Joint path and sample based measurement reporting for ai / ML positioning

Abstract

Aspects presented herein may improve the overall performance of artificial intelligence (AI) or machine learning (ML) (AI / ML) positioning by enabling a wireless device (e.g., a user equipment (UE), a base station, or a transmission reception point (TRP), etc.) to consider and report measurements observed from the time-domain channel response (e.g., the sample-based measurements). For example, in one aspect of the present disclosure, a wireless device receives, from a network entity, a request to perform a set of measurements for an AI / ML input, where the request includes a list of desired measurement schemes. The wireless device performs the set of measurements for the AI / ML input using at least one measurement scheme in the list of desired measurement schemes. The wireless device transmits, to the network entity, the set of measurements for the AI / ML input and an indication of the at least one measurement scheme.

Description

JOINT PATH AND SAMPLE BASED MEASUREMENT REPORTING FOR AI / ML POSITIONINGCROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims the benefit of Greece Patent Application No. 20250100012, entitled “JOINT PATH AND SAMPLE BASED MEASUREMENT REPORTING FOR AI / ML POSITIONING” and filed on January 8, 2025, which is expressly incorporated by reference herein in its entirety.TECHNICAL FIELD

[0002] The present disclosure relates generally to communication systems, and more particularly, to wireless communication involving artificial intelligence (Al) or machine learning (ML) (AI / ML) positioning or sensing.INTRODUCTION

[0003] Wireless communication systems are widely deployed to provide various telecommunication services such as telephony, video, data, messaging, and broadcasts. Typical wireless communication systems may employ multiple-access technologies capable of supporting communication with multiple users by sharing available system resources. Examples of such multiple-access technologies include code division multiple access (CDMA) systems, time division multiple access (TDMA) systems, frequency division multiple access (FDMA) systems, orthogonal frequency division multiple access (OFDMA) systems, single-carrier frequency division multiple access (SC-FDMA) systems, and time division synchronous code division multiple access (TD-SCDMA) systems.

[0004] These multiple access technologies have been adopted in various telecommunication standards to provide a common protocol that enables different wireless devices to communicate on a municipal, national, regional, and even global level. An example telecommunication standard is 5G New Radio (NR). 5G NR is part of a continuous mobile broadband evolution promulgated by Third Generation Partnership Project (3 GPP) to meet new requirements associated with latency, reliability, security, scalability (e.g., with Internet of Things (IoT)), and other requirements. 5G NR includes services associated with enhanced mobile broadband (eMBB), massive129025-2490W001machine type communications (mMTC), and ultra-reliable low latency communications (URLLC). Some aspects of 5G NR may be based on the 4G Long Term Evolution (LTE) standard. There exists a need for further improvements in 5G NR technology. These improvements may also be applicable to other multi-access technologies and the telecommunication standards that employ these technologies.

[0005] Some telecommunication standards also provide positioningprotocols and techniques that enable mobile network operators to provide high-accuracy location services to their subscribers. For example, 5GNR include various standards for network-based positioning that use signals and featuresof the 5Gnetwork to perform or improve the positioning of a device. There also exists a need for further improvements in these positioning protocols and techniques.BRIEF SUMMARY

[0006] The following presents a simplified summary of one or more aspects in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects. This summary neither identifies key or critical elements of all aspects nor delineates the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that is presented later.

[0007] In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus receives, from a network entity, a request to perform a set of measurements for an artificial intelligence (Al) or machine learning (ML) (AI / ML) input, where the request includes a list of desired measurement schemes. The apparatus performs the set of measurements for the AI / ML input using at least one measurement scheme in the list of desired measurement schemes. The apparatus transmits, to the network entity, the set of measurements for the AI / ML input and an indication of the at least one measurement scheme.

[0008] In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus transmits, to a wireless device, a request to perform a set of measurements for an AI / ML input, where the request includes a list of desired measurement schemes. The apparatus receives, from the wireless device,129025-2490W001the set of measurements for the AI / ML input and an indication of at least one measurement scheme associated with the wireless device forthe set of measurements.

[0009] To the accomplishment of the foregoing and related ends, the one or more aspects may include the features hereinafter fully described and particularly pointed out in the claims. The following description and the drawings set forth in detail certain illustrative features of the one or more aspects. These features are indicative, however, of but a few of the various ways in which the principles of various aspects may be employed.BRIEF DESCRIPTION OF THE DRAWINGS

[0010] FIG. l is a diagram illustrating an example of a wireless communications system and an access network.

[0011] FIG. 2A is a diagram illustrating an example of a first frame, in accordance with various aspects of the present disclosure.

[0012] FIG. 2B is a diagram illustrating an example of downlink (DL) channels within a subframe, in accordance with various aspects of the present disclosure.

[0013] FIG. 2C is a diagram illustrating an example of a second frame, in accordance with various aspects of the present disclosure.

[0014] FIG. 2D is a diagram illustrating an example of uplink (UL) channels within a subframe, in accordance with various aspects of the present disclosure.

[0015] FIG. 3 is a diagram illustrating an example of a base station and user equipment (UE) in an access network.

[0016] FIG. 4 is a diagram illustrating an example of a UE positioning based on reference signal measurements (which may also be referred to as "network -based positioning") in accordance with various aspects of the present disclosure.

[0017] FIG. 5 is a diagram illustrating an example radio access technology (RAT)-dependent positioning in accordance with various aspects of the present disclosure.

[0018] FIG. 6A is a diagram illustrating an example of direct artificial intelligence (Al) or machine learning (ML) (AI / ML) positioning in accordance with various aspects of the present disclosure.

[0019] FIG. 6B is a diagram illustrating an example of AI / ML assisted positioning in accordance with various aspects of the present disclosure.129025-2490W001

[0020] FIG. 7 is a diagram illustrating an example of UE-based positioning with a UE-side AI / ML model, direct AI / ML or AI / ML assisted positioning in accordance with various aspects of the present disclosure.

[0021] FIG. 8 A is a diagram illustrating an example of UE-assisted / location management function (LMF)-based positioning with a UE-side AI / ML model, AI / ML assisted positioning in accordance with various aspects of the present disclosure.

[0022] FIG. 8B is a diagram illustrating an example of UE-assisted / LMF-based positioning with an LMF-side AI / ML model, direct AI / ML positioning in accordance with various aspects of the present disclosure.

[0023] FIG. 9A is a diagram illustrating an example of network node assisted positioning with a base station (gNB)-side AI / ML model, AI / ML assisted positioning in accordance with various aspects of the present disclosure.

[0024] FIG. 9B is a diagram illustrating an example of network node assisted positioning with LMF-side AI / ML model, direct AI / ML positioning in accordance with various aspects of the present disclosure.

[0025] FIG. 10 is a diagram illustrating an example sample-based measurement in accordance with various aspects of the present disclosure.

[0026] FIG. 11 is a diagram illustrating an example structure of a path and additional path measurement report in accordance with various aspects of the present disclosure.

[0027] FIG. 12 is a communicationflowillustratingan example signalingforjointpath-based measurement and sample-based measurement reporting for AI / ML positioning in accordance with various aspects of the present disclosure.

[0028] FIG. 13 is a flowchart of a method of wireless communication.

[0029] FIG. 14 is a flowchart of a method of wireless communication.

[0030] FIG. 15 is a diagram illustrating an example of a hardware implementation for an example apparatus and / or network entity.

[0031] FIG. 16 is a diagram illustrating an example of a hardware implementation for an example network entity.

[0032] FIG. 17 is a flowchart of a method of wireless communication.

[0033] FIG. 18 is a diagram illustrating an example of a hardware implementation for an example network entity.DETAILED DESCRIPTION129025-2490W001

[0034] Aspects presented herein may improve the overall performance of artificial intelligence (Al) or machine learning (ML) (AI / ML) positioning by enabling a wireless device (e.g., a user equipment (UE), a base station, or a transmission reception point (TRP), etc.) to consider and report measurements observed from the time-domain channel response (e.g., the sample-based measurements). For example, a wireless device may be configured to support the path-based measurement scheme and / or the sample-based measurement scheme for AI / ML input running at a location server side (e.g., running at a location management function (LMF) such as described in connection with FIGs. 8B and 9B). The wireless device and the location server may be configured to exchange signaling on whether the wireless device is able to support “path-only” (e.g., just capable of performingthe path-based measurement), sample- only (e.g., just capable of performingthe sample-based measurement), or joint path and sample measurement reporting (e.g., capable of performing both the samplebased measurement and the path-based measurement). For example, depending on implementations, a wireless device may be configured to indicate its capabilities on supported measurement schemes (including support for their joint operation) to a location server. The wireless device may also be configured to indicate the applicable measurement schemes. The location server may signal the wireless device a set of specified / desired measurement schemes, and / or prioritization / conditioning for a set of measurement schemes. In addition, the wireless device may report measurements with additional indicator on selected measurement scheme and parameters (or priority / condition found for the scheme the wireless device selects).

[0035] The detailed description set forth below in connection with the drawings describes various configurations and does not represent the only configurations in which the concepts described hereinmay be practiced. The detailed description includes specific details for the purpose of providing a thorough understanding of various concepts. However, these concepts may be practiced without these specific details. In some instances, well known structures and components are shown in block diagram form in order to avoid obscuring such concepts.

[0036] Several aspects of telecommunication systems are presented with referenceto various apparatus and methods. These apparatus and methods are described in the following detailed description and illustrated in the accompanying drawings by various blocks, components, circuits, processes, algorithms, etc. (collectively referred to as129025-2490W001“elements”). These elements may be implemented using electronic hardware, computer software, or any combination thereof. Whether such elements are implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system.

[0037] By way of example, an element, or any portion of an element, or any combination of elements may be implemented as a “processing system” that includes one or more processors. When multiple processors are implemented, the multiple processors may perform the functions individually or in combination. Examples of processors include microprocessors, microcontrollers, graphics processing units (GPUs), central processing units (CPUs), application processors, digital signal processors (DSPs), reduced instruction set computing (RISC) processors, systems on a chip (SoC), baseband processors, field programmable gate arrays (FPGAs), programmable logic devices (PLDs), state machines, gated logic, discrete hardware circuits, and other suitable hardware configured to perform the various functionality described throughout this disclosure. One or more processors in the processing system may execute software. Software, whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise, shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software components, applications, software applications, software packages, routines, subroutines, objects, executables, threads of execution, procedures, functions, or any combination thereof.

[0038] Accordingly, in one or more example aspects, implementations, and / or use cases, the functions described may be implemented in hardware, software, or any combination thereof. If implementedin software, the functions may b e stored on or encoded as one or more instructions or code on a computer-readable medium. Computer-readable media includes computer storage media. Storage media may be any available media that can be accessed by a computer. By way of example, such computer-readable media can include a random-access memory (RAM), a read-only memory (ROM), an electrically erasable programmable ROM (EEPROM), optical disk storage, magnetic disk storage, other magnetic storage devices, combinations of the types of computer- readable media, or any other medium that can be used to store computer executable code in the form of instructions or data structures that can be accessed by a computer.129025-2490W001

[0039] While aspects, implementations, and / or use cases are describedin this application by illustration to some examples, additional or different aspects, implementations and / or use cases may come about in many different arrangements and scenarios. Aspects, implementations, and / oruse cases described herein may be implemented across many differingplatform types, devices, systems, shapes, sizes, and packaging arrangements. For example, aspects, implementations, and / or use cases may come about via integrated chip implementations and other non-module-component based devices (e.g., end-user devices, vehicles, communication devices, computing devices, industrial equipment, retail / purchasing devices, medical devices, artificial intelligence (Al)-enabled devices, etc.). While some examples may or may not be specifically directed to use cases or applications, a wide assortment of applicability of described examples may occur. Aspects, implementations, and / oruse cases may range a spectrum from chip-level or modular components to non-modular, non-chip- level implementations and further to aggregate, distributed, or original equipment manufacturer (OEM) devices or systems incorp oratingone or more techniques herein. In some practical settings, devices incorporating described aspects and features may also include additional components and features for implementation and practice of claimed and described aspect. For example, transmission and reception of wireless signals necessarily includes a number of components for analog and digital purposes (e.g., hardware components including antenna, RF-chains, power amplifiers, modulators, buffer, processor(s), interleaver, adders / summers, etc.). Techniques described herein may be practiced in a wide variety of devices, chip-level components, systems, distributed arrangements, aggregated or disaggregated components, end-user devices, etc. of varying sizes, shapes, and constitution.

[0040] Deployment of communication systems, such as 5GNR systems, may be arranged in multiple manners with various components or constituent parts. In a 5G NR system, or network, a network node, a network entity, a mobility element of a network, a radio access network (RAN) node, a core network node, a network element, or a network equipment, such as a base station (BS), or one or more units (or one or more components) performing base station functionality, may be implemented in an aggregated or disaggregated architecture. For example, a BS (such as a Node B (NB), evolved NB (eNB), NR BS, 5GNB, access point (AP), a transmission reception point129025-2490W001(TRP), or a cell, etc.) may be implemented as an aggregated base station (also known as a standalone BS or a monolithic BS) or a disaggregated base station.

[0041] An aggregated base station may be configured to utilize a radio protocol stack that is physically or logically integrated within a single RAN node. A disaggregated base station may be configured to utilize a protocol stack that is physically or logically distributed among two or more units (such as one or more central or centralized units (CUs), one or more distributed units (DUs), or one or more radio units (RUs)). In some aspects, a CU may be implemented within a RAN node, and one or more DUs may be co-located with the CU, or alternatively, may be geographically or virtually distributed throughout one or multiple other RAN nodes. The DUs may be implemented to communicate with one or more RUs. Each of the CU, DU and RU can be implemented as virtual units, i.e., a virtual central unit (VCU), a virtual distributed unit (VDU), or a virtual radio unit (VRU).

[0042] Base station operation or network design may consider aggregation characteristics of base station functionality. For example, disaggregated base stations may be utilized in an integrated access backhaul (IAB) network, an open radio access network (O- RAN (such as the network configuration sponsored by the O-RAN Alliance)), or a virtualized radio access network (vRAN, also known as a cloud radio access network (C-RAN)). Disaggregation may include distributing functionality across two or more units at various physical locations, as well as distributing functionality for at least one unit virtually, which can enable flexibility in network design. The various units of the disaggregated base station, or disaggregated RAN architecture, can be configured for wired or wireless communication with at least one other unit.

[0043] FIG. 1 is a diagram 100 illustrating an example of a wireless communications system and an access network. The illustrated wireless communications system includes a disaggregated base station architecture. The disaggregated base station architecture may include one or more CUs 110 that can communicate directly with a core network 120 via a backhaul link, or indirectly with the core network 120 through one or more disaggregated base station units (such as a Near-Real Time (Near-RT) RAN Intelligent Controller (RIC) 125 via an E2 link, or a Non-Real Time (Non-RT) RIC 115 associated with a Service Management and Orchestration (SMO) Framework 105, or both). A CU 110 may communicate with one or more DUs 130 via respective midhaul links, such as an Fl interface. The DUs 130 may communicate with one or129025-2490W001more RUs 140 via respective fronthaul links. The RUs 140 may communicate with respective UEs 104 via one or more radio frequency (RF) access links. In some implementations, theUE 104 may be simultaneously served by multiple RUs 140.

