of those metrics negatively impacts the sensing task. The function that is capable of computing the contribution of each metric may output the contribution of the errors in different ways, as indicated in examples hereafter.

[0200] In an embodiment, the function outputs the accuracy / resolution / integrity of one or more metrics. In this case, the UE may rely on the initial sensing task configuration for the conditions that define the accuracy / resolution / integrity are met or not. The UE may also receive similar thresholds (e.g., soft thresholds), to trigger reporting of the failure report, where the accuracy / resolution / integrity can be expressed as an absolute value, a percentage, an x% confidence interval, etc. The accuracy / resolution / integrity may also be estimated leveraging on statistical properties, e.g., mean estimation, moving average estimation, weighted average estimation, weighted moving average estimation, a probability distribution function modelled by its intrinsic parameters, etc., where in the latter case the function parameters are used to assess that the accuracy / resolution / integrity of the sensing metrics is not being met.

[0201] In an embodiment, the function outputs the uncertainty range of the sensing related measurements. An uncertainty range defines an interval within which a numerical result is expected to lie within a specified level of confidence. The interval often used is the 5-95 percentile of the distribution reporting the uncertainty. In this case, the UE may rely on additional configuration to determine an uncertainty range. The UE may also receive thresholds similar to the sensing task configuration (e.g., soft thresholds), to trigger reporting of the failure report, where the uncertainty range can be expressed as an absolute interval, an x% confidence interval, an indication via a lookup table that maps an index with uncertainty ranges, a binary representation (e.g., zero if uncertainty between 5% and 45%, and 1 if above 45%), etc.

[0202] In an embodiment, the function outputs sensing related measurements for one or more metrics. In this case, the function outputs information related to the samples that are problematic for each of the metric (see the first embodiment, step S240.

[0203] In an embodiment, the function outputs sensing task requirement updates. In this case, because the UE cannot achieve the accuracy of the sensing metrics based on the current measurements and estimates of metrics (Doppler / delay / angles, etc.), the function may output suggestions for an update to the sensing task requirements. This can be achieved in a multitude of ways. As an example, if the accuracy of the sensing task comprises measurements of all Doppler, delays, angles, and the UE determines, given the sensing task configuration, that the accuracy for Doppler and delay is met but the angles being measured are not within the configured criteria, the function may determine new requirements for the sensing task. This can take different forms. The function may suggest, in some embodiments, an increase in the rate or percentage of false alarms, and / or decrease the accuracy requirement for the angle measurements (e.g., lowering its percentage). In some embodiments, the function may suggest an increase in the latency requirement of the sensing task (i.e., suggest more time for it to be completed). In someembodiments, the function may suggest a reduction of the configured confidence levels. In some embodiments, the function may suggest more relaxed thresholds for a position and / or velocity estimate task (e.g., decrease the required accuracy of one or more metrics). In some embodiments, the function may suggest a decrease in the sensing resolution requirement (e.g., decrease the velocity resolution). In some embodiments, the function may suggest a decrease in the missed detection requirement. All the above represent outputs of the function if the function is tailored to update sensing task requirements. It is worth pointing out that the function may output one or more of the examples provided, e.g., increase the latency requirement of the sensing task, while decreasing accuracy thresholds for Doppler, while increasing the false alarm detection requirement.

[0204] In an embodiment, the function outputs unknown or correlated sources of error: Some correlations between metrics are known (see the description of the first embodiment), but the NW does not have this information. For example, velocity estimation is linked to both Doppler and range measurements. Sometimes it may only be estimated using Doppler, but at other times range estimation may provide extra accuracy or information. In some cases, velocity estimation is not directly linked to AoA, for example, but AoA together with velocity estimation can provide better tracking of a specific target. To account for these cases, the function may also output estimates of the correlations between metrics. The correlations may be multi-dimensional, i.e., errors due to propagation can affect SNR, that in turn has an effect on the angle measurements, as an example. Another example is that the delay recorded may have an impact on accurate Doppler shift assessment, and that may originally be caused by the AoA of one or more sensing signals. The function may therefore output a tuple where a weight is assigned to each metric that is contributing negatively to the sensing task accuracy, or for the accuracy of one or more metrics.

[0205] An example of a tuple with an example weight assignment is <Timing and frequency errors (delay errors), Doppler shift and velocity errors, Antenna directivity and gains errors, Angle estimation errors, SNR issues, Propagation and attenuation effects, Micro-Doppler errors, Single bounce vs multiple bounce signals, characterization of objects with different material> = <20%, 15%, 2%, 10%, 30%, 5%, 0%, 0%, 18%>.

[0206] The UE may further be configured to exclude weight assignments that are above / below certain thresholds. For example, the NW may only be interested in knowing which contributors mark above / below e.g., a certain percentage, and / or specific one or more contributors (that can be signaled implicitly or explicitly), and / or the main contributor, etc.

[0207] The UE may further be configured to filter the inputs to the function in a similar way as in other embodiments, where, for example, the UE may be configured with additional SNRthresholds, where the inputs considered may be within a certain interval if the SNR is above / below threshold(s), and within another interval if not. In other embodiments, the UE may only compute the function with inputs where the SNR is above / below certain thresholds, or within an interval, etc.

[0208] The UE may determine a similar tuple where the weights assigned to each element of the tuple pertain to configuration suggestions that can help mitigating the problem with one or more metrics. As an example, Doppler related errors are better mitigated by an increase in sensing signals while angular measurements may be more trustworthy if SNR is better, and in the same way, the BW might need to be increased in time to mitigate range-related errors or more symbols with shorter duration may be required. The shorter duration symbols may be sent by increasing the subcarrier spacing for example. For one or more of the metrics, the function may output a weight assigned to configuration aspects that could be improved. For example, the function may output the weightage of time slots / symbols and BW, {BW, time} — > {0.3, 0.7}.

[0209] The function may also output the probability distribution function with probabilities associated to each metric and report only metrics that are above a certain probability threshold, for example 0.07.

[0210] The BW can be further linked to a preconfigured BW part, can be a range in frequency, a number of subcarriers, etc. Time can be represented in terms of absolute time, number of slots / frames, symbol length, etc. SNR may be expressed in terms of average SNR from all samples, power density, etc.

[0211] The function may also output, in addition to the examples provided, suggestions for the next reporting occasion. This can be useful to optimize reporting and feasible because, based on past sensing related samples / measurements and their evolution, the function may estimate when the next time would be such that a meaningful change would occur. The meaningful change may be, e.g., a delta to the current weight in the tuple. In some embodiments, the UE may constantly assess the function output and trigger the report when the meaningful change happens. This suggestion can be represented by a time, a number of slots, and / or a number of frames, etc.

[0212] FIG. 4 illustrates a flowchart of a method according to a third embodiment of the present principles, in which the UE determines and reports on the function that best estimates the contribution and / or the function that provides better accuracy for a metric.

[0213] In the method of the second embodiment, the contribution of metrics, for example Doppler, angular and delay, is computed by executing a function that requires samples (Doppler / angular / delay...) over time as input. There may be multiple functions that are able to compute the error contribution, and each function estimates better depending on the type of object,speed, material, the metric itself, etc. The UE can report to the NW the function that best estimates the contribution of a metric and / or the function that provides better accuracy. This can be achieved by the UE computing the contribution and / or accuracy for a number of Doppler / angular / delay samples using the multiple functions, and reporting the function that for example yields the highest accuracy. This implicitly tells the NW how to frame the status of the sensing task at the UE and helps deciding on different resource allocation.

[0214] In brief, the UE receives information indicative of an initial configuration for sampling of sensing signals, the sensing task requirements and thresholds of delay, Doppler and angles to measure accuracy of each metric, and a configuration for best function determination, from a pool of functions that can compute the contribution and / or accuracy for a number of Doppler / angular / delay samples. The UE then executes the set of functions, determines and indicates to the NW the best performing function.

[0215] In step S410, the UE indicates to the network its capability to determine, using a pool of functions (including at least one function) the contribution and / or accuracy for a number of Doppler / angular / delay samples.

[0216] The pool of functions may be part of the UE’s implementation and / or may delivered by the NW upon UE request, upon configuration of a sensing task, upon NW triggered transfer at any point in time, etc. Because this embodiment deals with a set of functions, there may be a need to indicate to the NW that the UE has this capability, and which functions are available. The UE may send an indication to the NW (e.g., via RRC, MAC CE and / or UCI) of the capabilities of one or more functions already described with reference to step S310 of the second embodiment. The UE can indicate all of its functions. The UE can indicate a subset of its functions, based on, e.g., an ongoing sensing task. In this case, the sensing task configuration (e.g., measurement of a AoA) may make the UE indicate functions capable of computing the contribution of errors to that angle measurement. The UE can indicate the capability with explicit function identifiers. The UE can indicate functions IDs that can be linked to e.g., a lookup table, etc.

[0217] In step S420, the UE receives from the network configuration information for how to perform the sensing task and information indicative of a configuration for determining one or more functions.

[0218] The configuration information is indicative of how to perform the sensing task, e.g., indication of a specific pilot signal, its time, frequency domain resources and the format of sensing signals, etc. The UE also receives time related configuration, e.g., for how long to perform a sensing task, when to report sensing related measurements, etc. A more detailed description has already been provided in “Initial common solution components”.