[0044] Each of the units, i.e., the CUs 110, theDUs 130, the RUs 140, as well as theNear- RT RICs 125, the Non-RT RICs 115, and the SMO Framework 105, may include one or more interfaces or be coupled to one or more interfaces configured to receive or to transmit signals, data, or information (collectively, signals) via a wired or wireless transmission medium. Each of the units, or an associated processor or controller providing instructions to the communication interfaces of the units, can be configured to communicate with one or more of the other units via the transmission medium. For example, the units can include a wired interface configured to receive or to transmit signals over a wired transmission medium to one or more of the other units. Additionally, the units can include a wireless interface, which may include a receiver, a transmitter, or a transceiver (such as an RF transceiver), configured to receive or to transmit signals, or both, over a wireless transmission medium to one or more of the other units.

[0045] In some aspects, the CU 110 may host one or more higher layer control functions.Such control functions can include radio resource control (RRC), packet data convergence protocol (PDCP), service data adaptation protocol (SDAP), or the like. Each control function can be implemented with an interface configured to communicate signals with other control functions hosted by the CU 110. The CU 110 may be configured to handle user plane functionality (i.e., Central Unit - User Plane (CU-UP)), control plane functionality (i.e., Central Unit - Control Plane (CU-CP)), or a combination thereof. In some implementations, theCU 110 can be logically split into one or more CU-UP units and one or more CU-CP units. The CU-UP unit can communicate bidirectionally with the CU-CP unit via an interface, such as an El interface when implemented in an O-RAN configuration. The CU 110 can be implemented to communicate with the DU 130, as necessary, for network control and signaling.

[0046] The DU 130 may correspond to a logical unit that includes one or more base station functions to control the operation of one or more RUs 140. In some aspects, the DU 130 may host one or more of a radio link control (RLC) layer, a medium access control (MAC) layer, and one or more high physical (PHY) layers (such as modules for129025-2490W001forward error correction (FEC) encoding and decoding, scrambling, modulation, demodulation, or the like) depending, at least in part, on a functional split, such as those defined by 3 GPP. In some aspects, the DU 130 may further host one or more low PHY layers. Each layer (or module) can be implemented with an interface configured to communicate signals with other layers (and modules) hosted by the DU 130, or with the control functions hosted by the CU 110.

[0047] Lower-layer functionality can be implemented by one or more RUs 140. In some deployments, an RU 140, controlled by a DU 130, may correspond to a logical node that hosts RF processing functions, or low-PHY layer functions (such as performing fast Fourier transform (FFT), inverse FFT (iFFT), digital beamforming, physical random access channel (PRACH) extraction and filtering, or the like), or both, based at least in part on the functional split, such as a lower layer functional split. In such an architecture, the RU(s) 140 can be implemented to handle over the air (OTA) communication with one or more UEs 104. In some implementations, real-time and non-real-time aspects of control and user plane communication with the RU(s) 140 can be controlled by the corresponding DU 130. In some scenarios, this configuration can enable the DU(s) 130 and the CU 110 to be implemented in a cloud-based RAN architecture, such as a vRAN architecture.

[0048] The SMO Framework 105 may be configured to support RAN deployment and provisioning of non-virtualizedandvirtualizednetwork elements. Fornon-virtualized network elements, the SMO Framework 105 may be configured to support the deployment of dedicated physical resources for RAN coverage requirements that may be managed via an operations and maintenance interface (such as an 01 interface). For virtualized network elements, the SMO Framework 105 may be configured to interact with a cloud computing platform (such as an open cloud (O-Cloud) 190) to perform network element life cycle management (such as to instantiate virtualized network elements) via a cloud computing platform interface (such as an 02 interface). Such virtualized network elements can include, but are not limited to, CUs 110, DUs 130, RUs 140andNear-RTRICs 125. In some implementations, the SMO Framework 105 can communicate with a hardware aspect of a 4G RAN, such as an open eNB (O- eNB) 111, via an 01 interface. Additionally, in some implementations, the SMO Framework 105 can communicate directly with one or more RUs 140 via an 01129025-2490W001interface. The SMO Framework 105 also may include aNon-RTRIC 115 configured to support functionality of the SMO Framework 105.

[0049] The Non-RT RIC 115 may be configured to include a logical function that enables non-real-time control and optimization of RAN elements and resources, artificial intelligence (Al) / machine learning (ML) (AI / ML) workflows including model training and updates, or policy -based guidance of applications / features in the Near- RT RIC 125. The Non-RT RIC 115 may be coupled to or communicate with (such as via an Al interface) the Near-RT RIC 125. TheNear-RTRIC 125 may be configured to include a logical function that enables near-real-time control and optimization of RAN elements and resources via dataset collection and actions over an interface (such as via an E2 interface) connecting one or more CUs 110, one or more DUs 130, or both, as well as an O-eNB, with the Near-RT RIC 125.

[0050] In some implementations, to generate AI / ML models to be deployed in the Near-RT RIC 125, the Non-RT RIC 115 may receive parameters or external enrichment information from external servers. Such information may be utilized by the Near-RT RIC 125 and may be received at the SMO Framework 105 or the Non-RT RIC 115 from non-network data sources or from network functions. In some examples, the Non-RTRIC 115 or the Near-RT RIC 125 may be configured to tune RAN behavior or performance. For example, the Non-RT RIC 115 may monitor long-term trends and patterns for performance and employ AI / ML models to perform corrective actions through the SMO Framework 105 (such as reconfiguration via 01) or via creation of RAN management policies (such as Al policies).

[0051] At least one of the CU 110, the DU 130, and the RU 140 maybe referred to as abase station 102. Accordingly, abase station 102 may include one ormore ofthe CU 110, the DU 130, and the RU 140 (each component indicated with dotted lines to signify that each component may or may not be included in the base station 102). The base station 102 provides an access point to the core network 120 for aUE 104. The base station 102 may include macrocells (high power cellular base station) and / or small cells (low power cellular base station). The small cells include femtocells, picocells, and microcells. A network that includes both small cell and macrocells may be known as a heterogeneous network. A heterogeneous network may also include Home Evolved Node Bs (eNBs) (HeNBs), which may provide service to a restricted group known as a closed subscriber group (CSG). The communication links between the129025-2490W001RUs 140 and the UEs 104 may include uplink (UL) (also referred to as reverse link) transmissions fromaUE 104 to an RU 140 and / or downlink (DL) (also referred to as forward link) transmissions from an RU 140 to aUE 104. The communication links may use multiple-input and multiple-output (MIMO) antenna technology, including spatial multiplexing, beamforming, and / or transmit diversity. The communication links may be through one or more carriers. The base station 102 / UEs 104 may use spectrum up to FMHz (e.g., 5, 10, 15, 20, 100, 400, etc. MHz) bandwidth per carrier allocated in a carrier aggregation of up to a total of Fx MHz (x component carriers) used for transmission in each direction. The carriers may or may not be adjacent to each other. Allocation of carriers may be asymmetric with respecttoDL andUL (e.g., more or fewer carriers may be allocated for DL than for UL). The component carriers may include a primary component carrier and one or more secondary component carriers. A primary component carrier may be referred to as a primary cell(PCell) and a secondary component carrier may be referred to as a secondary cell (SCell).

[0052] Certain UEs 104 may communicate with each other using device-to-device (D2D) communication link 158. The D2D communication link 158 may use the DL / UL wireless wide area network (WWAN) spectrum. TheD2D communication link 158 may use one or more sidelink channels, such as a physical sidelink broadcast channel (PSBCH), a physical sidelink discovery channel (PSDCH), a physical sidelink shared channel (PSSCH), and a physical sidelink control channel (PSCCH). D2D communication may be through a variety of wireless D2D communications systems, such as for example, Bluetooth™ (Bluetooth is a trademark of the Bluetooth Special Interest Group (SIG)), Wi-Fi™ (Wi-Fi is a trademark of the Wi-Fi Alliance) based on the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standard, LTE, or NR.

[0053] The wireless communications system may further include a Wi-Fi AP 150 in communication with UEs 104 (also referred to as Wi-Fi stations (STAs)) via communication link 154, e.g., in a 5 GHz unlicensed frequency spectrum orthe like. When communicating in an unlicensed frequency spectrum, the UEs 104 / AP 150 may perform a clear channel assessment (CCA) prior to communicating in order to determine whether the channel is available.

[0054] The electromagnetic spectrum is often subdivided, based on frequency / wavelength, into various classes, bands, channels, etc. In 5GNR, two initial operating bands have129025-2490W001been identified as frequency range designations FR1 (410 MHz - 7.125 GHz) and FR2 (24.25 GHz - 52.6 GHz). Although a portion of FR1 is greater than 6 GHz, FR1 is often referred to (interchangeably) as a “sub-6 GHz” band in various documents and articles. A similar nomenclature issue sometimes occurs with regard to FR2, which is often referred to (interchangeably) as a “millimeter wave” bandin documents and articles, despite being different from the extremely high frequency (EHF) band (30 GHz - 300 GHz) which is identified by the International Telecommunications Union (ITU) as a “millimeter wave” band.

[0055] The frequencies between FR1 andFR2 are often referred to as mid-band frequencies.Recent 5G NR studies have identified an operating band for these mid-band frequencies as frequency range designation FR3 (7.125 GHz - 24.25 GHz). Frequency bands falling within FR3 may inherit FR1 characteristics and / or FR2 characteristics, and thus may effectively extend features of FR1 and / or FR2 into midband frequencies. In addition, higher frequency bands are currently being explored to extend 5 G NR op eration b ey ond 52.6 GHz . For example, three higher op erating b ands have been identified as frequency range designations FR2-2 (52.6 GHz - 71 GHz), FR4 (71 GHz- 114.25 GHz), andFR5 (114.25 GHz- 300 GHz). Each of these hi^ier frequency bands falls within the EHF band.

[0056] With the above aspects in mind, unless specifically stated otherwise, the term “sub-6GHz” or the like if used herein may broadly represent frequencies that may be less than 6 GHz, may be within FR1 , or may include mid-band frequencies. Further, unless specifically stated otherwise, the term “millimeter wave” or the like if used herein may broadly represent frequencies that may include mid-band frequencies, may be within FR2, FR4, FR2-2, and / or FR5, or may be within the EHF band.

[0057] The base station 102 and the UE 104 may each include a plurality of antennas, such as antenna elements, antenna panels, and / or antenna arrays to facilitate beamforming The base station 102 may transmit a beamformed signal 182 to the UE 104 in one or more transmit directions. The UE 104 may receive the beamformed signal from the base station 102 in one or more receive directions. The UE 104 may also transmit a beamformed signal 184 to the base station 102 in one or more transmit directions. The base station 102 may receive the beamformed signal from the UE 104 in one or more receive directions. The base station 102 / UE 104 may perform beam training to determine the best receive and transmit directions for each of the base station 102 / 129025-2490W001UE 104. The transmit and receive directions for the base station 102 may or may not be the same. The transmit and receive directions for the UE 104 may or may not be the same.

[0058] The base station 102 may include and / or be referred to as a gNB, Node B, eNB, an access point, a base transceiver station, a radio base station, a radio transceiver, a transceiver function, a basic service set (BSS), an extended service set (ESS), a TRP, network node, the network entity, network equipment, or some other suitable terminology. The base station 102 can be implemented as an integrated access and backhaul (IAB) node, a relay node, a sidelink node, an aggregated (monolithic) base station with a baseband unit (BBU) (including a CU and a DU) and an RU, or as a disaggregated base station including one or more of a CU, a DU, and / or an RU. The set of base stations, which may include disaggregated base stations and / or aggregated base stations, may be referred to as next generation (NG) RAN (NG-RAN).

[0059] The core network 120 may include an Access and Mobility Management Function (AMF) 161, a Session Management Function (SMF) 162, a User Plane Function (UPF) 163, a Unified Data Management (UDM) 164, one or more location servers 168, and other functional entities. The AMF 161 is the control node that processes the signaling between the UEs 104 and the core network 120. The AMF 161 supports registration management, connection management, mobility management, and other functions. The SMF 162 supports session management and other functions. The UPF 163 supports packet routing, packet forwarding, and other functions. The UDM 164 supports the generation of authentication and key agreement (AKA) credentials, user identification handling, access authorization, and subscription management. The one or more location servers 168 are illustrated as including a Gateway Mobile Location Center (GMLC) 165 and a Location Management Function (LMF) 166. However, generally, the one or more location servers 168 may include one or more location / positioning servers, which may include one or more of the GMLC 165, the LMF 166, a position determination entity (PDE), a serving mobile location center (SMLC), a mobile positioning center (MPC), or the like. The GMLC 165 and the LMF 166 support UE location services. The GMLC 165 provides an interface for clients / applications (e.g., emergency services) for accessing UE positioning information. The LMF 166 receives measurements and assistance information from the NG-RAN and the UE 104 via the AMF 161 to compute the position of the UE129025-2490W001104. TheNG-RAN may utilize one or more positioning methods in orderto determine the position of the UE 104. Positioningthe UE 104 may involve signal measurements, a position estimate, and an optional velocity computation based on the measurements. The signal measurements may be made by the UE 104 and / or the base station 102 serving the UE 104. The signals measured may be based on one or more of a satellite positioning system (SPS) 170 (e.g., one or more of a Global Navigation Satellite System (GNSS), global position system (GPS), non-terrestrial network (NTN), or other satellite position / location system), LTE signals, wireless local area network (WLAN) signals, Bluetooth signals, a terrestrial beacon system (TBS), sensor-based information (e.g., barometric pressure sensor, motion sensor), NR enhanced cell ID (NRE-CID) methods, NRsignals(e.g., multi-round trip time (Multi-RTT), DL angle- of-departure (DL-AoD), DL time difference of arrival (DL-TDOA), UL time difference of arrival (UL-TDOA), and UL angle-of-arrival (UL-AoA) positioning), and / or other systems / signals / sensors.

[0060] Examples of UEs 104 include a cellular phone, a smartphone, a session initiation protocol (SIP) phone, a laptop, a personal digital assistant (PDA), a satellite radio, a global positioning system, a multimedia device, a video device, a digital audio player (e.g., MP3 player), a camera, a game console, a tablet, a smart device, a wearable device, a vehicle, an electric meter, a gas pump, a large or small kitchen appliance, a healthcare device, an implant, a sensor / actuator, a display, or any other similar functioning device. Some of the UEs 104 may be referred to as loT devices (e.g, parking meter, gas pump, toaster, vehicles, heart monitor, etc.). TheUE 104 may also be referred to as a station, a mobile station, a subscriber station, a mobile unit, a subscriber unit, a wireless unit, a remote unit, a mobile device, a wireless device, a wireless communications device, a remote device, a mobile subscriber station, an access terminal, a mobile terminal, a wireless terminal, a remote terminal, a handset, a user agent, a mobile client, a client, or some other suitable terminology. In some scenarios, the term UE may also apply to one or more companion devices such as in a device constellation arrangement. One or more of these devices may collectively access the network and / or individually access the network.

[0061] Referring again to FIG. 1, in certain aspects, the UE 104 may have a measurement scheme indication component 198 that may be configured to receive, from a network entity, a request to perform a set of measurements for an AI / ML input, where the129025-2490W001request includes a list of desired measurement schemes; perform the set of measurements for the AI / ML input using at least one measurement scheme in the list of desired measurement schemes; and transmit, to the network entity, the set of measurements for the AI / ML input and an indication of the at least one measurement scheme. In certain aspects, the base station 102 may have a measurement scheme indication component 199 that may be configured to receive, from a network entity, a request to perform a set of measurements for an AI / ML input, where the request includes a list of desired measurement schemes; perform the set of measurements for the AI / ML input using at least one measurement scheme in the list of desired measurement schemes; and transmit, to the network entity, the set of measurements for the AI / ML input and an indication of the at least one measurement scheme. In certain aspects, the one or more location servers 168 may have a measurement scheme configuration component 197 thatmay be configured to transmit, to a wireless device, a request to perform a set of measurements for an AI / ML input, where the request includes a list of desired measurement schemes; and receive, fromthe wireless device, the set of measurements for the AI / ML input and an indication of at least one measurement scheme associated with the wireless device for the set of measurements.

[0062] FIG. 2 A is a diagram 200 illustrating an example of a first subframe within a 5GNR frame structure. FIG. 2B is a diagram 230 illustrating an example of DL channels within a 5G NR subframe. FIG. 2C is a diagram 250 illustrating an example of a second subframe within a 5G NR frame structure. FIG. 2D is a diagram 280 illustrating an example of UL channels within a 5 G NR subframe. The 5 G NR frame structure may be frequency division duplexed (FDD) in which for a particular set of subcarriers (carrier system bandwidth), subframes within the set of subcarriers are dedicated for either DL or UL, or may be time division duplexed (TDD) in which for a particular set of subcarriers (carrier system bandwidth), subframes within the set of subcarriers are dedicated for both DL andUL. In the examples provided by FIGs. 2A, 2C, the 5G NR frame structure is assumed to be TDD, with subframe 4 being configured with slot format 28 (with mostly DL), where D is DL, U is UL, and F is flexible for use between DL / UL, and subframe 3 being configured with slot format 1 (with all UL). While subframes 3, 4 are shown with slot formats 1, 28, respectively, any particular subframe may be configured with any of the various available slot formats 0-61. Slot formats 0, 1 are all DL, UL, respectively. Other slot formats 2-61129025-2490W001include a mix of DL, UL, and flexible symbols. UEs are configured with the slot format (dynamically through DL control information (DCI), or semi- statically / statically through radio resource control (RRC) signaling) through a received slot format indicator (SFI). Note that the description infra applies also to a 5G NR frame structure that is TDD.

[0063] FIGs. 2 A-2D illustrate a frame structure, and the aspects of the present disclosure may be applicable to other wireless communication technologies, which may have a different frame structure and / or different channels. A frame (10 ms) may be divided into 10 equally sized subframes (1 ms). Each subframe may include one or more time slots. Subframes may also include mini-slots, which may include 7, 4, or 2 symbols. Each slot may include 14 or 12 symbols, depending on whether the cyclic prefix (CP) is normal or extended. For normal CP, each slot may include 14 symbols, and for extended CP, each slot may include 12 symbols. The symbols on DL may be CP orthogonal frequency division multiplexing (OFDM) (CP-OFDM) symbols. The symbols on UL may be CP-OFDM symbols (for high throughput scenarios) or discrete Fourier transform (DFT) spread OFDM (DFT-s-OFDM) symbols (for power limited scenarios; limited to a single stream transmission). The number of slots within a subframe is based on the CP and the numerology. The numerology defines the subcarrier spacing (SCS) (see Table 1). The symbol length / duration may scale with 1 / SCS.Table 1: Numerology, SCS, and CP

[0064] For normal CP (14 symbols / slot), different numerologies p 0 to 4 allowfor 1, 2, 4, 8, and 16 slots, respectively, per subframe. For extended CP, the numerology 2 allows129025-2490W001for 4 slots per subframe. Accordingly, for normal CP and numerology p, there are 14 symbols / slot and 2.Llsi ots / sub frame. The subcarrier spacing may be equal to 2^ * 15 kHz, where . is the numerology 0 to 4. As such, the numerology p=0 has a subcarrier spacing of 15 kHz and the numerology p=4 has a subcarrier spacing of 240 kHz. The symbol length / durationis inversely related to the subcarrier spacing. FIGs.2A-2D provide an example of normal CP with 14 symbols per slot and numerology p=2 with 4 slots per subframe. The slot duration is 0.25 ms, the subcarrier spacing is 60 kHz, and the symbol duration is approximately 16.67 ps. Within a set of frames, there may be one or more different bandwidth parts (BWPs) (see FIG. 2B) that are frequency division multiplexed. Each BWP may have a particular numerology and CP (normal or extended).

[0065] A resource grid may be used to represent the frame structure. Each time slot includes a resource block (RB) (also referred to as physical RBs (PRBs)) that extends 12 consecutive subcarriers. The resource grid is divided into multiple resource elements (REs). The number of bits carried by each RE depends on the modulation scheme.

[0066] As illustrated in FIG. 2 A, some of the REs carry reference (pilot) signals (RS) for the UE. The RS may include demodulation RS (DM-RS) (indicated as Rfor one particular configuration, but other DM-RS configurations are possible) and channel state information reference signals (CSI-RS) for channel estimation attheUE. The RS may also include beam measurement RS (BRS), beam refinement RS (BRRS), and phase tracking RS (PT-RS).

[0067] FIG. 2B illustrates an example of various DL channels within a subframe of a frame.The physical downlink control channel (PDCCH) carries DCI within one or more control channel elements (CCEs) (e.g., 1, 2, 4, 8, or 16 CCEs), each CCE including six RE groups (REGs), each REG including 12 consecutive REs in an OFDM symbol of an RB. A PDCCH within one BWP may be referred to as a control resource set (CORESET). A UE is configured to monitor PDCCH candidates in a PDCCH search space (e.g., common search space, UE-specific search space) during PDCCH monitoring occasions on the CORESET, where the PDCCH candidates have different DCI formats and different aggregation levels. Additional BWPs may be located at greater and / or lower frequencies across the channel bandwidth. A primary synchronization signal (PSS) may be within symbol 2 of particular subframes of a frame. The PSS is used by a UE 104 to determine subframe / symbol timing and a129025-2490W001physical layer identity. A secondary synchronization signal (SSS) may be within symbol 4 of particular subframes of a frame. The SSS is used by a UE to determine a physical layer cell identity group number and radio frame timing. Based on the physical layer identity and the physical layer cell identity group number, the UE can determine a physical cell identifier (PCI). Based on the PCI, the UE can determine the locations of the DM-RS. The physical broadcast channel (PBCH), which carries a master information block (MIB), may be logically grouped with the PSS and SSS to form a synchronization signal (SS) / PBCH block (also referred to as SS block (SSB)). The MIB provides a number of RBs in the system bandwidth and a system frame number (SFN). The physical downlink shared channel (PDSCH) carries user data, broadcast system information not transmitted through the PBCH such as system information blocks (SIBs), and paging messages.

[0068] As illustrated in FIG. 2C, some of the REs carry DM-RS (indicated as R for one particular configuration, but other DM-RS configurations are possible) for channel estimation at the base station. The UE may transmit DM-RS for the physical uplink control channel (PUCCH) and DM-RS for the physical uplink shared channel (PUSCH). The PUSCH DM-RS may be transmitted in the first one or two symbols of the PUSCH. The PUCCH DM-RS may be transmitted in different configurations depending on whether short or long PUCCHs are transmitted and depending on the particular PUCCH format used. The UE may transmit sounding reference signals (SRS). The SRS may be transmitted in the last symbol of a subframe. The SRS may have a comb structure, and a UE may transmit SRS on one of the combs. The SRS may be used by a base station for channel quality estimation to enable frequencydependent scheduling on the UL.

[0069] FIG. 2D illustrates an example of various UL channels within a subframe of a frame.The PUCCH may be located as indicated in one configuration. The PUCCH carries uplink control information (UCI), such as scheduling requests, a channel quality indicator (CQI), a precoding matrix indicator (PMI), a rank indicator (RI), and hybrid automatic repeat request (HARQ) acknowledgment (ACK) (HARQ-ACK) feedback (i.e., one or more HARQ ACK bits indicating one or more ACK and / or negative ACK (NACK)). The PUSCH carries data, and may additionally be used to carry a buffer status report (BSR), a power headroom report (PHR), and / or UCI.129025-2490W001

[0070] FIG. 3 is a block diagram of a base station 310 in communication with a UE 350 in an access network. In the DL, Internet protocol (IP) packets may be provided to a controller / processor 375. The controller / processor 375 implements layer 3 and layer 2 functionality. Layer 3 includes a radio resource control (RRC) layer, and layer 2 includes a service data adaptation protocol (SDAP) layer, a packet data convergence protocol (PDCP) layer, a radio link control (RLC) layer, and a medium access control (MAC) layer. The controller / processor 375 provides RRC layer functionality associated with broadcasting of system information (e.g., MIB, SIBs), RRC connection control (e.g., RRC connection paging, RRC connection establishment, RRC connection modification, and RRC connection release), inter radio access technology (RAT) mobility, and measurement configuration for UE measurement reporting; PDCP layer functionality associated with header compression / decompression, security (ciphering, deciphering, integrity protection, integrity verification), and handover support functions; RLC layer functionality associated with the transfer of upper layer packet data units (PDUs), error correction through ARQ, concatenation, segmentation, and reassembly of RLC service data units (SDUs), re-segmentation of RLC data PDUs, and reordering of RLC data PDUs; and MAC layer functionality associated with mapping between logical channels and transport channels, multiplexing of MAC SDUs onto transport blocks (TBs), demultiplexing of MAC SDUs from TBs, scheduling information reporting, error correction through HARQ, priority handling, and logical channel prioritization.

[0071] The transmit (TX) processor 316 and the receive (RX) processor 370 implement layer 1 functionality associated with various signal processing functions. Layer 1, which includes a physical (PHY) layer, may include error detection on the transport channels, forward error correction (FEC) coding / decoding of the transport channels, interleaving, rate matching, mapping onto physical channels, modulation / demodulation of physical channels, andMIMO antenna processing The TX processor 316 handles mapping to signal constellations based on various modulation schemes (e.g., binary phase-shift keying (BPSK), quadrature phase-shift keying (QPSK), M-phase-shift keying (M-PSK), M-quadrature amplitude modulation (M-QAM)). The coded and modulated symbols may then be split into parallel streams. Each stream may then be mapped to an OFDM subcarrier, multiplexed with a reference signal (e.g., pilot) in the time and / or frequency domain, and then combined129025-2490W001together using an Inverse Fast Fourier Transform (IFFT) to produce a physical channel carryingatime domain OFDMsymbol stream. The OFDM stream is spatially precoded to produce multiple spatial streams. Channel estimates from a channel estimator 374 may be used to determine the coding and modulation scheme, as well as for spatial processing. The channel estimate may be derived from a reference signal and / or channel condition feedback transmitted by the UE 350. Each spatial stream may then be provided to a different antenna 320 via a separate transmitter 318Tx. Each transmitter 318Tx may modulate a radio frequency (RF) carrier with a respective spatial stream for transmission.

[0072] At the UE 350, each receiver 354Rx receives a signal through its respective antenna 352. Each receiver 354Rx recovers information modulated onto an RF carrier and provides the information to the receive (RX) processor 356. The TX processor 368 and the RX processor 356 implement layer 1 functionality associated with various signal processing functions. TheRX processor 356 may perform spatial processing on the information to recover any spatial streams destined fortheUE350. If multiple spatial streams are destined for the UE 350, they may be combined by the RX processor 356 into a single OFDM symbol stream. The RX processor 356 then converts the OFDM symbol stream from the time-domain to the frequency domain using a Fast Fourier Transform (FFT). The frequency domain signal includes a separate OFDM symbol stream for each subcarrier of the OFDM signal. The symbols on each subcarrier, and the reference signal, are recovered and demodulated by determining the most likely signal constellation points transmitted by the base station 310. These soft decisions may b e based on channel estimates computed by the channel estimator 358. The soft decisions are then decoded and deinterleaved to recover the data and control signals that were originally transmitted by the base station 310 on the physical channel. The data and control signals are then provided to the controller / processor 359, which implements layer 3 and layer 2 functionality.

[0073] The controller / processor 359 can be associated with at least one memory 360 that stores program codes and data. The at least one memory 360 may be referred to as a computer-readable medium. In the UL, the controller / processor 359 provides demultiplexing between transport and logical channels, packet reassembly, deciphering, header decompression, and control signal processing to recover IP129025-2490W001packets. The controller / processor 359 is also responsible for error detection using an ACK and / or NACK protocol to support HARQ operations.

[0074] Similar to the functionality described in connection with the DL transmission by the base station 310, the controller / processor 359 provides RRC layer functionality associated with system information (e.g., MIB, SIBs) acquisition, RRC connections, and measurement reporting; PDCP layer functionality associated with header compression / decompression, and security (ciphering, deciphering, integrity protection, integrity verification); RLC layer functionality associated with the transfer of upper layer PDUs, error correction through ARQ, concatenation, segmentation, and reassembly of RLC SDUs, re-segmentation of RLC data PDUs, and reordering of RLC data PDUs; and MAC layer functionality associated with mapping between logical channels and transport channels, multiplexing of MAC SDUs onto TBs, demultiplexing of MAC SDUs from TBs, scheduling information reporting, error correction through HARQ, priority handling, and logical channel prioritization.

[0075] Channel estimates derived by a channel estimator 358 from a reference signal or feedback transmitted by the base station 310 may be used by the TX processor 368 to select the appropriate coding and modulation schemes, and to facilitate spatial processing. The spatial streams generated by the TX processor 368 may be provided to different antenna 352 via separate transmitters 354Tx. Each transmitter 354 Tx may modulate an RF carrier with a respective spatial stream for transmission.

[0076] The UL transmission is processed at the base station 310 in a manner similar to that described in connection with the receiver function atthe UE 350. Each receiver 318Rx receives a signal through its respective antenna 320. Each receiver 318Rx recovers information modulated onto an RF carrier and provides the information to a RX processor 370.