[0219] The information indicative of a configuration for determining one or more functions enables the UE to determine, from the pool of function(s), one or more functions that are capable of determining the contribution and / or accuracy for a number of Doppler / angular / delay samples, the one or more functions that best describe the error contributions (functions may be vendor / operator supplied and can be sectorized by e.g., SNR and / or computational delay).

[0220] It will be understood that the UE is configured with a set of function(s) that can be vendor or operator supplied, and / or based on UE request (for example, if the UE did not succeed to select from the predefined functions any function that matches the requirements, then the UE may request another pool of functions or even another type of functions to search in a better space for functions that better describe the error contributions), and / or based on NW configuration that may deliver this and may be subject to UE capabilities and computational power. Different functions may be used: continuous functions (e.g., Identity functions, Constant functions, polynomial functions, quadratic functions, cubic functions, etc.), or non-continuous functions (e.g., rational functions, modulus functions, Dirichlet functions, step functions, piecewise-defined functions). A combination of one or more of these sets of functions can form a pool of functions from which can be selected ones that are suitable for describing the error contributions. By enriching this pool, the probability to reach the ideal function representation will typically increase but with the trade-off with increased searching complexity. It is worth noting that, by enabling piecewise functions this gives additional level of control in terms of complexity and accuracy where, the more parameters are defined or included to the piecewise function, the closer the function will be to the truth or to the ideal representation of the samples. Furthermore, it is possible to use a combination of simple functions (e.g., linear functions) that each can be mapped to a segment or sector as shown in FIG. 5, where ax, bx, and ex are functions that each approximates the RMSE function in a different range of SNR called sector / segment, and a, b and c are constants to search for. FIG. 5 illustrates example segmentation and application of three linear piece-wise functions, to a function that maps SNR of sensing-related samples to the RMSE of a target metric. It is worth noting that if the derivation of the function is required, then non-continuous functions will not be suitable.

[0221] The UE may be configured to apply only a subset of the functions based on, e.g., SNR and / or computational delays. This includes selecting a subset of the functions in case the SNR of one or more sensing samples falls above / below and / or within a certain SNR threshold / interval. The SNR segmentation may further be associated with time intervals, where e.g., the UE determines a subset of functions given the SNR meets the configured criteria for a specific amount of time, a specific number of samples, a certain average SNR, etc.

[0222] Similarly, the UE may be configured to select the subset of functions based on the computational delay of one or more of the functions. This is important to note, especially in cases where the latency requirements for the sensing task are strict, and because the computational delay of each function may be known, but it is also a function of the current CPU usage at the UE. Thresholds for computational delay may be configured at the UE, in the form of a maximum time, a maximum CPU load, maximum power spent in computing the function, etc.

[0223] In step S430, the UE performs sensing-related measurements, e.g., Doppler, delay, angles, differentiation single vs multiple bounce from multipath components. A more detailed description has already been provided in “Initial common solution components”.

[0224] In step S440, the UE determines, based on the sensing-related measurements, estimates of delay, Doppler (and micro-Doppler), angles (AoA) and single bounce vs multiple bounce from the sensing signals. A more detailed description has already been provided in “Initial common solution components”.

[0225] In step S450, the UE determines a set of functions to execute based on at least one characteristic, for example the SNR, of one or more sensing samples and / or the computational delay of the set of functions.

[0226] The functions to execute may be selected based on SNR or computational delay or both, as illustrated in FIG. 6, and the selection is not limited to these factors. For example, the UE may search for functions that satisfy one of the factors at a time, e.g., first the SNR and then the computational delay. It is possible to have scenarios where no common functions exist (i.e., functions that satisfy both the SNR and the computational delay at the same time), and in that case the subset of the functions will be null. In this case, the UE might ask for a new pool of functions, the UE might request to relax the SNR / computational delay constraints, and / or the UE might do the selection based on one of the factors (the NW may pre-emptively indicate which factor beforehand, pre-empting a null subset of functions). As the conditions or factors increases in combinations the probability to find a function that satisfies all of them will decrease and the searching complexity will decrease since there are less functions to choose from.

[0227] FIG. 6 illustrates a Venn diagram with an initial set of functions, and subsets of functions that meet the SNR criteria, the computational delay criteria, or both.

[0228] The UE may be defined with different searching algorithms that may comprise different sets of parameters that can be UE-based or NW-based. Examples of parameters that can affect the complexity of the searching algorithm include the number of functions (once this is reached, the searching algorithm may terminate) and / or a defined searching time window, and / or a defined number of epochs, and / or a defined number of iterations and / or number of steps.

[0229] The computational delay will typically differ from one applied function to another, for example, executing a linear function or a constant function typically requires less computational power and time compared to cubic or polynomial functions or even non-linear functions. In that case, this will affect the sensing samples that may be considered. For example, within duration T = 10 ms, considering a function that requires 2 ms per input sample, then 5 samples will be processed. For another function with computational time of 5 ms per input sample, then only 2 samples would be processed. In that case, the NW must be also aware about the number of samples or the computational delay for each function per sample or the average or any statistical representation. The UE may transmit this additional information (i.e., the number of samples it was able to process and in how much time), in step S460.

[0230] In step S460, the UE can indicate the determined set of functions to the NW and can additionally include the measured SNR for one or more sensing samples.

[0231] The selected subset of functions may be indicated and reported in different ways, for example, via an explicit ID indication, and / or an index that can be linked to a look-up table, etc. The UE may, as mentioned, further include SNR related information, like average SNR of the samples, SNR of each sample, etc., and / or computational delay information, e.g., computational time, number of samples processed, the metric to which the information pertains to, etc.

[0232] In step S470, the UE executes the determined set of functions to compute the contribution and / or accuracy for a number of Doppler / angular / delay samples. This has already been described with reference to step S310 of the second embodiment.

[0233] In step S480, the UE determines the ‘best’ function(s), that is the function that e.g., yields the highest accuracy (or lowest RMSE), for one or more metrics.

[0234] The UE may determine one or more functions for each defined metric or KPI (accuracy, RMSE, etc.) to maximize / minimize / trade-off based on one or more metrics and / or different computations and measurements (e.g., complexity, computational delay, etc.). This can be achieved by executing the previously determined subset of functions internally and comparing the scores of each function in terms of e.g., the function(s) that yields the highest accuracy, and / or the function(s) that yields the lowest RMSE, for one or more of the metrics.

[0235] In step S490, the UE indicates the determined one or more ‘best’ function(s) to the NW, where additional information can be added, like the number of sensing samples used, the SNR profile, computational processing delay information, etc.

[0236] The UE can report the ‘best’ performing function(s) to the NW, e.g., via RRC, MAC CE and / or UCI. Additional information can be sent along with the functions, as described with reference to step S460.

[0237] FIG. 7 illustrates a flow chart of a method according to a fourth embodiment of the present principles in which the UE sends to the NW a compressed representation of samples (e.g., Doppler / angular / delay) and the associated SNR for NW-sided computation of metric contributions.

[0238] The contribution of Doppler / angular / delay etc. metrics in in the third embodiment is computed by executing a function that requires Doppler / angular / delay samples over time as input. If this function resides at the NW, the UE needs to report the Doppler / angular / delay samples, which can increase overhead in the air interface due to large numbers of samples that need to be reported. This embodiment serves to indicate to the NW a function that fits a number of Doppler / angular / delay samples, so the NW can execute that function to generate the inputs required to compute the contributions of each metric to the overall accuracy of the sensing task.

[0239] In brief, the UE receives information indicative of an initial configuration for sampling of sensing signals. Information indicative of the sensing task requirements and thresholds of delay, Doppler and angles to measure the accuracy of each metric. The UE further receives information indicative of a configuration for a certain number of samples or past observation window for fitting of a function. The UE then determines what is the function that best fits the samples, and reports that function to the NW. The UE can fit and report an additional function that best fits to the SNR of each of the samples during the observation window.

[0240] In step S710, the UE receives from the network configuration information and information indicative of an observation time window.

[0241] The configuration information is indicative of how to perform the sensing task (e.g., indication of a specific pilot signal, its time, frequency domain resources and the format of sensing signals, etc. UE also receives time related configuration, e.g., for how long to perform a sensing task, when to report sensing related measurements, etc.). A more detailed description has already been provided in “Initial common solution components”.

[0242] The observation time window indicates the time window for the fitting of Doppler / angular / delay samples and the SNR values associated with these samples, e.g., a time window to consider for samples to calculate the estimates of Doppler / angular / delay and / or SNR thresholds for filtering of the samples, e.g., the observation window can be defined by the time that comprises samples within a certain SNR interval.

[0243] It will be appreciated that samples of sensing related measurements may create huge data volumes. As an example, the UE may be configured by the sensing task to create a 3D function of a Doppler-delay map. As another simpler example, the UE may be configured to estimate angle measurements over time. Regardless of the sensing task and / metric(s) considered, the function thatcomputes the contribution of a metric may require a large number of input samples. If the function resides at the NW, a function determination procedure may be required for signaling overhead reduction. It is assumed that the most interesting case for the UE to report on samples of sensing related measurements is when the accuracy of one or more metrics has not been met, but data collection for successful cases is not precluded.

[0244] The UE may be configured with an observation time window to consider the input samples, e.g., a time window, where the input samples may be raw sensing related measurements, estimates, and / or sensing results (e.g., DL Timing Drift). The window may further consider e.g., SNR thresholds and / or an interval, for filtering of the samples. As an example, the UE may consider only a subset of samples that are above / below certain SNR thresholds, further filtering the input samples. If the UE is configured with such a filtering technique, the samples may further be aggregated in two ways. The UE can disregard samples above / below an SNR threshold, and keeps the timestamp of those samples, creating a first function. The UE can also disregard samples above / below an SNR threshold but aggregate the samples using a pre-defined granularity, creating a second function. The granularity may be part of the initial configuration, vendor pre-defined, delivered to the UE before or during the sensing task, etc.