[0077] The controller / processor 375 can be associated with at least one memory 376 that stores program codes and data. The at least one memory 376 may be referred to as a computer-readable medium. In the UL, the controller / processor 375 provides demultiplexing between transport and logical channels, packet reassembly, deciphering, header decompression, control signal processing to recover IP packets. The controller / processor 375 is also responsible for error detection using an ACK and / or NACK protocol to support HARQ operations.129025-2490W001

[0078] At least one of the TX processor 368, the RX processor 356, and the controller / processor 359 may be configured to perform aspects in connection with the measurement scheme indication component 198 of FIG. 1.

[0079] At least one of the TX processor 316, the RX processor 370, and the controller / processor 375 may be configured to perform aspects in connection with the measurement scheme indication component 199 of FIG. 1.

[0080] FIG. 4 is a diagram 400 illustrating an example of a UE positioningbased on reference signal measurements (which may also be referred to as “network-based positioning”) in accordance with variousaspectsofthe present disclosure. The UE404 may transmit UL SRS 412 at time TSRS_TX and receive DL positioning reference signals (PRS) (DL PRS) 410 at time TPRS RX- The TRP 406 may receive the UL SRS 412 at time TSRS RX and transmit the DL PRS 410 at time TpRSTX- The UE 404 may receive the DL PRS 410 before transmitting the UL SRS 412, or may transmit the UL SRS 412 before receiving the DL PRS 410. In both cases, a positioning server(e.g., location servers) 168) or the UE 404 may determine the RTT 414 based on ||TSRS _RX - TPRSTX| - |TSRS TX - TPRS _RX||. Accordingly, multi-RTT positioning may make use of the UE Rx-Tx time difference measurements (i.e., |TSRS TX - TPRS _RX|) and DL PRS reference signal received power (RSRP) (DL PRS-RSRP) of downlink signals received from multiple TRPs 402, 406 and measured by the UE 404, and the measured TRP Rx-Tx time difference measurements (i.e., |TSRS_RX - TPRSTX|) and UL SRS-RSRP at multiple TRPs 402, 406 of uplink signals transmitted from UE 404. The UE 404 measures the UE Rx-Tx time difference measurements (and / or DL PRS-RSRP of the received signals) using assistance data received from the positioning server, and the TRPs 402, 406 measure the gNB Rx-Tx time difference measurements (and / or UL SRS-RSRP of the received signals) using assistance data received from the positioning server. The measurements may be used atthe positioning server or the UE 404 to determine the RTT, which is used to estimate the location of the UE 404. Other methods are possible for determining the RTT, such as for example using DL-TDOA and / or UL-TDOA measurements.

[0081] PRSs may be defined for network-based positioning (e.g., NR positioning) to enable UEs to detect and measure more neighbor transmission and reception points (TRPs), where multiple configurations are supported to enable a variety of deployments (e.g, indoor, outdoor, sub-6, mmW, etc.). To support PRS beam operation, beam sweeping129025-2490W001may also be configured for PRS. The UL positioning reference signal may be based on sounding reference signals (SRSs) with enhancements / adjustments for positioning purposes. In some examples, UL-PRS may be referred to as “SRS for positioning” and a new Information Element (IE) may be configured for SRS for positioning in RRC signaling.

[0082] DL PRS-RSRP may be defined as the linear average over the power contributions (in [W]) of the resource elements of the antenna port(s) that carry DL PRS reference signals configured for RSRP measurements within the considered measurement frequency bandwidth. In some examples, for FR1, the ref erencepointfortheDL PRS- RSRP may be the antenna connector of the UE. For FR2, DL PRS-RSRP may be measured based on the combined signal from antenna elements corresponding to a given receiver branch. ForFRl and FR2, if receiver diversity is in use by the UE, the reported DL PRS-RSRP value may not be lower than the corresponding DL PRS- RSRP of any of the individual receiver branches. Similarly, UL SRS-RSRP may be defined as linear average of the power contributions (in [W]) of the resource elements carrying sounding reference signals (SRS). UL SRS-RSRP may be measured over the configured resource elements within the considered measurement frequency bandwidth in the configured measurement time occasions. In some examples, for FR1 , the reference point for the UL SRS-RSRP may be the antenna connector of the base station (e.g., gNB). For FR2, UL SRS-RSRP may be measured based on the combined signal from antenna elements correspondingto a given receiver branch. For FR1 and FR2, if receiver diversity is in use by the base station, the reported UL SRS- RSRP value may not be lower than the corresponding UL SRS-RSRP of any of the individual receiver branches.

[0083] PRS-path RSRP (PRS-RSRPP) may be defined as the power of the linear average of the channel response at the i-th path delay of the resource elements that carry DL PRS signal configured for the measurement, where DL PRS-RSRPP for the 1 st path delay is the power contribution corresponding to the first detected path in time. In some examples, PRS path Phase measurement may refer to the phase associated with an i- th path of the channel derived using a PRS resource.

[0084] DL-AoD positioning may make use of the measured DL PRS-RSRP of downlink signals received from multiple TRPs 402, 406 at the UE 404. The UE 404 measures the DL PRS-RSRP of the received signals using assistance data received from the129025-2490W001positioning server, and the resulting measurements are used along with the azimuth angle of departure (A-AoD), the zenith angle of departure (Z-AoD), and other configuration information to locate the UE 404 in relation to the neighboring TRPs 402, 406.

[0085] DL-TDOA positioning may make use of the DL reference signal time difference (RSTD) (and / or DL PRS-RSRP) of downlink signals received from multiple TRPs 402, 406 at the UE 404. The UE 404 measures the DL RSTD (and / or DL PRS-RSRP) of the received signals using assistance data received from the positioning server, and the resulting measurements are used along with other configuration information to locate the UE 404 in relation to the neighboring TRPs 402, 406.

[0086] UL-TDOA positioning may make use of the UL relative time of arrival (RTOA)(and / or UL SRS-RSRP) at multiple TRPs 402, 406 of uplink signals transmitted from UE 404. The TRPs 402, 406 measure the UL-RTOA (and / or UL SRS-RSRP) of the received signals using assistance data received from the positioning server, and the resulting measurements are used along with other configuration information to estimate the location of the UE 404.

[0087] UL-AoApositioningmay make use of the measured azimuth angle of arrival (A-AoA) and zenith angle of arrival (Z-AoA) at multiple TRPs 402, 406 of uplink signals transmitted from the UE 404. The TRPs 402, 406 measure the A-AoA and the Z-AoA of the received signals using assistance data received from the positioning server, and the resulting measurements are used along with other configuration information to estimate the location of the UE 404. For purposes of the present disclosure, a positioning operation in which measurements are provided by a UE to a base station / positioningentity / serverto be used in the computation of theUE’s position may be described as “UE-assisted,” “UE-assisted positioning,” and / or “UE-assisted position calculation,” while a positioning operation in which a UE measures and computes its own position maybe described as“UE-based ,” “UE-based positioning,” and / or “UE-based position calculation.”

[0088] Additional positioning methods may be used for estimating the location of the UE 404, such as for example, UE-side UL-AoD and / or DL-AoA. Note that data / measurements from various technologies may be combined in various ways to increase accuracy, to determine and / or to enhance certainty, to129025-2490W001supplement / complement measurements, and / or to substitute / provide for missing information.

[0089] Note that the terms “positioning reference signal” and “PRS” generally refer to specific reference signals that are used for positioning in NR and LTE systems. However, as used herein, the terms “positioning reference signal” and “PRS” may also refer to any type of reference signal that can be used for positioning, such as but not limited to, PRS as defined in LTE and NR, TRS, PTRS, CRS, CSLRS, DMRS, PSS, SSS, SSB, SRS, UL-PRS, etc. In addition, the terms “positioning reference signal” and “PRS” may refer to downlink or uplink positioning reference signals, unless otherwise indicated by the context. To further distinguish the type of PRS, a downlink positioning reference signal may be referred to as a “DL PRS,” and an uplink positioning reference signal (e.g., an SRS-for-positioning, PTRS) may be referred to as an “UL-PRS.” In addition, for signals that may be transmitted in both the uplink and downlink (e.g., DMRS, PTRS), the signals may be prepended with “UL” or “DL” to distinguish the direction. For example, “UL-DMRS” may be differentiated from “DL-DMRS.” In addition, the term “location” and “position” may be used interchangeably throughout the specification, which may referto a particular geographical or a relative place.

[0090] For purposes of the present disclosure, “UE Rx - Tx time difference” may be defined as TUE-RX - TUE-TX, where: TUE.Rx is the UE received timing of downlink subframe #i from a Transmission Point (TP), defined by the first detected path in time. TUE-TX is the UE transmit timing of uplink subframe #j that is closest in time to the subframe #i received from the TP. Multiple DL PRS or CSLRS for tracking resources, as instructed by higher layers, can be used to determine the start of one subframe of the first arrival path of the TP. For frequency range 1, the reference point for TUE-RX measurement may be the Rx antenna connector of the UE and the reference point for TUE-TX measurement may be the Tx antenna connector of the UE. For frequency range 2, the reference point for TUE-RX measurement may be the Rx antenna of the UE and the reference point for TUE-TX measurement may be the Tx antenna of the UE.

[0091] “DL reference signal time difference (DLRSTD)” is the DL relative timing difference between the Transmission Point (TP) j and the reference TP z, defined as TsubframeRxj - TsubframeRxi, where: TsubframeRxj is the time when the UE receives the start of one subframe from TP j. TSubframeRxi is the time when the UE receives the corresponding129025-2490W001start of one subframe from TP z that is closest in time to the subframe received from TP j. Multiple DL PRS resources can be used to determine the start of one subframe from a TP. For frequency range 1 , the reference point for the DL RSTD may be the antenna connector of the UE. For frequency range 2, the reference point for the DL RSTD may be the antenna of the UE.

[0092] “DL PRS reference signal received power (DL PRS-RSRP),” is defined as the linear average over the power contributions (in [W]) of the resource elements that carry DL PRS reference signals configured for RSRP measurements within the considered measurement frequency bandwidth. For frequency range 1 , the reference point for the DL PRS-RSRP may be the antenna connector of the UE. For frequency range 2, DL PRS-RSRP may be measured based on the combined signal from antenna elements corresponding to a given receiver branch. For frequency range 1 and 2, if receiver diversity is in use by the UE, the reported DL PRS-RSRP value may notbe lower than the corresponding DL PRS-RSRP of any of the individual receiver branches.

[0093] “DL PRS reference signal received path power (DL PRS-RSRPP),” is defined as the power of the linear average of the channel response at the i-th path delay of the resource elements that carry DL PRS signal configured for the measurement, where DL PRS-RSRPP for the 1 st path delay is the power contribution corresponding to the first detected path in time. For frequency range 1 , the reference point for the DL PRS- RSRPP may be the antenna connector of the UE. For frequency range 2, DL PRS- RSRPP may be measured based on the combined signal from antenna elements corresponding to a given receiver branch. For frequency range 1 and 2, if receiver diversity is in use by the UE for DL PRS-RSRPP measurements, the reported DL PRS-RSRPP value included in the higher layer parameter NR-DL-AoD-MeasElement for the first and additional measurements may be provided for the same receiver branch(es) as applied for DL PRS-RSRP measurements

[0094] DL reference signal carrier phase (RSCP)” is defined as the phase of the channel response at the 1stpath delay derived from the resource elements carrying DL PRS configured for the measurement. DL RSCP is associated with the center frequency of the DL positioning frequency layer (PFL) configured for the measurement for RRC connected, RRC inactive, and RRC idle modes. For frequency range 1, the reference point for the DL RSCP may be the antenna connector of the UE. For frequency range 2, the reference point for the DL RSCP may be the antenna of the UE.129025-2490W001

[0095] “DL reference signal carrier phase difference (RSCPD)” is defined as the difference of DL RSCPs measured from DL PRS transmitted in a DL PFL from the transmission point(TP) j and the reference TPz. If UE reports RSCPD measurements together with RSTD measurements in a measurement report element, the reference TP for RSCPD is the same as the reference TP reported for RSTD. For frequency range 1, the reference point for the DL RSCPD may be the antenna connector of the UE. For frequency range 2, the reference point for the DL RSCPD may be the antenna of the UE.

[0096] FIG. 5 is a diagram 500 illustrating an example radio access technology (RAT)- dependent positioning in accordance with various aspects of the present disclosure. For existing (e.g., classical) RAT-dependent positioning as discussed in connection with FIG. 4, as shown at 502, a positioning device / entity may be configured to input reference signal measurement(s), such as channel frequency response (CFR), channel impulse response (CIR), power delay profile (PDP), delay profile (DP) of PRS / SRS, etc., to a path finding algorithm to obtain a set of intermediate positioning measurements (e.g., RSTD, RTOA, LOS indicator, UE / gNB Rx-Tx time difference, etc.). Then, as shown at 504, the set of intermediate positioning measurements may be provided to a positioning engine (PE) to derive the location of a target, such as the coordinates of the target (which may be the positioning device itself). However, the existing RAT-dependent positioning may not be able to provide accurate positioning when the target is under non-line-of-sight(NLOS) conditions, such as when the target is in an urban dense area surrounded by tall buildings.

[0097] In some implementations, at least one artificial intelligence (Al) / machine learning (ML) (AI / ML) model may be configured / implemented at an entity / node (e.g., a UE, a network entity / node such as a base station, a location server, a location management function (LMF), etc.) for assisting the entity / node with the positioning of a UE (e.g., a target). For example, an AI / ML model may be trained to determine the position of a UE based on DL-AoA, DL-TDOA, CIR, radio frequency (RF) fingerprinting, etc. In most scenarios, using an AI / ML model may significantly improve UE positioning latency, accuracy / reliability, and / or efficiency. For example, AI / ML may enhance positioning accuracy in NLOS conditions because the AI / ML may have the capability to learns channel multipath profile and its mapping to location information.129025-2490W001

[0098] For purposes of the present disclosure, an AI / ML model that is implemented at a UE side may be referred to as a “UE-side model” and / or “UE-side AI / ML model.” On the other hand, an AI / ML model that is implemented at a network side may be referred to as a “network-side model,” “network-side AI / ML model,” and / or (network name} side AI / ML model (e.g., base station-side AI / ML model, LMF-side AI / ML model, etc.). In addition, positioning that is associated with a UE or a network entity / node using an AI / ML model to determine the position of the UE may be referred to as “direct AI / ML positioning,” whereas positioning that is associated with a UE or a network entity / node performing positioning related measurements using an AI / ML model (and transmitting the positioning related measurements to another entity) to determine the position of the UE may be referred to as “AI / ML assisted positioning” and / or “assisted AI / ML positioning.” Also, UE-based positioning (e.g., UE determines its own position) using at least one UE-side AI / ML model may be referred to as “direct UE AI / ML positioning” and / or “UE direct AI / ML positioning,” whereas UE-assisted positioning (e.g., a UE provides positioningmeasurements and a network entity, such as an LMF, determines the position for the UE based on the positioning measurements provided by the UE) using at least one UE-side AI / ML model may be referred to as “UE AI / ML assisted positioning,” “UE assisted AI / ML positioning” “AI / ML assisted UE positioning,” and / or “AI / ML UE assisted positioning,” etc. Similarly, network -based positioning (e.g., a network entity, such as an LMF, determines the position for the UE) using at least one network / LMF-side AI / ML model may be referred to as “direct network / LMF AI / ML positioning” and / or “network / LMF direct AI / ML positioning.”

[0099] For purposes of the present disclosure, at a high-level, an “AI / ML model” may refer to a program / algorithm that is capable of being trained on a set of data (which may be referred to as “training data”) to make certain decisions (without further human intervention), to recognize certain patterns, and / or predict certain outcomes, etc. In some examples and depending on the context, an “AI / ML model” may also refer to an actual physical model with given parameters and weights, and / or may refer to a logical model for which one or more models can be considered but all seen as one logical model from identification stand point. Similarly, depending on the context, an “AI / ML functionality” may refer to employing AI / ML to positioning without referringto an underlying model (physical and / or logical). The AI / ML functionality129025-2490W001may still be defined / identified based on measurements of information considered for its inputs and / or outputs. In some examples, the AI / ML functionality may refer to one or more AI / ML model for which model input may refer to a specific measurement type / or and quantities. The one or more model(s) may be logical or physical. The AI / ML functionality may also refer to one or more AI / ML model for which model outputmay referto a specific measurementtype / location information and / or quantity. The one or more model(s) can be logical or physical. Depending on the context, sometimes the term “AI / ML model” may be used interchangeably with the term “AI / ML functionality,” and AI / ML model and AI / ML functionality may collectively be referred to as “AI / ML.”

[0100] FIG. 6A is a diagram 600A illustrating an example of direct AI / ML positioning in accordance with various aspects of the present disclosure. For direct AI / ML positioning, an entity / node (e.g., a UE, a network entity / node such as a base station, a location server, etc.) may use at least one AI / ML model to determine the position of a UE or a target. For example, as shown at 602, the entity / node may input a set of PRS / SRS measurements (e g., CFR, CIR, PDP, DP, RSTD / difference-RSTD, RTOA / difference-RTOA,RSRP / RSRPP, etc.) to a direct AI / ML positioning model, and the direct AI / ML positioning model may output the location of the UE / target, such as the coordinates of the UE / target.

[0101] FIG. 6B is a diagram 600B illustrating an example of AI / ML assisted positioning in accordance with various aspects of the present disclosure. For AI / ML assisted positioning, an entity / node (e.g., a UE, a network entity / node such as a base station, etc.) may use at least one AI / ML model to assistthe measurement of reference signals (e.g., positioningreference signals such as PRS, SRS, etc.). Then, the entity / node may transmit the reference signal measurements to a location server, such as an LMF. In response, the location server may determine the position of a UE / target based on a non-AI / ML mechanism / algorithm, or based on using another AI / ML model to determine the position of the UE / target. For example, as shown at 604, the entity / node may input a set of PRS / SRS measurements (e.g., CFR, CIR, PDP, DP, RSTD / difference-RSTD, RTOA / difference-RTOA, RSRP / RSRPP, etc.) related to a UE / target to an AI / ML assisted positioning model, and the AI / ML assisted positioning model may output a set of intermediate positioning measurements (e.g, RSTD, RTOA, LOS indicator, UE / gNB Rx-Tx time difference, etc.). Then, as shown129025-2490W001at 606, the set of intermediate positioning measurements may be provided to a positioning engine (PE) (or another AI / ML model) to derive the location of the UE / target, such as the coordinates of the UE / target (which may be the entity / node itself).

[0102] FIG. 7 is a diagram 700 illustrating an example of UE-based positioning with aUE- side AI / ML model, direct AI / ML or AI / ML assisted positioning in accordance with various aspects of the present disclosure. In one implementation, a UE 702 may be associated with at least one AI / ML model 708, and the UE 702 may use the at least one AI / ML model 708 to perform the direct AI / ML positioning and / or the assisted AI / ML positioning based on downlink (DL) reference signals, such as positioning reference signals (PRSs). For example, the UE 702 may receive and measure a set of PRSs transmitted from a base station 706 (this may also be one or more base stations and / or one or more TRPs), such as measuring the reference signal received power (RSRP), channel impulse response (CIR), DL-AoD, reference signal time difference (RSTD), time of arrival (To A), and / or time of flight (ToF) of the set of PRSs, etc., which may be collectively be referred to as “PRS measurement(s)” and / or “PRS- based measurement(s).” In some examples, the UE 702 may use the at least one AI / ML model 708 for measuring the set of PRSs (e.g., for assisted AI / ML positioning). In some examples, based on the PRS measurement(s), the UE 702 may use the at least one AI / ML model 708 for determining its position (e.g., for direct AI / ML positioning). Note in this assisted AI / ML positioning example, the UE 702 may use the at least one AI / ML model 708 for performing PRS measurements, and the UE 702 may determine its position based on the PRS measurements without the assistance of an AI / ML model.

[0103] FIG. 8A is a diagram 800A illustrating an example of UE-assisted / LMF-based positioning with a UE-side AI / ML model, AI / ML assisted positioning in accordance with various aspects of the present disclosure. In another implementation, a UE 702 may be associated with at least one AI / ML model 708, and the UE 702 may use the at least one AI / ML model 708 to perform or assist measurement(s) of DL reference signals. For example, the UE 702 may receive and measure a set of PRSs transmitted from abase station 706 (this may also be one or more base stations and / or one or more TRPs) with the assistance of the at least one AI / ML model 708, which may be referred to as “PRS-based measurement(s).” Then, the UE 702 may transmit the PRS-based129025-2490W001measurement(s) (e.g., the output of the at least one AI / ML model 708 such as the RSTD, the LOS indicator, the UE Rx-Tx time difference, etc.) to a location server 704, such as an LMF. In response, the location server 704 may determine the position of the UE 702 based on the PRS-based measurement(s) (with or without suing an AI / ML model).

[0104] FIG. 8B is a diagram 800B illustrating an example of UE-assisted / LMF-based positioning with an LMF-side AI / ML model, direct AI / ML positioning in accordance with various aspects of the present disclosure. In another implementation, a UE 702 may not include a UE-side AI / ML model, and a location server 704 may use at least one AI / ML model 708 to determine the position of the UE 702. For example, the UE 702 may receive and measure a set of PRSs transmitted from a base station 706, and the UE 702 may transmit the PRS-based measurement(s) (e.g., CIR / PDP / DP, RSTD / difference-RSTD, RSRP / RSRPP, etc.) to the location server 704, such as an LMF. Based on the PRS-based measurement(s) from the UE 702, the location server 704 may use the PRS-based measurement(s) as an input to at least one AI / ML model 708, and receive the position oftheUE702 as an output from the at least one AI / ML model 708.

[0105] FIG. 9A is a diagram 900A illustrating an example of network (e.g., NG-RAN) node assisted positioning with a base station (gNB)-side AI / ML model, AI / ML assisted positioning in accordance with various aspects of the present disclosure. In another implementation, a network node, such as a base station 706, may be associated with at least one AI / ML model 708, and the base station 706 may use the at least one AI / ML model 708 to assist measurement(s) of uplink (UL) reference signals, such as sounding reference signals (SRSs). For example, the UE 702 may transmit a set of SRSs to the base station 706 (this may also be one or more base stations and / or one or more TRPs), and the base station 706 may receive and measure the set of SRSs (which may be referred to as “SRS-based measurement(s)”) with the assistance of the at least one AI / ML model 708. Then, the base station 706 may transmitthe SRS-based measurement(s) (e.g., the output of the at least one AI / ML model 708 such as the RTOA, LOS indicator, gNB Rx-Tx time difference, etc.) to a location server 704, such as an LMF. In response, the location server 704 may determine the position of the UE 702 based on the SRS-based measurement(s) (with or without suing an AI / ML model).129025-2490W001

[0106] FIG. 9B is a diagram 900B illustrating an example of network (e.g., NG-RAN) node assisted positioning with LMF-side AI / ML model, direct AI / ML positioning in accordance with various aspects of the present disclosure. In another implementation, a network node, such as a base station 706 (this may also be one or morebase stations and / or one or more TRPs), may not include an AI / ML model, and a location server 704 may use at least one AI / ML model 708 to determine the position of a UE 702. For example, the UE 702 may transmit a set of SRSs to the base station 706, and the base station 706 may receive and measure the set of SRSs. Then, the base station 706 may transmit the SRS-based measurement(s) to the location server 704, such as an LMF. Based on the SRS-based measurement(s) fromthe base station 706, the location server 704 may use the SRS-based measurement(s) as an input to at least one AI / ML model 708, and receive the position of the UE 702 as an output from the at least one AI / ML model 708. For purposes of the present disclosure, positioning described in connection with FIGs. 7, 8 A, and 8B may be referred to as AI / ML positioning based on DL reference signals, and positioning describedin connection with FIGs. 9 A and 9B may be referred to as AI / ML positioning based on UL reference signals.

[0107] In some implementations, for direct AI / ML positioningas described in connection with FIGs. 8B and 9B, type(s) of measurement(s) that may be used as (suitable / potential) inputfor AI / ML model inferenceconsideringperformance impact and associated signaling overhead may include channel impulse response (CIR), power delay profile (PDP), reference signal receive power (RSRP), reference signal received path power (RSRPP), and / or reference signal time difference (RSTD), etc. For AI / ML assisted positioning with UE-assisted and network node-assisted positioning described in connection with FIGs. 8 A and 9 A, respectively, measurement report to carry AI / ML model (suitable / potential) output to a location server such as an LMF may include ToA, path phase, RSTD, line-of-sight(LOS) / non-line-of-sight (NLOS) indicator, RSRPP, and / or soft inf ormation / high resolution of RSTD, etc. In some examples, AI / ML model inference output that may provide performance benefits may include timing estimation (note the report to LMF may be derived based on and maybe different from the model inference output) and / or LOS / NLOS indicator.

[0108] For network node assisted positioning such as described in connection with FIG. 9 A, at least LOS / NLOS indicator and / or timing information may be supported by a base129025-2490W001station (e.g., the base station 706) for reporting (e.g., to a location server such as the location server 704). If LOS / NLOS indicator is reported by the base station, the indicator may be reported as a soft indicator or a hard indicator depending on implementations. If timing information is reported, the base station maybe configured to report the timing information via UL RTOA or gNB Rx-Tx time difference. Similarly, forUE-assisted positioning such as describedin connection with FIG. 8A, at least LOS / NLOS indicator and / or timing information may be supported by a UE (e.g., the UE 702) for reporting (e.g., to a location server such as the location server 704). If LOS / NLOS indicator is reported by the UE, the indicator may be reported as a soft indicator or a hard indicator depending on implementations. If timing information is reported, the base station may be configured to report the timing information via DL RSTD or UE Rx-Tx time difference.

[0109] For AI / ML based positioning such as described in connection with FIG. 9B, at least (1) timing information, and / or (2) paired timing information and power information may be supported by a base station (e.g., the base station 706) for reporting time domain channel measurements. Similarly, for AI / ML based positioning such as described in connection with FIG. 8 A, at least (1) timing information, and / or (2) paired timing information and power information may be supported by a UE (e.g., the UE 702) for reporting time domain channel measurements (e.g., to a location server such as the location server 704 or an LMF).

[0110] Depending on implementations, for AI / ML based positioning, the time domain channel measurements may be: (a) sample-based measurements, where the timing information is an integer multiple of sampling periods, and / or (b) path-based measurements, where the timing information is according to the detected path timing and may not be an integer multiple of sampling periods.

[0111] For purposes of the present disclosure, a “path-based measurement” may refer to the measurement that evaluates the characteristics of the radio propagation path between a transmitter and a receiver. For example, a path-based measurement may include measuring a first path, which may generally refer to the first signal arrival that a receiver detects, which may be the direct path or the initial path of a multipath component. In some scenarios, the firstpath may correspondto the direct line-of-sight (LOS) path between the transmitter and the receiver, or the strongest signal path in the environment. It is often the primary and most direct signal transmission route in129025-2490W001the absence of obstacles or interference. A “first path finding method / algorithm” may refer to a method / algorithm that is capable of finding / identifying the first path, which may also be referred to as a “path processing operation” depending on the context.

[0112] A “sample-based measurement” may refer to the measurement that is composed of Nt' samples of the estimated channel responsein time domain. The timing information for the Nt' samples may be reported with a timing granularity T, where T = 2kxTc, k represents the timing reporting granularity factor, and Tc is the basic time unit (e.g., for NR). The corresponding measurement (e.g., power if reported) may correspond to the measurement for the reported Nt' samples (note the value of Nt' and k may be signaled). The timing information may be defined relative to a reference time. Also, there may be a window of Nt samples from which the Nt’ samples are to be selected (e.g., a number of strongest samples are selected). Depending on the context, in some examples, the “sample” may also be referred to as a measurement, an additional measurement, or an enhanced measurement.

[0113] FIG. 10 is a diagram 1000 illustrating an example sample-based measurement in accordance with various aspects of the present disclosure. As shown at 1002, a sample-based measurement may be based on a configuring a wireless device to measure and select ten (10) strongest samples (e.g., Nt’ = 10) from a window of Nt samples (e.g., Nt = 20, 30, or 50, etc.)

[0114] Table 2 below provides an example list of positioning methodsthat may be supported by a UE and / or a network entity.129025-2490W001Table 2: Example of supported UE positioning methods

[0115] Table 3 below provides an example list of measurement results associated with DL- TDOA that may be transferred / transmitted from a UE to an LMF.129025-2490W001Table 3: Example list of measurement results associated with DL-TDOA

[0116] Table 4 below provides an example list of measurement results associated with DL- AoD that may be transferred / transmitted from a UE to an LMF.129025-2490W001Table 4: Example list of measurement results associated with AoD

[0117] Table 5 below provides an example list of measurement results associated with multi- RTT (mRTT) that may be transferred / transmitted from a UE to an LMF.129025-2490W001Table 5: Example list of measurement results associated with multi-RTT

[0118] FIG. 11 is a diagram 1100 illustrating an example structure of a path and additional path measurement report in accordance with various aspects of the present disclosure. In one example, as shown at 1102, aUE may report measurements (e.g., timing and power) of a first path and additional paths associated with DL-TDOA in an information element (IE) L-TDOA-MeasElement.129025-2490W001

[0119] As discussed above, AI / ML positioning may be able to provide high positioning accuracy in stringent NLOS conditions. In existing positioning methods such as described in connection with FIG. 4, a UE, a base station (gNB), and / or a TRP (collectively as a “wireless device” or simply as a “device” hereafter) may be configured to report the first path and optionally additional path measurements (e.g, for path-based measurements).