[0245] In step S720, the UE performs sensing related measurements, e.g., Doppler, delay, angles, differentiation single vs multiple bounce from multipath components. A more detailed description has already been provided in “Initial common solution components”.

[0246] In step S730, the UE determines, based on the above measurements, the estimates of metrics, for example delay, Doppler (and micro-Doppler), angles (AoA) and single bounce vs multiple bounce from the sensing signals. A more detailed description has already been provided in “Initial common solution components”.

[0247] In step S740, the UE determines a function that ‘best’ fits the (Doppler / angular / delay) samples, e.g., by executing a mathematical fitting procedure, or by determining from a certain function type (e.g., exponential, polynomial, 3D function, piecewise function etc.), the parameters that best define the fitted function, for example by providing the highest or lowest comparison value such as least-mean-square or. This may also be determined by AI / ML methods or statistical methods. There may be more than one function, one respectively for different regions or values of SNR.

[0248] Different functions may be used, for example continuous functions (e.g., Identity functions, Constant functions, polynomial functions, quadratic functions, cubic functions, etc.), or non-continuous functions (e.g., rational functions, modulus functions, Dirichlet functions, step functions, piecewise-defined functions). The UE may perform the fitting procedure based on itsimplementation or it may be configured to use one or more types of functions and determine the parameters that define them. As an example, the 3D function that best describes the samples may follow a specific 3D function profile, for which the UE determines the parameters that define that 3D function, after fitting the sampled values. As another example, the function that best describes the samples may be a polynomial function, and the UE may determine the full function equation, and / or the polynomial parameters that define it, given that it was instructed to use a polynomial type function.

[0249] In step S750, the UE determines a function that best fits the SNR of the Doppler / angular / delay samples, e.g., by aggregating samples and averaging the individual SNR of each sample, etc.

[0250] The determination can rely on samples of a sensing-related measurement over time. Even though the samples may be segmented by e.g., SNR, the determination can only provide a timehorizon based representation.

[0251] FIG. 8 depicts three examples of how a function can be fitted to the SNR values over time.

[0252] The example SNR fitting procedures have different observation windows. The left diagram illustrates average SNR of Doppler over time, the middle diagram average SNR of delay over time, and the right diagram average SNR of AoA over time.

[0253] In step S760, the UE transmits to the NW an indication of the determined functions that best fit Doppler / angular / delay samples, and their recorded SNR, where the UE can additionally include e.g., statistical properties associated to the functions such as mean, standard deviation, polynomial, etc.

[0254] The UE can transmit indexes for functions, and / or function parameters that can represent the functions, etc., where additional statistical properties could be included. Examples of additional information include, e.g., statistical properties associated to the functions such as mean, and / or standard deviation of the samples, etc. The additional statistical properties may refer to all the samples, or to a subset of them (e.g., filtered by SNR), min / max deviation, etc.

[0255] FIG. 9 illustrates a flow chart of a method according to a fifth embodiment of the present principles in which the UE recommends a preferred configuration to meet the requirements of both communications and sensing tasks.

[0256] Indicating to the NW a better configuration for the sensing task, e.g., a sensing signal with higher BW, can increase the probability of a successful overall sensing task.

[0257] In brief, the UE information indicative of an initial configuration for sampling of sensing signals, the sensing task requirements and thresholds of delay, Doppler and angles to measureaccuracy of each metric. The UE also receives QoS and latency requirements. Based on the measurements taken in terms of SNR, delay, Doppler, angles, the UE determines a new configuration that may achieve the target accuracy of the sensing task and reports the suggested configuration.

[0258] In step S910, the UE receives from the network configuration information and information indicative of conditions.

[0259] The configuration information is indicative of how to perform the sensing task (e.g., indication of a specific pilot signal, its time, frequency domain resources and the format of sensing signals, etc. UE also receives time related configuration, e.g., for how long to perform a sensing task, when to report sensing related measurements, etc.). A more detailed description has already been provided in “Initial common solution components”.

[0260] The information indicative of conditions enables to determine the required communication and sensing resource allocation / configuration (e.g., threshold values for error contributions of Doppler, delay, angles, etc., thresholds for QoS related parameters, e.g., UL buffer values, number of re-transmissions, etc.).

[0261] As for the UE receiving conditions for sensing measurements such as delay, Doppler and angles, this has already been described with reference to step S210 of the first embodiment.

[0262] In addition to the sensing requirements, the UE receives information indicative of a configuration related to communication requirements, such as QoS requirements e.g., UL buffer values, number of re-transmissions, etc. When a sensing task is being performed along with communication, the resources of communication are being used for sensing purposes and vice versa. The UE can determine, based on the requirements of both communication and sensing, which one is important and how much resources each may require. The UE may also be configured by the NW with a weight parameter (e.g., a percentage), that dictates which of sensing and communications is the most important task. The function to determine can be provided to the UE by the NW or be implementation specific by vendors or be learned using AIML methods. The description of step S950 provides further information.

[0263] The UE is configured with QoS requirements and triggers to report to the network when QoS requirements in term of e.g., UL / DL throughput, packet error rate and packet delay, are determined to be compromised. There may be cases where both sensing and communication requirements are met at a certain moment, but due to changes in the UE’ s UL buffer for instance, UE is able to determine that QoS requirements are going to be comprised. Conversely, based on the accuracy of an ongoing sensing task, the UE may determine that it will require more resources allocated to the sensing task, and that will in turn affect the performance of the active QoS sessions.

[0264] The UE can be configured with QoS threshold values (e.g., soft thresholds) for, e.g., DL\UL throughput, packet error rate and packet delay. In this case, the UE triggers a report when a threshold for each of these QoS parameters falls below / above the threshold or falls within a certain interval. This can help the NW to allocate, proactively or dynamically, resources between communication and sensing.

[0265] The NW can send configuration information to the UE to report when rate of change of QoS parameters, e.g., packet delay, packet error rate and / or DLVUL throughput. An example is, when the rate of change of the UL buffer at the UE changes from rate X to rate Y, or if the increase in change rate is higher than a certain value, the UE may trigger a report to inform the NW of the preferred configuration. Similarly, when throughput changes with rate T, the UE may trigger a report to the NW.

[0266] Threshold (triggering condition) could be a change rate of the buffer status apart from threshold, this may indicate to the UE when this happens to trigger the report and inform the network.

[0267] QoS requirements may be provided to UE in terms of QoS classes to accommodate different services, whether it is voice, video services, etc. Each QoS class may have associated parameters such as latency, reliability and throughput and they are either provided to the UE before the sensing task or they are already known to the UE, configured by the NW., e.g., via RRC signaling. The configuration logic of the examples above applies to these requirements, as well as other QoS related parameters that might be introduced in the future. Each QoS session with an ongoing sensing may be configured via dynamic or fixed signaling (RRC, DCI / UCI, MAC CE) and this may be transmitted to the UE, or alternatively, it may be implicitly determined by the UE from already existing or previous QoS session and sensing task.

[0268] The sensing task requirements and how sensing performance in terms of overall accuracy can be achieved has already been described.

[0269] In step S920, the UE performs sensing related measurements (e.g., Doppler, delay, angles, differentiation single vs multiple bounce from multipath components). A more detailed description has already been provided in “Initial common solution components”.

[0270] In step S930, the UE determines, based on the above measurements, the estimates of delay, Doppler (and micro-Doppler), angles (AoA) and single bounce vs multiple bounce from the sensing signals. A more detailed description has already been provided in “Initial common solution components”.

[0271] In step S940, the UE determines whether the accuracy related to each relevant metric is met or not. For further details, see for example step S240 of the first embodiment.

[0272] In step S950, the UE determines whether the communication-related requirements are met with the current sensing related configuration.

[0273] If the sensing accuracy, determined in step S940, and the communication requirements determined in step S930, the UE can determine the communication and sensing trade-off.

[0274] The UE can be provided with a weight for the communications and for the sensing tasks (e.g., a percentage). The UE can be provided with a multitude of weights representing the importance of the different QoS parameters, e.g., DL / UL throughput, packet error rate, packet delay, etc. and / or a plurality of weights representing the importance of the different accuracies of different sensing related metrices. 49his can be executed by the UE as a function that can determine the trade-off between communication performance and sensing performance.

[0275] The function may be provided by the NW or be left for UE implementation. The UE can receive the function based on a dedicated request. The function can be delivered to the UE while configuring a sensing task, etc.

[0276] The reason to consider a function for the UE to compute the importance of either the communication and / or the sensing task is because the sensing task may be more complex, e.g., the UE may be configured to measure several sensing related metrics, while at the same time, the UE may be configured with specific QoS configuration that distinguishes, e.g., between different applications that are under QoS requirements to be met. But whether the sensing and communication tasks are more or less complex, the most important aspect is that the UE determines the joint importance of both tasks. So as an example, a resulting weight for each helps determining the best (or preferred) configuration. This is important to mention that the UE may be in a situation where, e.g., the weight for QoS requirements is 80% and therefore, the weight for sensing is 20%. With this weight setting, and if the UE determines the accuracy of the sensing task is not met and moreover, the QoS requirements configured are also not met, the preferred configuration will focus on the communications only. As a result, the UE may determine a preferred configuration that requests less resources for the sensing task and / or more resources for the communications task. Conversely, with a weight of 80% for the sensing task and 20% for the communications task, and if the UE is in a situation where the accuracy of the sensing task exceeds significantly the requirements, the UE may request, e.g., the activation of a pre-configured BW part for communication purposes.