[0120] Aspects presented herein may improve the overall performance of AI / ML positioning by enabling a wireless device (e.g., a UE, a base station, or a TRP, etc.) to consider and report measurements observed from the time-domain channel response (e.g., the sample-based measurements). For example, a wireless device may be configured to support the path-based measurement scheme and / or the sample-based measurement scheme for AI / ML input running at a location server side (e.g., running at an LMF such as described in connection with FIGs. 8B and 9B). The wireless device and the location server may be configured to exchange signaling on whether the wireless device is able to support “path-only” (e.g., just capable of performingthe path-based measurement), sample-only (e.g., just capable of performing the sample-based measurement), or joint path and sample measurement reporting (e.g., capable of performing both the sample-based measurement and the path-based measurement). For example, depending on implementations, a wireless device may be configured to indicate its capabilities on supported measurement schemes (including support for theirjoint operation) to a location server. The wireless devicemay alsobe configured to indicate the applicable measurement schemes. The location server may signal, to the wireless device, a set of specified / desired measurement schemes, and / or prioritization / conditioningfor a set of measurement schemes. In addition, the wireless device may report measurements with additional indicator on selected measurement scheme and parameters (orpriority / conditionfound for the schemethe wireless device selects).

[0121] FIG. 12 is a communication flow 1200 illustrating an example signaling for joint pathbased measurement and sample-based measurement reporting for AI / ML positioning in accordance with various aspects of the present disclosure. The numbering; associated with the communication flow 1200 do not specify a particular temporal order and are merely used as references for the communication flow 1200.129025-2490W001

[0122] At 1210, a wireless device 1202 (e.g., a UE, a positioning reference unit (PRU), a base station, a TRP, etc.) may transmit, to a network entity 1204 (e.g., a location server, an LMF, an AI / ML server, a sensing management function, an AI / ML management function, a crowd-sourcing entity, a network data analytics function (NWDAF), etc.), an indication of its capability for measurement scheme(s) (and also type(s)) corresponding to input for AI / ML (e.g., for an AI / ML model / functionality at the network entity 1204, such as described in connection with FIGs. 8B and 9B).

[0123] For example, a dedicated LTE Positioning Protocol (LPP) and / or NR Positioning Protocol A (NRPPa) (collectively as” LPP / NRPPa” hereafter) signaling / messaging may be configured for the wireless device 1202 for enabling the wireless device 1202 to indicate its supported capability of measurement scheme(s) and type(s) that may be considered for the input of the AI / ML at the network entity 1204 (e.g., for input at the LMF side AI / ML positioning model / functionality).

[0124] Depending on implementations, the wireless device 1202 may be configured to provide the supported capability of measurement scheme(s) andtype(s) to the network entity 1204 on its own initiative, or based on a request from the network entity 1204 (which may be referred to as “on-demand”). For example, at 1212, the network entity 1204 may transmit, to the wireless device 1202, a request to provide the capability for measurement schemes and types correspondingtoinputfor AI / ML. In response to the request, at 1210, the wireless device 1202 may provide its capability for measurement scheme(s) and type(s) corresponding to input for AI / ML to the network entity 1204.

[0125] In some examples, the wireless device 1202 may be configured to provide the supported capability of measurement scheme(s) and type(s) per band. In other words, the supported capability of measurement scheme(s) and type(s) may be indicated by the wireless device 1202 per band, where each band may have specific capabilities. For example, the wireless device 1202 may support a first measurement scheme and / or type for a first band, and a second measurement scheme and / or type for a second band, etc.

[0126] The indication / provision of the supported capability of measurement scheme(s) may include: (1) the wireless device 1202 is able to support just the path-based measurement scheme, (2) the wireless device 1202 is able to support just the samplebased measurement scheme, (3) the wireless device 1202 is able to support the pathbased measurement scheme or the sample-based measurement scheme ata time, or129025-2490W001(4) the wireless device 1202 is able to support both the path-based measurement scheme and the sample-based measurement scheme at a time (e.g., simultaneously).

[0127] In some implementations, the wireless device 1202 may further provide / indicate information or limitation(s) associated with each measurement scheme. For example, if the wireless device 1202provides / indicatesthatitis capable of supporting the pathbased measurement scheme, the wireless device 1202 may further provide / indicate: (1) the measurement type(s) supported for the path-based measurement scheme (e.g, timing, power, phase, paired timing and power, paired timing and phase, paired timing, power, and phase, etc.), (2) the maximum number of supported TRPs, reference signal (RS) resource sets, and / or RS resources for the path-based measurement scheme, (3) the maximum supported timing granularity factor k for the path -based measurement scheme, and / or (4) the maximum number of additional paths L that may be considered for the path-based measurement scheme, etc.

[0128] In another example, if the wireless device 1202 provides / indicates that it is capable of supporting the sample-based measurement scheme, the wireless device 1202 may further provide / indicate: (1) the measurement type(s) supported for the sample-based measurement scheme (e.g., timing, power, phase, paired timing and power, paired timing and phase, paired timing, power, and phase, etc.), (2) the maximum number of supported TRPs, RS resource sets, and / or RS resources for the sample-based measurement scheme, (3) the maximum supported timing granularity factor k for the sample-based measurement scheme, (4) the maximum number of samples Nt’ supported for the sample-based measurement scheme, (5) the maximum truncation window size Nt (from which the Nt’ samples may be selected) supported for the sample-based measurement scheme, and / or (6) a list of supported Nt / Nt’ selection rules / criteria (e.g., strongest power samples, local peaks observed in time domain channel response, samples above a configured threshold (e.g., threshold defined with respect to the strongest sample), and / or consecutive samples in time domain, etc.).

[0129] If the measurement type(s) supported by the wireless device 1202 for the path-based measurement scheme and / or the sample-based measurement scheme include the timing, the formatforthe timing (which may be referred to as the “timing format’ hereafter) may be based on: (1) Type 1 - codeword (e.g., multiples / integer of Tc ora fraction of Tc timing), which may be configured to utilize an existingreportingtiming format for path-based measurement reporting, (2) Type 2 - bitmap showing sample129025-2490W001timing location, (3) Type 3 - differential codeword (e.g., similar to Type 1 but each additional timing information may be indicated as a codeword indicating a difference with the timing of the previous sample), and / or (4) a maximum bitmap length.

[0130] If the measurement type(s) supported by the wireless device 1202 for the path-based measurement scheme and / or the sample-based measurement scheme include the power, the format for the power (which may be referred to as the “power format’ hereafter) may be based on: (1) Type 1 - codeword (e.g., multiples / integer of dBm or a fractional dBm value), which may be configured to utilize an existing reporting RSRP format for path-based measurement reporting, (2) Type 2 - bitmap showing sample power on a raster, (3) Type 3 - differential codeword (e.g., similar to Type 1 but each additional power information is indicated as a codeword indicating a difference with the power of the previous sample), and / or (4) a maximum bitmap length.

[0131] If the measurement type(s) supported by the wireless device 1202 for the path-based measurement scheme and / or the sample-based measurement scheme include the phase, the format for the phase (which may be referred to as the “phase format’ hereafter) may be based on: (1) Type 1 - codeword (e.g., multiples / integer of radiant or a fractional radiant value), which may be configured to utilize an existing reporting phase format for path-based measurement reporting, (2) Type 2 - bitmap showing sample phase on a raster, (3) Type 3 - differential codeword (e.g., similar to Type 1 but each additional phase information is indicated as a codeword indicating a difference with the phase of the previous sample), and / or (4) a maximum bitmap length.

[0132] In some examples, the wireless device 1202 may also support timing, power, and / or phase referencing (e.g., for the Type 1, Type 2, and / or Type 3 mentioned above), where measurements for a measurement scheme may be based on a common reference. For example, the common reference may be a (1) reference TRP, (2) an uplink (UL) or downlink (DL) (collectively as “UL / DL”) subframe boundary of a reference TRP, (3) an UL / DL subframe boundary of an observed TRP, (4) time of arrival (ToA) or reception (Rx) timing of an earlier UL signal, (5) ToA / Rx timing of an earlier DL signal, (6) transmission (Tx) timing of an earlier UL signal, and / or (7) Tx timing of an earlier DL signal, etc.129025-2490W001

[0133] In another example, if the wireless device 1202 provides / indicates that it is capable of supporting both the path-based measurement scheme and the sample-based measurement scheme (collectively as “joint measurement” or “joint measurement scheme” hereafter) (e.g., the wireless device 1202 is capable of running both measurement schemes together or at the same time), the wireless device 1202 may further provide / indicate: (1) the measurement type(s) supported for the joint measurement scheme (e.g., timing, power, phase, paired timing and power, paired timing and phase, paired timing, power, and phase, etc.), (2) the maximum number of supported TRPs, RS resource sets, and / or RS resources for the joint measurement scheme, (3) the maximum supported or the limitation for the timing granularity factor k for the joint measurement scheme, (4) the maximum number of measurements M = Nt’ + L supported for the joint measurement scheme, (5) the maximum number of additional paths L that may be considered for the joint measurement scheme, (6) the maximum number of samples Nt’ supported for the joint measurement scheme, (7) the maximum truncation window size Nt (from which the Nt’ samples may be selected) supported for the joint measurement scheme, (8) a list of supported Nt / Nt’ selection rules / criteria (e.g., strongest power samples, local peaks observed in time domain channel response, samples above a configured threshold (e.g., threshold defined with respect to the strongest sample), and / or consecutive samples in time domain, etc.), and / or (9) supported anchoring of Nt or Nt’ samples with respect to first or strongest path for the joint measurement scheme (e.g., Nt’ / Nt samples starting from an offset defined with respect to the first (or strongest) detected path, Nt’ / Nt samples around the first (or strongest) detected path, supported offset values for Nt’ / Nt measurement anchoring etc.)

[0134] Similarly, if the measurement type(s) supportedby the wireless device 1202 forthe joint measurement scheme include the timing, the timing format may be based on: (1) Type 1 - codeword, (2) Type 2 - bitmap showing sample timing location, (3) Type 3 - differential codeword, and / or (4) a maximum bitmap length. If the measurement type(s) supported by the wireless device 1202 for the joint measurement scheme include the power, the power format may be based on: (1) Type 1 - codeword, (2) Type2 -bitmap showing sample power on a raster, (3)Type3 - differential codeword, and / or (4) a maximum bitmap length. If the measurement type(s) supported by the wireless device 1202 forthe joint sample-based measurement scheme include the129025-2490W001phase, the phaseformatmay be based on: (l)Type 1 - codeword, (2) Type 2 - bitmap showing sample phase on a raster, (3) Type 3 - differential codeword, and / or (4) a maximum bitmap length. In addition, the wireless device 1202 may also support timing, power, and / or phase referencing (e.g., for the Type 1, Type 2, and / or Type 3 mentioned above), where measurements for the joint measurement scheme may be based on a common reference. For example, the common reference may be a (1) reference TRP, (2) an UL / DL subframe boundary of a reference TRP, (3) an UL / DL subframe boundary of an observed TRP, (4) ToA / Rx timing of an earlier UL signal, (5) ToA / Rx timing of an earlier DL signal, (6) Tx timing of an earlier UL signal, and / or (7) Tx timing of an earlier DL signal, etc.

[0135] In another example, if the wireless device 1202 provides / indicates that it is capable of supporting both the path-based measurement scheme and the sample-based measurement scheme (either supporting one measurement scheme at a time or supporting both measurement schemes at the same time), the wireless device 1202 may further provide / indicate that: (1) the path-based measurement scheme is the default setting and more / additional sample-based measurements are possible, (2) the sample-based measurement scheme is the default setting and more / additional pathbased measurements are possible, (3) the path-based measurement scheme demands / specifies more processing compared to the sample-based measurement scheme, (4) the path-based measurement scheme demands / specifies less processing compared to the sample-based measurement scheme, and / or (5) the joint processing capabilities for both the path-based measurement scheme and the sample-based measurement scheme (e.g., tuple of maximum limits on measurements and reporting when both measurement schemes are enabled / performed).

[0136] Referring back to FIG. 12, in some implementations, at 1214, the wireless device 1202 may also provide an indication of applicable measurement scheme(s) corresponding to AI / ML input (e.g., after providing the indication of the supported measurement scheme(s) at 1210). For example, a dedicated LPP / NRPPa signaling / messaging may be configured for the wireless device 1202 for enablingthe wireless device 1202 to indicate its applicable capabilities of measurement scheme(s) and type(s) that may be considered for the input of the AI / ML at the network entity 1204 (e.g., for input at the LMF side AI / ML positioning model / functionality). The applicable capabilities may be a shortened version of the capabilities supported by the wireless device 1202129025-2490W001discussed above. For purposes of the present disclosure, measurement scheme(s) “supported” by the wireless device 1202 may refer to the measurement scheme(s) that are capable of supported by the wireless device 1202. On the other hand, measurement scheme(s) “applicable” by the wireless device 1202 may refer to the measurement scheme(s) that may (currently) be applied or can be applied by the wireless device 1202 (e.g., the wireless device 1202 has enough processing power and / or memory to apply). For example, the wireless device 1202 may “support” performing either the path-based measurement scheme or the sample-based measurement scheme at a time, or performing both the path-based measurement scheme and the sample-based measurement scheme simultaneously when the wireless device 1202 is above certain processing and / or memory capacity. However, the wireless device 1202 may currently just be able to perform either the path-based measurement scheme or the sample-based measurement scheme (e.g., due to processing / memory availability at the wireless device 1202). In other words, the measurement scheme(s) applicable by the wireless device 1202 may be a subset of the measurement scheme(s) supported by the wireless device 1202.

[0137] At 1216, based on the indication of measurement scheme(s) supported and / or applicable by the wireless device 1202 (e.g., received at 1210 and / or 1214), the network entity 1204 may transmit, to the wireless device 1202, a request for a set of measurements that is to be used as an input for the AI / ML at the network entity 1204, where the request may indicate or configure at least one measurement scheme to be used for the set of measurements (e.g., selected from the ones supported / applicable by the wireless device 1202). In addition, the request may also provide the measurement type(s) (e.g., timing, power, and / or phase) specified by the network entity 1204 and / or the condition(s) / format(s) for reporting the set of measurements, etc.

[0138] For example, a dedicated LPP / NRPPa signaling / messaging may be configured for the network entity 1204 for enabling the network entity 1204 to configure / request the wireless device 1202 with measurement scheme(s) and type(s) to be reported for the input of the AI / ML at the network entity 1204 (e.g., for input at the LMF side AI / ML positioning model / functionality). In addition, the request may also be configured to be specific to a band, a positioning frequency layer (PFL), a TRP, an RS resource set, or an RS resource (e.g., each band, PFL, TRP, RS resource set, or RS may have a129025-2490W001specific request). The request may also indicate the desired measurement scheme(s) to be applied by the wireless device 1202, such as to apply just the sample-based measurement scheme, just the path-based measurement scheme, to apply either the path-based measurement scheme or the sample-based measurement scheme, or to apply both the path-based measurement scheme and the sample-based measurement scheme (e.g., apply the joint measurement scheme), etc.