[0277] As described, the UE suggests / recommends the NW to (re)configure resources to achieve sensing accuracy and / or desired communication performance. Similarly, UE also suggests / recommends the NW to reconfigure if sensing accuracy is met and there are remainingresources that the UE is left with. These resources may be used for more sensing or for communication.

[0278] The resource configuration may result in an increase or decrease in the number of OFDM symbols or slots for sensing signals.

[0279] The resource configuration may result in an increase or decrease of the BW allocation. The UE can determine the size of the required BW, and / or a specific BW part to request activation, and / or a subset of BW parts, etc. The determination can be based on the weight for each of the sensing and communications tasks, the current QoS status (e.g., thresholds for DL / UL tput, packet error rate, packet delay, etc.), and the current accuracy of the one or more sensing metrices. The UE may also determine a time associated with the BW parts, that would be the computed time required to achieve the QoS requirements configured. The UE may perform this computation based on current / past traffic data for one or more applications, its UL buffer levels, etc., and / or the status of the sensing task.

[0280] The resource configuration may result in a provision of more / less PRS resources (this may be e.g., an indication of PRS comb structure suggested by the UE, and / or the desired time and frequency resources which can be mapped to the PRS resources by the NW). There is current support for PRS adaptation, but the focus is solely on the sensing (e.g., positioning) task requirements. Herein, the UE may determine, based on the previously mentioned aspects, that the PRS resources need reconfiguration. The UE may determine the new PRS requirements by assessing the status and weight of each task, determining the QoS status as previously detailed, and based on that information, determine the new PRS configuration that best suits both task’s requirements. This outcome could be represented in different ways, e.g., increase / decrease PRS BW, number of slots, comb structure, etc.

[0281] The resource configuration may result in an activation of dual connectivity and / or Carrier Aggregation (CA). The UE may also activate a pre-configured measurement configuration, perform measurements, and request the activation of CA and / or dual connectivity to the NW. for this purpose, the UE may be configured with specific thresholds from the NW, e.g., for RSRP, for the purpose of identifying potential CA / DC candidates. In this case, the UE may trigger such request, and include measurements that result from assessing those neighbour cells.

[0282] In case the sensing accuracy of one or more metrices is not met and / or communication / QoS related requirements are not satisfied, in step S960, the UE determines a preferred configuration based on the QoS requirements of the communication and sensing accuracy requirements (e.g., increase / decrease number of OFDM symbols / slots, increase / decrease BW allocation of the sensing signal, request different CSI-RS / PRS resources, etc. that satisfycommunications and / or sensing requirements), and, in step S970, the UE transmits information indicative of the determined preferred configuration to the network.

[0283] The UE transmits a message, e.g., via UCI, MAC CE and / or RRC, with the preferred configuration. Additional details may be included in this message, as described in the examples below.

[0284] The UE may send an indication to the NW that the communication task is more important than the sensing task OR that the sensing task is more important than the communication task and the desired accuracy has not been met and therefore, the NW reconfigures the resources.

[0285] The UE can provide a NW a time in which a sensing signal (PRS, CSI-RS or any other signal for sensing) is already configured, an indication that using the sensing signal at that time should be enough to reach the desired sensing performance. This allows the NW to anticipate and reconfigure to save resources or for efficient resource allocation.

[0286] If the sensing accuracy is met with the configured resources and there are resources left that can be utilized for some other purpose to perform more sensing, the UE can indicate the NW about the remaining resources along with a scheduling request, if the UE has any communication data to be sent in the UL.

[0287] The UE can send the indication to the NW about the remaining resources. The remaining resources are in terms of remaining time slots or the number of symbols.

[0288] The remaining resources can be the BW allocated to the NW for sensing and UE can send the indication about the remaining BW.

[0289] The UE can be configured with PRS resources to perform sensing. UE indicates the NW that the desired sensing performance is met and suggests the NW to free up these resources and use them for communication purposes.

[0290] The UE can be configured with PRS resources to perform sensing, and the UE can indicate to the NW that the desired sensing performance is met and suggest the NW to use the resources for more sensing or for another sensing task.

[0291] The UE can be configured with PRS resources to perform sensing and the UE can indicate to the NW that the desired sensing performance is met and suggest the NW to use the resources somewhere else (provide it to another UE or anything that NW may use the resources for).

[0292] The UE can perform a sensing task and upon determining that one or more of packet error rate, throughput DL / UL, and / or packet error rate fall below a preconfigured value (Details in Step 1) trigger a report or indication to send to the NW.

[0293] The UE can perform a sensing task and upon determining that the change of rate of one or more of packet error rate, throughput DL / UL, and / or packet error rate trigger a report orindication to send to the NW. For example, incoming packets in packets buffer have a 2% increase since last X time slots or seconds or any other time unit. This can trigger the UE to report to the NW about this change.

[0294] Based on QoS requirements and buffer status report of the UE, the UE can send a scheduling request (SR) to the NW. In this case, UE is able to determine that it has communication data to be transmitted and QoS requirements might be compromised, and communication task is more important than the sensing task. The UE can send an indication to the NW that communication task is more important, or the NW may know this implicitly. The UE can also send a Buffer Status Report (BSR) to the NW along with the SR.

[0295] The UE can be configured to send the report in specific time (configured using the information in step S910). The time to report may be periodic or aperiodic or on-demand.

[0296] FIG. 10 illustrates a flow chart of a method of a sixth embodiment of the present principles in which the UE indicates to the NW the expected time a sensing task cannot be performed.

[0297] While performing a sensing task, the UE may detect that any of the metrics, i.e., Doppler / angular / delay, may fall below e.g., a certain SNR and / or above an RMSE threshold. Based on this, the NW may decide or not on a different resource allocation configuration (as in the previous solution) for an increased probability of a successful sensing task. To assist the NW in the decision, the UE can transmit the expected time that metric will remain below the SNR and / or above the RMSE thresholds.

[0298] In brief, the UE receives information indicative of an initial configuration for sampling of sensing signals, the sensing task requirements and thresholds of delay, Doppler and angles to measure accuracy of each metric. The UE further receives information indicative of a further configuration with e.g., an SNR (or RMSE) threshold (e.g., a soft threshold) to trigger the prediction of e.g., SNR values. The UE then determines and transmits the expected time that metric will remain below / above the SNR / RMSE thresholds, based on the predicted values.

[0299] In step S1010, the UE receives from the network configuration information and trigger thresholds. It is noted that, as in other embodiments, the information can be received separately, for example at different times.

[0300] The configuration information is indicative of how to perform the sensing task (e.g., indication of a specific pilot signal, its time, frequency domain resources and the format of sensing signals, etc. UE also receives time related configuration, e.g., for how long to perform a sensing task, when to report sensing related measurements, etc.). A more detailed description has already been provided in “Initial common solution components”.

[0301] The trigger thresholds, for example related to SNR or RMSE, indicate thresholds for triggering the predictions of e.g., SNR for one or more metric, delay, Doppler, angles.

[0302] In addition, the UE can receive threshold values in terms of SNR for one or more metrics. For instance, speed or velocity estimation for a particular target during a particular sensing task (e.g., UAV flight trajectory tracking), meets the requirements if the instantaneous or average SNR remain within a pre-defined threshold. This means that velocity estimation can be provided with high confidence and with better accuracy as long as SNR or received sensing signals does not fall below this threshold. UE is provided with these thresholds for each sensing metric.

[0303] As can be seen from the examples provided herein and in 3GPP TS 22.837 (release 19), the requirements for each task are typically different and therefore, it is expected that the SNR requirements for each of these tasks and for each metrices are different. In step S1010, the NW provides this configuration / assistance information to the UE.

[0304] Furthermore, SNR bounds or lower bound in this case, may be tighter or loosened for each of these sensing metrics and this will depend on the ongoing sensing task requirements. The SNR threshold for delay estimation could be tighter if, e.g., two objects need to be distinguished for a sensing task.

[0305] These thresholds can be provided in terms of RMSE values for each sensing metric. In this case, the receiver, i.e., the UE already knows the optimal value or the known value for the RMSE. This may also be provided by the NW. Based on this value and estimated value, UE may determine the RMSE and how confident UE is about this value. If it falls above a certain threshold, UE triggers a report to the NW. The report is about the UE prediction of the next time window whether SNR or RMSE is going to be below / above the configured thresholds for each sensing metric (more details are provided with reference to step 1040)

[0306] The UE can trigger a report at configured times provided by the NW. UE receives time information when to send this indication to the NW. The indication is about the UE predicting the next time window whether SNR or RMSE is going to be above the configured thresholds for each sensing metric (more details are provided with reference to step 1040). The time to report to the NW can be periodic, implicitly known to the UE, aperiodic, where the NW provides times in which UE will report to the NW, or dynamically configured, e.g., UE only reports when NW asks for it otherwise it assumes that it is not supposed to report it.

[0307] In step SI 020, the UE performs sensing related measurements (e.g., Doppler, delay, angles, differentiation single vs multiple bounce from multipath components). A more detailed description has already been provided in “Initial common solution components”.