[0139] In some implementations, the request for the set of measurements (e.g., at 1216) may also indicate the desired / configured measurement scheme details / information (e.g, a set of parameters to be applied to a measurement scheme), such as (1) a configured / desired timing granularity factor k, (2) a configured / desired number of samplesNf or paths L, (3 ) a configured / desired total number of measurements M, (4) a configured / desired measurement type with each scheme (e.g., just timing measurement, just power measurement, just phase measurement, paired timing and power measurements, pairedtimingand phase measurements, pairedpowerandphase measurements, paired timing, power, and phase measurements, etc.), (5) a configured / desired measurement timing, power, and / or phase reporting format (e.g, Type 1 codeword, Type 2 bitmap, and / or Type 3 differential codeword, etc.), (6) a configured / desired bitmap length (if configured / applicable), (7) a configured / desired Nt window length, (8) a configured / desiredNf selection rule, (9) a configured / desired Nt window placement rule, (10) anchoring of Nt or Nt’ samples with respect to first or strongestpathforthejointmeasurement scheme (e.g., Nt’ / Nt samples startingfrom an offset defined with respect to the first (or strongest) detected path, Nt’ / Nt samples around the first (or strongest) detected path, supported offset values for Nt’ / Nt measurement anchoring etc.), and / or (11) a configured / desired time, power, and / or phase referencing, etc.

[0140] Similarly, the network entity 1204 may indicate the configured / desired measurement scheme details / information based on supported measurement scheme capabilities and / or the applicable measurement scheme capabilities of the wireless device 1202. In some implementations, the network entity 1204 may also indicate, to the wireless device 1202, the prioritization between multiple or two measurement schemes. For example, the network entity 1204 may indicate to the wireless device 1202 that the sample-based measurement scheme is the baseline and default measurement scheme for the measurement and reporting and the path-based measurement scheme is129025-2490W001optional, or that the path-based measurement scheme is the baseline and default measurement scheme for the measurement and reporting and the sample-based measurement scheme is optional. Alternatively, the prioritization of the measurement scheme(s)may also be based on apre-configuration. For example, the wireless device 1202 may be predefined / preconfigured to apply a first measurement scheme as the default and the application of the second measurement scheme may be optional (e.g, predefined / preconfigured based on a specification).

[0141] In some implementations, the network entity 1204 may also indicate, to the wireless device 1202, a set of conditions on when to consider / apply one of the measurement schemes. Forexample, the set of conditions may include: (1) the wireless device 1202 conducts the path-based measurement scheme and reporting if the bandwidth (BW) (for measuring reference signals) satisfies a BW threshold, (2) the wireless device 1202 conducts the path-based measurement scheme and reporting if the delay spread satisfies a delay spread threshold, (3) the wireless device 1202 conducts the pathbased measurement and reporting if the RSRP satisfies an RSRP threshold, (4) the wireless device 1202 conducts the sample-based measurement scheme and reporting if the BW satisfies a BW threshold, (5) the wireless device 1202 conducts the samplebased measurement scheme and reporting if the delay spread satisfies a delay spread threshold, and / or (6) the wireless device 1202 conducts the sample-based measurement scheme and reporting if the RSRP satisfies an RSRP threshold, etc.

[0142] Based on the request from the network entity 1204, at 1218 and 1220, the wireless device 1202 may be configured to receive and measure / ob serve a set of reference signals (RSs) from another wireless device 1206 (e.g., a UE, base station, or TRP, etc.) to obtain a set of measurements based on one or more measurement types (e.g, just sample-based measurement, just path-based measurement, or both the samplebased and path-basedmeasurements). Depending on whether the wireless device 1202 and / or the wireless device 1206 is aUE, a base station, or a TRP, the set of RSs may include a set of positioning reference signals (PRSs), a set of sounding reference signals (SRSs), a set of synchronization signal blocks (SSBs), a set of channel start information reference signals (CSI-RSs), a set of sidelink (SL)-PRSs, a set of SL- SSBs, a set of SL-CSI-RS, or a combination thereof. For example, if the wireless device 1202 is a UE and the wireless device 1206 is a base station or a TRP, the set of RSs may be a set of PRSs, a set of SSBs, ora set of CSI-RSs. If the wireless device129025-2490W0011202 is a base station or a TRP and the wireless device 1206 is aUE, the set of RSs may be a set of SRSs. If the wireless device 1202 is a first UE and the wireless device 1206isa secondUE,the set of RSs may be a set of SL-PRSs, a setof SL-SSBs, and / or a set of SL-CSI-RS, etc.

[0143] At 1222, the wireless device 1202 may transmit / provide the set of measurements to the network entity 1204 (e.g., the measurements corresponding to the AI / ML input at the network entity 1204). In addition, the set of measurements may also include a set of indications / indicators on the measurement scheme(s) and / or type(s) used for obtaining the set of measurements.

[0144] For example, a dedicated LPP / NRPPa signaling / messaging may be configured for the wireless device 1202 for enablingthe wireless device 1202 to report indications on measurement scheme(s) applied and its related details along with the set of measurements for the input of the AI / ML at the network entity 1204 (e.g., for input at the LMF side AI / ML positioning model / functionality). Depending on implementations, the indications may be a set of dedicated filed(s) or information element(s) (IE(s)) in which the wireless device 1202 indicates the measurement scheme and details used / considered for obtaining the set of measurements. For example, the indication may be a dedicated field / IE that indicates the set of measurements is obtained usingthesample-basedmeasurementschemeor is obtained using the path-based measurement scheme. The wireless device 1202 may also include additional information / details in the indication(s), such as (1) the timing granularity factor k used / applied, (2) the number of samples Nt’ or paths L, (3) the Nt window size, (4) the bitmap length (if reported), (5) the timing, power, and / or phase format type, the (6) timing, power, and / or phase referencing option, (7) the rule(s) used to select Nt’ samples, and / or (8) therule(s) used to anchor Nt window and / or Nt’ samples, etc.

[0145] In some implementations, the wireless device 1202 may have the capability to provide / indicate one indication (or indication details / information described above) that it is common to multiple reported measurements, and / or common to multiple reported measurements per band, perPFL, per RS resource set, and / or per resource, etc. In another example (or as an alternative), the wireless device 1202 may have the capability to provide / indicate multiple indications (or indication details / information129025-2490W001described above) that are specific at a band, a PFL, an RS resource set, and / or a resource level.

[0146] In some examples, depending on the implementations, the wireless device 1202 may have the ability to choose whether to abide by the request from the network entity 1204 (e.g., received at 1216). For example, the wireless device 1202 may ignore the request from the network entity 1204 to use a specific measurement scheme, and perform the measurement using a default / preconfigured measurement scheme. For example, the wireless device 1202 may consider the path-based measurement scheme as the default and baseline measurement reporting scheme. In some examples, the wireless device 1202 may also have the capability to decide on the final parameters for path-based and / or sample-based measurement schemes (e.g., decide the values for k,Nt, Nt’, bitmap length, format, and / or referencing, etc.). Then, at 1222, the wireless device 1202 may indicate its final choice of the final parameters it used for measurement to the network entity 1204.

[0147] FIG. 13 is a flowchart 1300 of wireless communication. The method may be performed by a wireless device (e.g., the UE 104, 404, 702; the base station 102, 706; thewireless device 1202; the apparatus 1504; the network entity 1602). Themethod may enable the wireless device to consider and report measurements observed from the time-domain channel response (e.g., the sample-based measurements).

[0148] At 1308, the wireless device may receive, from a network entity, a request to perform a set of measurements for an AI / ML input, where the request includes a list of desired measurement schemes, such as described in connection with FIG. 12. For example, at 1216, based on the indication of measurement scheme(s) supported and / or applicable by the wireless device 1202 (e.g., received at 1210 and / or 1214), thewireless device 1202 may receive, from the network entity 1204, a request for a set of measurements that is to be used as an input for the AI / ML at the network entity 1204, where the request may indicate or configure at least one measurement scheme to be used for the set of measurements (e.g., selected from the ones supported / applicable by the wireless device 1202). The reception of the request may be performed by, e.g., the measurement scheme indication component 198, the transceiver(s) 1522, the cellular baseband processor(s) 1524, and / orthe application processor(s) 1506 of the apparatus 1504 in FIG. 15. The reception of the request may also be performed by, e.g., the measurement scheme indication component 199, the transceiver(s) 1646, the RU129025-2490W001processor(s) 1642, the DU processor(s) 1632, and / or the CU processor(s) 1612, of the network entity 1602 in FIG. 16.

[0149] In one example, the request to perform the set of measurements for the AI / ML input is specific to a band, a PFL, a TRP, an RS resource set, or an RS resource.

[0150] In another example, the request further indicates a set of parameters to be applied for each measurement scheme in the list of desired measurement schemes.

[0151] At 1314, the wireless device may perform the set of measurements for the AI / ML input using at least one measurement scheme in the list of desired measurement schemes, such as described in connection with FIG. 12. For example, at 1218 and 1220, the wireless device 1202 may be configured to receive and measure / ob serve a set of RSs from another wireless device 1206 (e.g., a UE, base station, or TRP, etc.) to obtain a set of measurements based on one or more measurement types (e.g., just sample-based measurement, just path-based measurement, or both the sample-based and path-based measurements). The set of measurements may be performed by, e.g, the measurement scheme indication component 198, the transceiver(s) 1522, the cellular baseband processor(s) 1524, and / or the application processor(s) 1506 of the apparatus 1504 in FIG. 15. The set of measurements may also be performed by, e.g, the measurement scheme indication component 199, the transceiver(s) 1646, the RU processor(s) 1642, the DU processor(s) 1632, and / or the CU processor(s) 1612, of the network entity 1602 in FIG. 16.

[0152] In one example, to perform the set of measurements for the AI / ML input using the at least one measurement scheme, the wireless device may be configured to receive a set of RSs, and measure the set of RSs using the at least one measurement scheme.

[0153] At 1316, the wireless device may transmit, to the network entity, the set of measurements for the AI / ML input and an indication of the at least one measurement scheme, such as described in connection with FIG. 12. For example, at 1222, the wireless device 1202 may transmit / provide the set of measurements to the network entity 1204 (e.g., the measurements corresponding to the AI / ML input at the network entity 1204). In addition, the set of measurements may also include a set of indications / indicators on the measurement scheme(s) and / or type(s) used for obtaining the set of measurements. The transmission of the set of measurements may be performed by, e.g., the measurement scheme indication component 198, the transceiver(s) 1522, the cellular baseband processor(s) 1524, and / or the application129025-2490W001processor(s) 1506 of the apparatus 1504 in FIG. 15. The reception of the request may also be performed by, e.g., the measurement scheme indication component 199, the transceiver(s) 1646, the RU processor(s) 1642, the DU processor(s) 1632, and / or the CU processor(s) 1612, of the network entity 1602 in FIG. 16.

[0154] In one example, the wireless device may transmit, to the network entity prior to reception of the request, a second indication of capabilities related to a set of measurement schemes for the AI / ML input, such as described in connection with FIG.12. For example, at 1210, the wireless device 1202 (e.g., aUE, aPRU, abase station, a TRP, etc.) may transmit, to the network entity 1204 (e.g., a location server, anLMF, an AI / ML server, a sensing management function, an AI / ML management function, a crowd-sourcing entity, a network data analytics function (NWDAF), etc.), an indication of its capability for measurement scheme(s) (and also type(s)) corresponding to input for AI / ML (e.g., for an AI / ML model / functionality at the network entity 1204, such as described in connection with FIGs. 8B and 9B). The transmission of the second indication may be performed by, e.g., the measurement scheme indication component 198, the transceiver(s) 1522, the cellular baseband processor(s) 1524, and / or the application processor(s) 1506 of the apparatus 1504 in FIG. 15. The transmission of the second indication may also be performed by, e.g, the measurement scheme indication component 199, the transceiver(s) 1646, the RU processor(s) 1642, the DU processor(s) 1632, and / or the CU processor(s) 1612, of the network entity 1602 in FIG. 16.

[0155] In some implementations, the reception of the request is based on transmission of the second indication.

[0156] In some implementations, the set of measurement schemes indicates at least one of:either a sample-based measurement or a path-based measurement is supported at a time, or both the sample-based measurement or the path-based measurement are supported. In some implementations, the set of measurement schemes further includes at least one of the sample-based measurement or the path -based measurement.

[0157] In some implementations, the capabilities related to the set of measurement schemes further includes limitation information for each measurement scheme in the set of measurement schemes.129025-2490W001

[0158] In some implementations, the wireless device may transmit, to the network entity prior to the reception of the request, a third indication of processing capabilities related to processing the set of measurement schemes for the AI / ML input.

[0159] In some implementations, the wireless device may receive, from the network entity, a second requestto provide the set of measurement schemes supported by the wireless device for the AI / ML input, where transmission of the second indication is based on the second request, such as described in connection with FIG. 12. For example, at 1212, the network entity 1204 may transmit, to the wireless device 1202, a requestto provide the capability for measurement schemes and types corresponding to input for AI / ML. The reception of the second request may be performed by, e.g., the measurement scheme indication component 198, the transceiver(s) 1522, the cellular baseband processor(s) 1524, and / or the application processor(s) 1506 of the apparatus 1504 in FIG. 15. The reception of the second request may also be performed by, e.g, the measurement scheme indication component 199, the transceiver(s) 1646, the RU processor(s) 1642, the DU processor(s) 1632, and / or the CU processor(s) 1612, of the network entity 1602 in FIG. 16.

[0160] In some implementations, the wireless device may transmit, to the network entity prior to the reception of the request, a third indication of a set of applicable measurement schemes for the AI / ML input, where the list of desired measurement schemes is based on the set of applicable measurement schemes, such as described in connection with FIG. 12. For example, at 1214, the wireless device 1202 may also provide an indication of applicable measurement scheme(s) corresponding to AI / ML input (e.g., after providing the indication of the supported measurement scheme(s) at 1210). For example, a dedicated LPP / NRPPa signaling / messaging may be configured for the wireless device 1202 for enabling the wireless device 1202 to indicate its applicable capabilities of measurement scheme(s) and type(s) that may be considered for the input of the AI / ML at the network entity 1204 (e.g., for input at the LMF side AI / ML positioningmodel / functionality). The transmission of the third indicationmay be performed by, e.g., the measurement scheme indication component 198, the transceiver(s) 1522, the cellular baseband processor(s) 1524, and / or the application processor(s) 1506 of the apparatus 1504 in FIG. 15. The transmission of the third indication may also be performed by, e.g., the measurement scheme indication component 199, the transceiver(s) 1646, the RU processor(s) 1642, the DU129025-2490W001processor(s) 1632, and / or the CU processor(s) 1612, of the network entity 1602 in FIG. 16.