[0308] In step SI 030, the UE determines, based on the above measurements, the estimates of delay, Doppler (and micro-Doppler), angles (AoA) and single bounce vs multiple bounce from the sensing signals. A more detailed description has already been provided in “Initial common solution components”.

[0309] In step SI 040, the UE determines that one or more Doppler / angular / delay samples meet the configured SNR / RMSE criteria.

[0310] The UE estimates the received SNR and matches it against the SNR of each sensing metric such as delay, Doppler, and angles. The UE determines whether the estimated SNR (average SNR over X time window or instantaneous SNR) for each sensing metric falls within the configured SNR thresholds or not. The UE can also calculate RMSE for each sensing metric such as delay, Doppler, and angles. The UE can determine whether the RMSE (average SNR over X time window or instantaneous SNR) for each sensing metric falls within the configured SNR thresholds or not.

[0311] The UE can consider only the metrices to determine the SNR thresholds that are important to the sensing task. For example, for the intruder detection use case, the velocity estimation may not be important and Doppler estimations (or Doppler thresholds) may be unconsidered to determine the threshold against SNR. The Doppler estimation can be unconsidered if it falls below the threshold SNR. The rationale is that Doppler estimation in this case may be useful for the NW and therefore it is still considered if its falls above threshold, otherwise it is excluded and not use in the next step of predicting the time window.

[0312] In step S1050, the UE predicts one or more of Doppler / angular / delay samples, and / or SNR of the samples and / or the RMSE of the samples.

[0313] Based on the determination whether SNR for each metric falls below / above threshold values, UE can then predict a future time window in which the SNR / RMSE of one or more metrics will fall below / above threshold. The determination may be used for statistical methods to predict the time window and / or use AIML methods. UE can keep records of previous SNR values until a certain time period in the past and based on those values, it predicts the time window.

[0314] The UE can also calculate the probability distribution (PM{SNR = above threshold}, PM { SNR = below threshold}) and M is any metric such as delay, Doppler, angles etc. Each probability distribution for each metric will have associated time window in which SNR can be above / below threshold. Even though SNR remains the same for all metrices, the threshold values may be different for each metric, and it highly depends on the sensing task and its requirements.

[0315] The UE can consider only the SNR threshold and past SNR values for prediction purposes, of one or more metrices that are important to the ongoing sensing task. This can bedetermined as described with reference to the second embodiment, where the contribution of each error is calculated, or it can be provided to each UE by the NW.

[0316] The UE can consider only the SNR threshold and past SNR values for prediction for metrices that fall above SNR at a given time or if the average of SNR values for those metrices fall above given threshold.

[0317] The UE can also consider previous SNR threshold values as well as the accuracy of each metric until t-K time window. The accuracy, whether it was met or not is a useful information that could be used to predict time window in the future over which SNR may fall below or above a certain threshold value.

[0318] For these cases, RMSE can be substituted for SNR, but it is noted that where high values are desired with SNR, low values are desired with RSME.

[0319] In step SI 060, the UE predicts (estimates) the expected time one or more of Doppler / angular / delay estimates will remain below / above the configured threshold(s), based on the predictions and / or measurements of Doppler / angular / delay samples.

[0320] Each sensing metric may have different associated SNR threshold values and this may vary depending on the ongoing sensing task. This may as well affect the predictions of time window.

[0321] The time window can be provided in terms of time slots or frames, e.g., time starting from a particular time slot / frame until the end of time slot / frame number.

[0322] The time window can be a real time start between t— t+k, where t is the real time. The time t may start from the moment when the report was generated.

[0323] In step S 1070, the UE determines the expected time during which the sensing task cannot be successfully performed, based on the predicted values and the sensing task configuration.

[0324] Based on the predicted time window, a UE can determine whether the sensing task is or isn’t able to achieve the desired accuracy. It is assumed that functions already described (see third and fourth embodiments) are able to determine this.

[0325] The UE can determine, based on the latency requirements of the sensing task and the prediction of SNR / RMSE values, whether the UE can perform the sensing task or not.

[0326] The UE can determine that it is not able to perform the sensing task until X number of time slots or frames. The determination can also be made in real time. This time could be shortterm or long-term.

[0327] The UE can determine that it can estimate one more sensing metrics such as delay, Doppler, angular, micro-Doppler, object characterization etc., for X seconds (or any other time unit), or for X number of time slots or frames.

[0328] The UE can estimate whether it can perform the sensing task or not based on the requirements and metrics that are important for that sensing task.

[0329] In step SI 080, the UE transmits to the NW an indication of the expected time the sensing task cannot be successfully performed, where additional information can be included, such as predicted Doppler / angular / delay metric related information.

[0330] Based on the configuration of when to report to the NW or when the configured triggering conditions are met, the UE can transmit one or more of a report indicating that the UE cannot perform the ongoing sensing task, an indication that UE cannot perform sensing task until X number of time slots frames or seconds or any other time unit, a report including predictions results and indication whether UE can or cannot perform sensing, an indication that the UE can measure one of more sensing parameters with more confidence as opposed to one or more other sensing parameters.

[0331] Conclusion

[0332] Although features and elements are provided above in particular combinations, one of ordinary skill in the art will appreciate that each feature or element can be used alone or in any combination with the other features and elements. The present disclosure is not to be limited in terms of the particular embodiments described in this application, which are intended as illustrations of various aspects. Many modifications and variations may be made without departing from its spirit and scope, as will be apparent to those skilled in the art. No element, act, or instruction used in the description of the present application should be construed as critical or essential to the invention unless explicitly provided as such. Functionally equivalent methods and apparatuses within the scope of the disclosure, in addition to those enumerated herein, will be apparent to those skilled in the art from the foregoing descriptions. Such modifications and variations are intended to fall within the scope of the appended claims. The present disclosure is to be limited only by the terms of the appended claims, along with the full scope of equivalents to which such claims are entitled. It is to be understood that this disclosure is not limited to particular methods or systems.

[0333] The foregoing embodiments are discussed, for simplicity, with regard to the terminology and structure of infrared capable devices, i.e., infrared emitters and receivers. However, the embodiments discussed are not limited to these systems but may be applied to other systems that use other forms of electromagnetic waves or non-electromagnetic waves such as acoustic waves.

[0334] It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting. As used herein, the term "video" or the term "imagery" may mean any of a snapshot, single image and / or multiple images displayedover a time basis. As another example, when referred to herein, the terms "user equipment" and its abbreviation "UE", the term "remote" and / or the terms "head mounted display" or its abbreviation "HMD" may mean or include (i) a wireless transmit and / or receive unit (WTRU); (ii) any of a number of embodiments of a WTRU; (iii) a wireless-capable and / or wired-capable (e.g., tetherable) device configured with, inter alia, some or all structures and functionality of a WTRU; (iii) a wireless-capable and / or wired-capable device configured with less than all structures and functionality of a WTRU; or (iv) the like. Details of an example WTRU, which may be representative of any WTRU recited herein, are provided herein with respect to FIGs. 1 A-1D. As another example, various disclosed embodiments herein supra and infra are described as utilizing a head mounted display. Those skilled in the art will recognize that a device other than the head mounted display may be utilized and some or all of the disclosure and various disclosed embodiments can be modified accordingly without undue experimentation. Examples of such other device may include a drone or other device configured to stream information for providing the adapted reality experience.

[0335] In addition, the methods provided herein may be implemented in a computer program, software, or firmware incorporated in a computer-readable medium for execution by a computer or processor. Examples of computer-readable media include electronic signals (transmitted over wired or wireless connections) and computer-readable storage media. Examples of computer- readable storage media include, but are not limited to, a read only memory (ROM), a random access memory (RAM), a register, cache memory, semiconductor memory devices, magnetic media such as internal hard disks and removable disks, magneto-optical media, and optical media such as CD-ROM disks, and digital versatile disks (DVDs). A processor in association with software may be used to implement a radio frequency transceiver for use in a WTRU, UE, terminal, base station, RNC, or any host computer.

[0336] Variations of the method, apparatus and system provided above are possible without departing from the scope of the invention. In view of the wide variety of embodiments that can be applied, it should be understood that the illustrated embodiments are examples only, and should not be taken as limiting the scope of the following claims. For instance, the embodiments provided herein include handheld devices, which may include or be utilized with any appropriate voltage source, such as a battery and the like, providing any appropriate voltage.

[0337] Moreover, in the embodiments provided above, processing platforms, computing systems, controllers, and other devices that include processors are noted. These devices may include at least one Central Processing Unit ("CPU") and memory. In accordance with the practices of persons skilled in the art of computer programming, reference to acts and symbolicrepresentations of operations or instructions may be performed by the various CPUs and memories. Such acts and operations or instructions may be referred to as being "executed," "computer executed" or "CPU executed."

[0338] One of ordinary skill in the art will appreciate that the acts and symbolically represented operations or instructions include the manipulation of electrical signals by the CPU. An electrical system represents data bits that can cause a resulting transformation or reduction of the electrical signals and the maintenance of data bits at memory locations in a memory system to thereby reconfigure or otherwise alter the CPU's operation, as well as other processing of signals. The memory locations where data bits are maintained are physical locations that have particular electrical, magnetic, optical, or organic properties corresponding to or representative of the data bits. It should be understood that the embodiments are not limited to the above-mentioned platforms or CPUs and that other platforms and CPUs may support the provided methods.

[0339] The data bits may also be maintained on a computer readable medium including magnetic disks, optical disks, and any other volatile (e.g., Random Access Memory (RAM)) or non-volatile (e.g., Read-Only Memory (ROM)) mass storage system readable by the CPU. The computer readable medium may include cooperating or interconnected computer readable medium, which exist exclusively on the processing system or are distributed among multiple interconnected processing systems that may be local or remote to the processing system. It should be understood that the embodiments are not limited to the above-mentioned memories and that other platforms and memories may support the provided methods.

[0340] In an illustrative embodiment, any of the operations, processes, etc. described herein may be implemented as computer-readable instructions stored on a computer-readable medium. The computer-readable instructions may be executed by a processor of a mobile unit, a network element, and / or any other computing device.

[0341] There is little distinction left between hardware and software implementations of aspects of systems. The use of hardware or software is generally (but not always, in that in certain contexts the choice between hardware and software may become significant) a design choice representing cost versus efficiency trade-offs. There may be various vehicles by which processes and / or systems and / or other technologies described herein may be effected (e.g., hardware, software, and / or firmware), and the preferred vehicle may vary with the context in which the processes and / or systems and / or other technologies are deployed. For example, if an implementer determines that speed and accuracy are paramount, the implementer may opt for a mainly hardware and / or firmware vehicle. If flexibility is paramount, the implementer may opt for a mainly softwareimplementation. Alternatively, the implementer may opt for some combination of hardware, software, and / or firmware.

[0342] The foregoing detailed description has set forth various embodiments of the devices and / or processes via the use of block diagrams, flowcharts, and / or examples. Insofar as such block diagrams, flowcharts, and / or examples include one or more functions and / or operations, it will be understood by those within the art that each function and / or operation within such block diagrams, flowcharts, or examples may be implemented, individually and / or collectively, by a wide range of hardware, software, firmware, or virtually any combination thereof. In an embodiment, several portions of the subject matter described herein may be implemented via Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs), digital signal processors (DSPs), and / or other integrated formats. However, those skilled in the art will recognize that some aspects of the embodiments disclosed herein, in whole or in part, may be equivalently implemented in integrated circuits, as one or more computer programs running on one or more computers (e.g., as one or more programs running on one or more computer systems), as one or more programs running on one or more processors (e.g., as one or more programs running on one or more microprocessors), as firmware, or as virtually any combination thereof, and that designing the circuitry and / or writing the code for the software and or firmware would be well within the skill of one of skill in the art in light of this disclosure. In addition, those skilled in the art will appreciate that the mechanisms of the subject matter described herein may be distributed as a program product in a variety of forms, and that an illustrative embodiment of the subject matter described herein applies regardless of the particular type of signal bearing medium used to actually carry out the distribution. Examples of a signal bearing medium include, but are not limited to, the following: a recordable type medium such as a floppy disk, a hard disk drive, a CD, a DVD, a digital tape, a computer memory, etc., and a transmission type medium such as a digital and / or an analog communication medium (e.g., a fiber optic cable, a waveguide, a wired communications link, a wireless communication link, etc.).

[0343] Those skilled in the art will recognize that it is common within the art to describe devices and / or processes in the fashion set forth herein, and thereafter use engineering practices to integrate such described devices and / or processes into data processing systems. That is, at least a portion of the devices and / or processes described herein may be integrated into a data processing system via a reasonable amount of experimentation. Those having skill in the art will recognize that a typical data processing system may generally include one or more of a system unit housing, a video display device, a memory such as volatile and non-volatile memory, processors such as microprocessors and digital signal processors, computational entities such as operating systems,drivers, graphical user interfaces, and applications programs, one or more interaction devices, such as a touch pad or screen, and / or control systems including feedback loops and control motors (e.g., feedback for sensing position and / or velocity, control motors for moving and / or adjusting components and / or quantities). A typical data processing system may be implemented utilizing any suitable commercially available components, such as those typically found in data computing / communication and / or network computing / communication systems.

[0344] The herein described subject matter sometimes illustrates different components included within, or connected with, different other components. It is to be understood that such depicted architectures are merely examples, and that in fact many other architectures may be implemented which achieve the same functionality. In a conceptual sense, any arrangement of components to achieve the same functionality is effectively "associated" such that the desired functionality may be achieved. Hence, any two components herein combined to achieve a particular functionality may be seen as "associated with" each other such that the desired functionality is achieved, irrespective of architectures or intermedial components. Likewise, any two components so associated may also be viewed as being "operably connected", or "operably coupled", to each other to achieve the desired functionality, and any two components capable of being so associated may also be viewed as being "operably couplable" to each other to achieve the desired functionality. Specific examples of operably couplable include but are not limited to physically mateable and / or physically interacting components and / or wirelessly interactable and / or wirelessly interacting components and / or logically interacting and / or logically interactable components.

[0345] With respect to the use of substantially any plural and / or singular terms herein, those having skill in the art can translate from the plural to the singular and / or from the singular to the plural as is appropriate to the context and / or application. The various singular / plural permutations may be expressly set forth herein for sake of clarity.

[0346] It will be understood by those within the art that, in general, terms used herein, and especially in the appended claims (e.g., bodies of the appended claims) are generally intended as "open" terms (e.g., the term "including" should be interpreted as "including but not limited to," the term "having" should be interpreted as "having at least," the term "includes" should be interpreted as "includes but is not limited to," etc.). It will be further understood by those within the art that if a specific number of an introduced claim recitation is intended, such an intent will be explicitly recited in the claim, and in the absence of such recitation no such intent is present. For example, where only one item is intended, the term "single" or similar language may be used. As an aid to understanding, the following appended claims and / or the descriptions herein may include usage of the introductory phrases "at least one" and "one or more" to introduce claim recitations. However,the use of such phrases should not be construed to imply that the introduction of a claim recitation by the indefinite articles "a" or "an" limits any particular claim including such introduced claim recitation to embodiments including only one such recitation, even when the same claim includes the introductory phrases "one or more" or "at least one" and indefinite articles such as "a" or "an" (e.g., "a" and / or "an" should be interpreted to mean "at least one" or "one or more"). The same holds true for the use of definite articles used to introduce claim recitations. In addition, even if a specific number of an introduced claim recitation is explicitly recited, those skilled in the art will recognize that such recitation should be interpreted to mean at least the recited number (e.g., the bare recitation of "two recitations," without other modifiers, means at least two recitations, or two or more recitations). Furthermore, in those instances where a convention analogous to "at least one of A, B, and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B, and C" would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and / or A, B, and C together, etc.). In those instances where a convention analogous to "at least one of A, B, or C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B, or C" would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and / or A, B, and C together, etc.). It will be further understood by those within the art that virtually any disjunctive word and / or phrase presenting two or more alternative terms, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase "A or B" will be understood to include the possibilities of "A" or "B" or "A and B." Further, the terms "any of' followed by a listing of a plurality of items and / or a plurality of categories of items, as used herein, are intended to include "any of," "any combination of," "any multiple of," and / or "any combination of multiples of the items and / or the categories of items, individually or in conjunction with other items and / or other categories of items. Moreover, as used herein, the term "set" is intended to include any number of items, including zero. Additionally, as used herein, the term "number" is intended to include any number, including zero. And the term "multiple", as used herein, is intended to be synonymous with "a plurality".

[0347] In addition, where features or aspects of the disclosure are described in terms of Markush groups, those skilled in the art will recognize that the disclosure is also thereby described in terms of any individual member or subgroup of members of the Markush group.

[0348] As will be understood by one skilled in the art, for any and all purposes, such as in terms of providing a written description, all ranges disclosed herein also encompass any and all possible subranges and combinations of subranges thereof. Any listed range can be easily recognized as sufficiently describing and enabling the same range being broken down into at least equal halves, thirds, quarters, fifths, tenths, etc. As a non-limiting example, each range discussed herein may be readily broken down into a lower third, middle third and upper third, etc. As will also be understood by one skilled in the art all language such as "up to," "at least," "greater than," "less than," and the like includes the number recited and refers to ranges which can be subsequently broken down into subranges as discussed above. Finally, as will be understood by one skilled in the art, a range includes each individual member. Thus, for example, a group having 1-3 cells refers to groups having 1, 2, or 3 cells. Similarly, a group having 1-5 cells refers to groups having 1, 2, 3, 4, or 5 cells, and so forth.

[0349] Moreover, the claims should not be read as limited to the provided order or elements unless stated to that effect. In addition, use of the terms "means for" in any claim is intended to invoke 35 U.S.C. §112, 6 or means-plus-function claim format, and any claim without the terms "means for" is not so intended.

[0350] Annex

[0351] Sensing

[0352] The application of ISAC technology in future mobile networks has already reached a consensus. For example, the international telecommunication union (ITU) international mobile telecommunication-2030 (IMT-2030) has identified JSC as one of the candidates enabling technologies of 6G. The ITU-Radiocommuni cation Sector (ITU-R) WP5D document indicates that IMT-2030 and beyond will consider integrated communication, positioning, and sensing, and potentially even jointly design flexible signals for concurrent communication, positioning and sensing with slight or no modification to hardware and waveform. By sensing is meant sensing using radio signals or radar-like sensing.

[0353] Sensing using reference signals.

[0354] Pilot or reference signals in wireless communications usually have good passive detection performance, strong anti-noise capability and good auto-correlation characteristics (highly sufficient ambiguity function which is pushpin type), hence they bear the potential for sensing and particularly for ISAC waveform design. Using these reference signals (e.g., PRS / SRSp) has the benefit of compatibility with most advanced mobile communication system available so far. Thus, these reference signals can be regarded as a sensing reference signal to simultaneously realize the functions of sensing, communication, and positioning in a convenient manner.

[0355] The pilot based OFDM waveform is suitable to realize short-range, medium-range and long-range radars based on the flexible allocation of pilot subcarriers. On top of that, PRS / SRSp designed especially for 5G in-band wireless positioning enjoys the advantages of long sequence, good autocorrelation, rich time-frequency resources, and flexible configuration, which is more suitable for radar sensing compared with other pilot signals.

[0356] The range estimation error, CRLB(Rr) can be expressed asand the velocity estimation error, CLRB(v), as

[0357] The CRLB for range and velocity estimation presented in the previous paragraph show that there is a performance trade-off between range and velocity estimation. Hence, this will influence the time-frequency resource allocation of the sensing reference signal, which is mainly determined by the sensing performance requirements. Furthermore, FIG. 12 shows the relationship between the CRLB of range and velocity estimation under different SNRs. As the SNR increases,the CRLB of range and velocity estimation decreases, which indicates that a better lower bound of accuracy can be reached. This will affect the sensing mode, the multi-slot configurations e.g., PRS resource repetition, and challenges the sensing processing algorithms.

[0358] Measurements

[0359] The description of the different measurements are taken from 3GPP TS 38.215 (Release19).

[0360] Received PowerDL PRS reference signal received power (DL PRS-RSRP)

[0361] Delay

[0362] Doppler

[0364] It will be appreciated that new measurements may also be defined for sensing such asDL-AoA etc.

[0365] Bandwidth Parts

[0366] 3 GPP TS 38.211 specifies Bandwidth Part (BWP) as a contiguous set of physical resource blocks (PRBs) for a given carrier. In other words, it is a subset of the total BW that comprises acontiguous RB subset of the common resource blocks for a given numerology (defined 0 to 3 for 5G). Each BWP defined for a numerology can have three different parameters: Subcarrier spacing, Symbol duration, Cyclic prefix (CP) length, PointA offset. Using BWP can significantly reduce the UE power consumption in NR due to several aspects (e.g., reduced bandwidth processing requirement to receive or transmit narrow bandwidth, enabling lower sampling rates, etc.), improve radio resources and enable supporting different services.

[0367] The UE can for example be configured with maximum 4 BWP for Downlink and Uplink each, but at a given point of time only one BWP is active for downlink and one for uplink. Each BWP is configured by RRC messages. If a UE is configured with a supplementary uplink, it can additionally be configured with up to four bandwidth parts in the supplementary uplink, with a single supplementary uplink bandwidth part being active at a given time.

[0368] According to TS 38.321-5.15, switching between BWPs can be done using different mechanisms: RRC -based adaptation, MAC CE (control element), DCI based adaptation, and Timer-based implicit fallback to default BWP. Switching between BWP is accompanied with a set of configurations changing processes. Accordingly, it would require a certain amount of time to switch between BWPs (BWP switching delay) and the minimum switching time is up to the switching mechanism and the UE capability which should be informed to network via UE capability Information.

[0369] Reference Signals (e.g., DL-PRS and UL-SRSp)

[0370] Multiple reference signals are used for communication related procedures. For positioning, 3GPP introduced in release 16 new positioning reference signals for downlink and uplink. These reference signals are called the positioning reference signal (DL-PRS) and sounding reference signals (UL-SRSp), respectively. An interesting thing about these reference signals compared to the conventional ones is that they feature high resource element (RE) density, high autocorrelation, and cross-correlation properties. Another important new feature is hearability, also known as Audibility, which is achieved with a concept called muting. With PRS muting, multiple cells transmit the PRS in a coordinated manner by muting the relevant PRS transmission occasions to avoid interference from adjacent cells. In terms of configuration, LMF provides DL- PRS configuration to UEs using LTE positioning protocol (LPP) while RAN configures UL-SRS to UEs using radio resource control (RRC) protocol.

[0371] The PRS configuration is done per positioning frequency layer (PFL). A PFL is defined as a collection of resource sets that can be associated with at most 64 TRPs, each TRP can have 2 resource sets. A resource set comprises up to 64 resources where each resource corresponds to a beam. Per frequency layer, a gNB can configure 2 sets of beams (e.g., wide and / or narrow), eachset is associated with one of the available resource sets. As per the 3GPP standard, it is possible to configure a UE up to four PFL configurations per downlink and same for the uplink.

[0372] At the resource level, different beams can be time-multiplexed across symbols or slots. Only one beam can be transmitted at a time. And the repetition of the resources (beam) can be done in two ways: sweep before repeat or repeat before sweep. Within a resource set period, the DL PRS resource which corresponds to a beam can be repeated up to 32 times, either in consecutive slots or with a repetition gap that can be configured. In other words, a UE can collect up to 32 measurements from that same resource configuration to achieve the best possible estimation accuracy. Different types of measurements can be done using DL-PRS signals (angle, time, power, etc.). These measurements can be extracted from the variations occurred to the received signal, by comparing it to an undistorted local replica at the receiver using different signal processing tools.

[0373] Artificial Intelligence and Machine Learning (AIML) for NR

[0374] The UE can perform a multitude of the described measurements. These measurements can be a valuable dataset that can be leveraged for predictive capabilities, especially in the context of supervised learning. Its usage is however not limited to that. Statistical properties can be retrieved from the measurement data, which can help creating insights, predicting certain target metrics, etc. Herein, a few examples of how both the UE or the NW can predict a target metric are provided. There is an assumption that it is the UE that executes prediction on measurements, but nothing precludes that the NW can execute them and deliver the predictions to the UE. In this case, the predicted values can be sent to the UE and the UE can either validate them by comparing current measurement values. The UE may also, upon reception of a predicted value, execute its own predictions and validate the values predicted by the NW if, e.g., UE predicted values do not differ from the NW predicted values by a certain amount, amount which could also be configured by the NW.

[0375] For the purpose of the present principles, the UE is assumed to have a pre-trained AI / ML model that is able to produce predictions of air-interface and / or sensing related measurements (RSRP, RSRQ, SINR, Doppler, angular, delay, etc.) of serving and / or neighbor cells (any cell, basically), and / or any TRP emitting a reference signal used for the purpose of sensing, e.g., a PRS. The predictions are a tool in this invention to anticipate the measurements the UE will experience.

[0376] In order to produce more meaningful predictions in this context, it makes sense to consider the UE predicts SNR of sensing measurements. Predictions can be executed in a time series manner. This means that from the moment the UE predictions are triggered, it will produce several prediction outputs over a future time span, with a certain granularity or time step.

[0377] FIG. 11 illustrates an example of the time series prediction for SNR in which a machine learning (ML) algorithm takes as input past SNR, current SNR, the metric and possibly other inputs to output the SNR at time t+1 along with error 1 and so on.

[0378] The predictions can also be done for one point in time only and can extend over several time steps. In many scenarios, prediction with time series output may be beneficial than single value predictions as it may be difficult to match the prediction with e.g., a specific NW configured SNR value with a single prediction point. Instead, the UE can then predict several samples of e.g., SNR, and with that information, it can easily determine the time it would take until the SNR values will be under / above a certain threshold.

[0379] The UE may be configured to predict future measurements based on current and / or historical measurements. For example, the UE may be configured with a trained AI / ML model that is able to produce predictions for radio interface radio signal levels and / or sensing related measurements. The AI / ML model at the UE may be implementation based. In another solution, the UE may obtain the AI / ML model from the NW. In one solution, the AI / ML model may be configured to take as an input current and / or historical SNR measurements. In another solution, the AI / ML model may be configured to take additional inputs such as UE location information, UE mobility, etc. The AI / ML model can be requested by the UE from the NW or from a server, based on the configuration of another event, e.g., a specific event related to a sensing task. The AI / ML model may be configured to produce single value predictions - i.e., SNR at a future specific time instant t. In another solution the AI / ML model may be configured to predict a series of SNR values corresponding to future time instances t+1, t+2 and so on, up to t+t_fb, which represents the time of the final predicted value.

[0380] The predicted value (e.g., SNR values) may be associated and / or represented by a confidence or error value, and may be represented by an average, peak, minimum value, etc. along a short time window representing the validity of that prediction. For example, the following could be the SNR prediction that the AI / ML generates at least x seconds with 95% confidence, at least y seconds with 90% confidence, at most z seconds with 80% confidence, etc.

[0381] As another example, the SNR prediction could be SNR of A between x and y seconds, with 95% confidence, SNR of B between y and z seconds, with 90% confidence, etc.,

[0382] Furthermore, it is assumed that there is some UE capability communication between the UE and the network about AIML capability (e.g., where the UE can indicate to the network the supported AIML models / functions, confidence level of predictions, time horizon of predictions (how far along in the future are the prediction being made), etc.,)

[0383] It is further assumed that the UE may support several AIML models for a certain functionality (e.g., with different prediction time horizons, prediction confidence levels, processing requirements, trained under / for operation in different frequencies / cells / location / times of day, etc.,).

[0384] It is further assumed that a given AIML model can operate in different modes (e.g., with different levels of prediction confidence levels at different prediction time horizons, etc.,)

[0385] It is further assumed that the UE may choose the AIML model to use for a certain functionality (e.g., network decides for which functionalities the UE can use AIML based operation, and the UE chooses the AIML model to use) or the network may explicitly control this (E.g., UE provides details of AIML models and their capabilities, network determines which model to activate for a particular functionality)

[0386] It is further assumed that the AIML models can be available at the UE already trained, or the UE may be provided with an untrained AIML model and performs the training by itself.

[0387] It is further assumed that the AIML model is available at the UE already trained, and the UE may be enabled / configured to perform further training (e.g., for different conditions such as frequencies / cells / location / times of day, for the same conditions as the initial training but for increasing the level of confidence or / and the prediction time horizon, etc.,)

Claims

CLAIMSWhat is claimed is:

1. A method at a wireless transmit / receive unit, WTRU, the method comprising: receiving, from a network, information indicative of a sensing task; obtaining sensing related measurements according to the information indicative of the sensing task; determining, based on the sensing related measurements, at least one estimated metric; determining, based on the at least one estimated metric, whether an accuracy for the sensing task has been achieved; and transmitting, to the network, information indicative of whether or not the accuracy for the sensing task has been achieved.

2. The method of claim 1, wherein the information indicative of a sensing task comprises at least one of indication of a pilot signal, a time for the sensing task, frequency domain resources, a format of sensing signals, how long to perform the sensing task, and when to report sensing related measurements.

3. The method of claim 1, wherein the information indicative of a sensing task comprises at least one condition to trigger transmitting the information indicative of whether or not the accuracy for the sensing task has been achieved.

4. The method of claim 1, wherein the sensing related measurements are for at least one of doppler, delay, angles, differentiation single vs multiple bounce from multipath components.

5. The method of claim 1, further comprising transmitting, to the network, the at least one estimated metric.

6. A wireless transmit / receive unit, WTRU, comprising at least one processor configured to: receive, from a network, information indicative of a sensing task; obtain sensing related measurements according to the information indicative of the sensing task; determine, based on the sensing related measurements, at least one estimated metric; determine, based on the at least one estimated metric, whether an accuracy for the sensing task has been achieved; andtransmit, to the network, information indicative of whether or not the accuracy for the sensing task has been achieved.

7. A method at a wireless transmit / receive unit, WTRU, the method comprising: receiving, from a network, information indicative of a sensing task and information indicative of at least one trigger condition for reporting; obtaining sensing related measurements according to the information indicative of the sensing task; determining, based on the sensing related measurements, at least one estimated metric; determining respective contributions of the at least one estimated metric to an accuracy of the sensing task; and in case at least one trigger condition is met by a contribution, transmitting, to the network, information indicative of the at least one estimated metric.

8. The method of claim 7, wherein the information indicative of a sensing task comprises at least one of indication of a pilot signal, a time for the sensing task, frequency domain resources, a format of sensing signals, how long to perform the sensing task, and when to report sensing related measurements.

9. The method of claim 7, wherein the sensing related measurements are for at least one of doppler, delay, angles, differentiation single vs multiple bounce from multipath components.

10. A wireless transmit / receive unit, WTRU, comprising at least one processor configured to: receive, from a network, information indicative of a sensing task and information indicative of at least one trigger condition for reporting; obtain sensing related measurements according to the information indicative of the sensing task; determine, based on the sensing related measurements, at least one estimated metric; determine respective contributions of the at least one estimated metric to an accuracy of the sensing task; and in case at least one trigger condition is met by a contribution, transmit, to the network, information indicative of the at least one estimated metric.

11. A method at a wireless transfer / receive unit, WTRU, the method comprising: receiving, from a network, information indicative of a sensing task; obtaining sensing related measurements according to the information indicative of the sensing task; determining, based on the sensing related measurements, at least one estimated metric; executing a plurality of functions, each function taking as input the at least one estimated metric; determining the function among the plurality of functions that best fulfils a set of evaluation criteria; and transmitting, to the network, information indicative of the determined function.

12. The method of claim 11, wherein the information indicative of a sensing task comprises at least one of indication of a pilot signal, a time for the sensing task, frequency domain resources, a format of sensing signals, how long to perform the sensing task, and when to report sensing related measurements.

13. The method of claim 11, wherein the information indicative of a sensing task comprises information related to selection of the plurality of functions from a set of functions.

14. The method of claim 11, wherein the sensing related measurements are for at least one of doppler, delay, angles, differentiation single vs multiple bounce from multipath components.

15. A wireless transmit / receive unit, WTRU, comprising at least one processor configured to: receive, from a network, information indicative of a sensing task; obtain sensing related measurements according to the information indicative of the sensing task; determine, based on the sensing related measurements, at least one estimated metric; execute a plurality of functions, each function taking as input the at least one estimated metric; determine the function among the plurality of functions that best fulfils a set of evaluation criteria; and transmit, to the network, information indicative of the determined function.

16. A method at a wireless transmit / receive unit, WTRU, the method comprising: receiving, from a network, information indicative of a sensing task; obtaining sensing related measurements according to the information indicative of the sensing task; determining, based on the sensing related measurements, at least one estimated metric; determining a first function among a plurality of functions that best fits at least a subset of the measurements according to a first set of evaluation criteria; determining a second function among a plurality of functions that best fits signal-to-noise ratios of at least a subset of the measurements according to a second set of evaluation criteria; and transmitting, to the network, information indicative of the first determined function and the second determined function.

17. The method of claim 16, wherein the information indicative of a sensing task comprises at least one of indication of a pilot signal, a time for the sensing task, frequency domain resources, a format of sensing signals, how long to perform the sensing task, and when to report sensing related measurements.

18. The method of claim 16, wherein the information indicative of a sensing task comprises at least one of information related to a time period for obtaining the sensing related measurements and one or more signal-to-noise ratio thresholds for filtering the sensing related measurements.

19. A wireless transmit / receive unit, WTRU, comprising at least one processor configured to: receive, from a network, information indicative of a sensing task; obtain sensing related measurements according to the information indicative of the sensing task; determine, based on the sensing related measurements, at least one estimated metric; determine a first function among a plurality of functions that best fits at least a subset of the measurements according to a first set of evaluation criteria; determine a second function among a plurality of functions that best fits signal-to-noise ratios of at least a subset of the measurements according to a second set of evaluation criteria; and transmit, to the network, information indicative of the first determined function and the second determined function.

20. A method at a wireless transmit / receive unit, WTRU, the method comprising: receiving, from a network, information indicative of a sensing task and information indicative of at least one trigger condition for reporting; obtaining sensing related measurements according to the information indicative of the sensing task; determining, based on the sensing related measurements, at least one estimated metric; determining whether an accuracy of the at least one estimated metric is not met; determining whether the at least one estimated metric meets the at least one trigger condition for reporting; and in case at least one accuracy is not met and / or the at least one estimated metric meets the at least one trigger condition for reporting: determining, based on at least one communication requirement and at least one sensing task accuracy requirement, a configuration for the sensing task; and transmitting, to the network, information indicative of the determined configuration.

21. The method of claim 20, wherein the information indicative of a sensing task comprises at least one of indication of a pilot signal, a time for the sensing task, frequency domain resources, a format of sensing signals, how long to perform the sensing task, and when to report sensing related measurements.

22. The method of claim 20, wherein the sensing related measurements are for at least one of doppler, delay, angles, differentiation single vs multiple bounce from multipath components.

23. A wireless transmit / receive unit, WTRU, comprising at least one processor configured to: receive, from a network, information indicative of a sensing task and information indicative of at least one trigger condition for reporting; obtain sensing related measurements according to the information indicative of the sensing task; determine, based on the sensing related measurements, at least one estimated metric; determine whether an accuracy of the at least one estimated metric is not met; determine whether the at least one estimated metric meets the at least one trigger condition for reporting; andin case at least one accuracy is not met and / or the at least one estimated metric meets the at least one trigger condition for reporting: determine, based on at least one communication requirement and at least one sensing task accuracy requirement, a configuration for the sensing task; and transmit, to the network, information indicative of the determined configuration.

24. A method at a wireless transmit / receive unit, WTRU, the method comprising: receiving, from a network, information indicative of a sensing task; obtaining sensing related measurements according to the information indicative of the sensing task; determining, based on the sensing related measurements, at least one estimated metric; determining whether samples of the measurements meet at least one quality criterion; predicting, based on whether samples of the measurements meet the at least one quality criterion, a future time window during which samples of the measurements do not meet the at least one quality criterion; estimating whether the sensing task cannot be performed with required accuracy during the future time window; and upon estimating that the sensing task cannot be performed with required accuracy during the future time window, transmitting, to the network, information indicative of the future time window.

25. The method of claim 24, wherein the information indicative of a sensing task comprises at least one of indication of a pilot signal, a time for the sensing task, frequency domain resources, a format of sensing signals, how long to perform the sensing task, and when to report sensing related measurements.

26. The method of claim 24, wherein the at least one quality criterion is a threshold for signal-to- noise ratio or for root mean square error.

27. A wireless transmit / receive unit, WTRU, comprising at least one processor configured to: receive, from a network, information indicative of a sensing task; obtain sensing related measurements according to the information indicative of the sensing task; determine, based on the sensing related measurements, at least one estimated metric;determine whether samples of the measurements meet at least one quality criterion; predict, based on whether samples of the measurements meet the at least one quality criterion, a future time window during which samples of the measurements do not meet the at least one quality criterion; estimate whether the sensing task cannot be performed with required accuracy during the future time window; and upon estimating that the sensing task cannot be performed with required accuracy during the future time window, transmit, to the network, information indicative of the future time window.

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