[0161] In another example, the wireless device may receive, from the network entity, a priority associated with each measurement scheme in the list of desired measurement schemes, where performance of the set of measurements for the AI / ML input using the at least one measurement scheme in the list of desired measurement schemes is based on the priority associated with the at least one measurement scheme, such as described in connection with FIG. 12. For example, in some implementations, the wireless device 1202 may receive, from the network entity 1204, an indication of the prioritization between multiple or two measurement schemes. For example, the network entity 1204 may indicate to the wireless device 1202 that the sample-based measurement scheme is the baseline and default measurement scheme for the measurement and reporting and the path-based measurement scheme is optional, or that the path-based measurement scheme is the baseline and default measurement scheme for the measurement and reporting and the sample-based measurement scheme is optional. The reception of the priority associated with each measurement scheme may be performed by, e.g., the measurement scheme indication component 198, the transceiver(s) 1522, the cellular baseband processor(s) 1524, and / or the application processor(s) 1506 of the apparatus 1504 in FIG. 15. The reception of the priority associated with each measurement scheme may also be performed by, e.g, the measurement scheme indication component 199, the transceiver(s) 1646, the RU processor(s) 1642, the DU processor(s) 1632, and / or the CU processor(s) 1612, of the network entity 1602 in FIG. 16.

[0162] In another example, the wireless device may receive, from the network entity, a condition associated with the at least one measurement scheme, where performance of the set of measurements for the AI / ML input using the at least one measurement scheme in the list of desired measurement schemes is based on the condition associated with the at least one measurement scheme being satisfied, such as described in connection with FIG. 12. For example, in some implementations, the network entity 1204 may also indicate, to the wireless device 1202, a set of conditions on when to consider / apply one of the measurement schemes. The reception of the condition associated with the at least one measurement scheme may be performed by, e.g., the measurement scheme indication component 198, the transceiver(s) 1522, the129025-2490W001cellular baseband processor(s) 1524, and / orthe application processor(s) 1506 of the apparatus 1504 in FIG. 15. The reception of the condition associated with the at least one measurement scheme may also be performed by, e.g., the measurement scheme indication component 199, thetransceiver(s) 1646, the RU processor(s) 1642, the DU processor(s) 1632, and / orthe CU processor(s) 1612, of the network entity 1602 in FIG. 16.

[0163] In another example, the wireless device corresponds to aUE, a base station, or a TRP, and the network entity corresponds to an LMF, an NWDAF, an AI / ML management function, or a sensing management function.

[0164] FIG. 14 is a flowchart 1400 of wireless communication. The method may be performed by a wireless device (e.g., the UE 104, 404, 702; the base station 102, 706; the wireless device 1202; the apparatus 1504; the network entity 1602). The method may enable the wireless device to consider and report measurements observed from the time-domain channel response (e.g., the sample-based measurements).

[0165] At 1408, the wireless device may receive, from a network entity, a request to perform a set of measurements for an AI / ML input, where the request includes a list of desired measurement schemes, such as describedin connection with FIG. 12. For example, at 1216, based on the indication of measurement scheme(s) supported and / or applicable by the wireless device 1202 (e.g., received at 1210 and / or 1214), the wireless device 1202 may receive, from the network entity 1204, a request for a set of measurements that is to be used as an input for the AI / ML at the network entity 1204, where the request may indicate or configure at least one measurement scheme to be used for the set of measurements (e.g., selected from the ones supported / applicable by the wireless device 1202). The reception of the request may be performed by, e.g., the measurement scheme indication component 198, the transceiver(s) 1522, the cellular baseband processor(s) 1524, and / orthe application processor(s) 1506 of the apparatus 1504 in FIG. 15. The reception of the request may also be performed by, e.g., the measurement scheme indication component 199, the transceiver(s) 1646, the RU processor(s) 1642, the DU processor(s) 1632, and / orthe CU processor(s) 1612, of the network entity 1602 in FIG. 16.

[0166] In one example, the request to perform the set of measurements for the AI / ML input is specific to a band, a PFL, a TRP, an RS resource set, or an RS resource.129025-2490W001

[0167] In another example, the request further indicates a set of parameters to be applied for each measurement scheme in the list of desired measurement schemes.

[0168] At 1414, the wireless device may perform the set of measurements for the AI / ML input using at least one measurement scheme in the list of desired measurement schemes, such as described in connection with FIG. 12. For example, at 1218 and 1220, the wireless device 1202 may be configured to receive and measure / ob serve a set of RSs from another wireless device 1206 (e.g., a UE, base station, or TRP, etc.) to obtain a set of measurements based on one or more measurement types (e.g., just sample-based measurement, just path-based measurement, or both the sample-based and path-based measurements). The set of measurements may be performed by, e.g, the measurement scheme indication component 198, the transceiver(s) 1522, the cellular baseband processor(s) 1524, and / orthe application processor(s) 1506 of the apparatus 1504 in FIG. 15. The set of measurements may also be performed by, e.g, the measurement scheme indication component 199, the transceiver(s) 1646, the RU processor(s) 1642, the DU processor(s) 1632, and / orthe CU processor(s) 1612, of the network entity 1602 in FIG. 16.

[0169] In one example, to perform the set of measurements for the AI / ML input using the at least one measurement scheme, the wireless device may be configured to receive a set of RSs, and measure the set of RSs using the at least one measurement scheme.

[0170] At 1416, the wireless device may transmit, to the network entity, the set of measurements for the AI / ML input and an indication of the at least one measurement scheme, such as described in connection with FIG. 12. For example, at 1222, the wireless device 1202 may transmit / provide the set of measurements to the network entity 1204 (e.g., the measurements corresponding to the AI / ML input at the network entity 1204). In addition, the set of measurements may also include a set of indications / indicators on the measurement scheme(s) and / or type(s) used for obtaining the set of measurements. The transmission of the set of measurements may be performed by, e.g., the measurement scheme indication component 198, the transceiver(s) 1522, the cellular baseband processor(s) 1524, and / orthe application processor(s) 1506 of the apparatus 1504 in FIG. 15. The reception of the request may also be performed by, e.g., the measurement scheme indication component 199, the transceiver(s) 1646, the RU processor(s) 1642, the DU processor(s) 1632, and / orthe CU processor(s) 1612, of the network entity 1602 in FIG. 16.129025-2490W001

[0171] In one example, as shown at 1402, the wireless device may transmit, to the network entity prior to reception of the request, a second indication of capabilities related to a set of measurement schemes for the AI / ML input, such as described in connection with FIG. 12. For example, at 1210, the wireless device 1202 (e.g., a UE, a PRU, a base station, a TRP, etc.) may transmit, to the network entity 1204 (e.g., a location server, an LMF, an AI / ML server, a sensing management function, an AI / ML management function, a crowd-sourcing entity, a network data analytics function (NWDAF), etc.), an indication of its capability for measurement scheme(s) (and also type(s)) corresponding to input for AI / ML (e.g., for an AI / ML model / functionality at the network entity 1204, such as described in connection with FIGs. 8B and 9B). The transmission of the second indication may be performed by, e.g., the measurement scheme indication component 198, the transceiver(s) 1522, the cellular baseband processor(s) 1524, and / or the application processor(s) 1506 of the apparatus 1504 in FIG. 15. The transmission of the second indication may also be performed by, e.g, the measurement scheme indication component 199, the transceiver(s) 1646, the RU processor(s) 1642, the DU processor(s) 1632, and / or the CU processor(s) 1612, of the network entity 1602 in FIG. 16.

[0172] In some implementations, the reception of the request is based on transmission of the second indication.

[0173] In some implementations, the set of measurement schemes indicates at least one of:either a sample-based measurement or a path-based measurement is supported at a time, or both the sample-based measurement or the path-based measurement are supported. In some implementations, the set of measurement schemes further includes at least one of the sample-based measurement or the path-based measurement.

[0174] In some implementations, the capabilities related to the set of measurement schemes further includes limitation information for each measurement scheme in the set of measurement schemes.

[0175] In some implementations, the wireless device may transmit, to the network entity prior to the reception of the request, a third indication of processing capabilities related to processing the set of measurement schemes for the AI / ML input.

[0176] In some implementations, as shown at 1404, the wireless device may receive, from the network entity, a second request to provide the set of measurement schemes supported by the wireless device for the AI / ML input, where transmission of the129025-2490W001second indication is based on the secondrequest, such as describedin connection with FIG. 12. For example, at 1212, the network entity 1204 may transmit, to the wireless device 1202, a request to provide the capability for measurement schemes and types corresponding to input for AI / ML. The reception of the second request may be performed by, e.g., the measurement scheme indication component 198, the transceiver(s) 1522, the cellular baseband processor(s) 1524, and / or the application processor(s) 1506 of the apparatus 1504 in FIG. 15. The reception of the second request may also be performed by, e.g., the measurement scheme indication component 199, the transceiver(s) 1646, the RU processor(s) 1642, the DU processor(s) 1632, and / or the CU processor(s) 1612, of the network entity 1602 in FIG. 16.

[0177] In some implementations, as shown at 1406, the wireless device may transmit, to the network entity prior to the reception of the request, a third indication of a set of applicable measurement schemes for the AI / ML input, where the list of desired measurement schemes is based on the set of applicable measurement schemes, such as described in connection with FIG. 12. For example, at 1214, the wireless device 1202 may also provide an indication of applicable measurement scheme(s) corresponding to AI / ML input (e.g., after providing the indication of the supported measurement scheme(s) at 1210). For example, a dedicated LPP / NRPPa signaling / messaging may be configured for the wireless device 1202 for enabling the wireless device 1202 to indicate its applicable capabilities of measurement scheme(s) and type(s) that may be considered for the input of the AI / ML at the network entity 1204 (e.g., for input at the LMF side AI / ML positioning model / functionality). The transmission of the third indication may be performed by, e.g., the measurement scheme indication component 198, the transceiver(s) 1522, the cellular baseband processor(s) 1524, and / orthe application processor(s) 1506 ofthe apparatus 1504 in FIG. 15. The transmission of the third indication may also be performed by, e.g., the measurement scheme indication component 199, the transceiver(s) 1646, the RU processor(s) 1642, the DU processor(s) 1632, and / orthe CU processor(s) 1612, ofthe network entity 1602 in FIG. 16.

[0178] In another example, as shown at 1410, the wireless device may receive, from the network entity, a priority associated with each measurement scheme in the list of desired measurement schemes, where performance of the set of measurements for the129025-2490W001AI / ML input using the at least one measurement scheme in the list of desired measurement schemes is based on the priority associated with the at least one measurement scheme, such as describedin connection with FIG. 12. For example, in some implementations, the wireless device 1202 may receive, from the network entity 1204, an indication of the prioritization between multiple or two measurement schemes. For example, the network entity 1204 may indicate to the wireless device 1202 that the sample-based measurement scheme is the baseline and default measurement scheme for the measurement and reporting and the path-based measurement scheme is optional, or that the path-based measurement scheme is the baseline and default measurement scheme for the measurement and reporting and the sample-based measurement scheme is optional. The reception of the priority associated with each measurement scheme may be performed by, e.g., the measurement scheme indication component 198, the transceiver(s) 1522, the cellular baseband processor(s) 1524, and / or the application processor(s) 1506 of the apparatus 1504 in FIG. 15. The reception of the priority associated with each measurement scheme may also be performed by, e.g., the measurement scheme indication component 199, the transceiver(s) 1646, the RU processor(s) 1642, the DU processor(s) 1632, and / or the CU processor(s) 1612, of the network entity 1602 in FIG. 16.

[0179] In another example, as shown at 1412, the wireless device may receive, from the network entity, a condition associated with the at least one measurement scheme, where performance of the set of measurements for the AI / ML input using the at least one measurement scheme in the list of desired measurement schemes is based on the condition associated with the at least one measurement scheme being satisfied, such as described in connection with FIG. 12. For example, in some implementations, the network entity 1204 may also indicate, to the wireless device 1202, a set of conditions on when to consider / apply one of the measurement schemes. The reception of the condition associated with the at least one measurement scheme may be performed by, e.g., the measurement scheme indication component 198, the transceiver(s) 1522, the cellular baseband processor(s) 1524, and / or the application processor(s) 1506 of the apparatus 1504 in FIG. 15. The reception of the condition associated with the at least one measurement scheme may also be performed by, e.g., the measurement scheme indication component 199, thetransceiver(s) 1646, the RU processor(s) 1642, the DU129025-2490W001processor(s) 1632, and / or the CU processor(s) 1612, of the network entity 1602 in FIG. 16.

[0180] In another example, the wireless device corresponds to aUE, a base station, or a TRP, and the network entity corresponds to an LMF, an NWDAF, an AI / ML management function, or a sensing management function.

[0181] FIG. 15 is a diagram 1500 illustrating an example of a hardware implementation for an apparatus 1504. The apparatus 1504 may be aUE, a component of aUE, or may implement UE functionality. In some aspects, the apparatus 1504 may include atleast one cellular baseband processor 1524 (also referred to as a modem) coupled to one or more transceivers 1522 (e.g., cellular RF transceiver). The cellular baseband processor(s) 1524 may include at least one on-chip memory 1524'. In some aspects, the apparatus 1504 may further include one or more subscriber identity modules (SIM) cards 1520 and at least one application processor 1506 coupled to a secure digital (SD) card 1508 and a screen 1510. The application processor(s) 1506 may include on-chip memory 1506'. In some aspects, the apparatus 1504 may further include a Bluetooth module 1512, a WLAN module 1514, an ultrawide band (UWB) module 1538 (e.g., a UWB transceiver), an SPS module 1516 (e.g., GNSS module), one or more sensors 1518 (e.g., barometric pressure sensor / altimeter; motion sensor such as inertial measurement unit (IMU), gyroscope, and / or accelerometer(s); light detection and ranging (LIDAR), radio assisted detection and ranging (RADAR), sound navigation and ranging (SONAR), magnetometer, audio and / or other technologies used for positioning), additional memory modules 1526, a power supply 1530, and / or a camera 1532. The Bluetooth module 1512, the UWB module 1538, the WLAN module 1514, and the SPS module 1516 may include an on-chip transceiver (TRX) (or in some cases, just a receiver (RX)). The Bluetooth module 1512, the WLAN module 1514, and the SPS module 1516 may include their own dedicated antennas and / or utilize the antennas 1580 for communication. The cellular baseband processor(s) 1524 communicates through the transceiver(s) 1522 via one or more antennas 1580 with the UE 104 and / or with an RU associated with a network entity 1502. The cellular baseband processor(s) 1524 and the application processor(s) 1506 may each include a computer-readable medium / memory 1524', 1506', respectively. The additional memory modules 1526 may also be considered a computer-readable medium / memory. Each computer-readable medium / memory 1524', 1506', 1526129025-2490W001may be non-transitory. The cellular baseband processor(s) 1524 and the application processor(s) 1506 are each responsible for general processing, includingthe execution of software stored on the computer-readable medium / memory. The software, when executed by the cellular baseband processor(s) 1524 / application processor(s) 1506, causes the cellular baseband processor(s) 1524 / application processor(s) 1506 to perform the various functions described supra. The cellular baseband processors) 1524 and the application processor(s) 1506 are configured to perform the various functions described supra based at least in part of the information stored in the memory. That is, the cellular baseband processor(s) 1524 and the application processor(s) 1506 maybe configuredto perform a first sub set of the various functions described supra without information storedin the memory and may be configured to perform a second subset of the various functions described supra based on the information stored in the memory. The computer-readable medium / memory may also be used for storing data that is manipulated by the cellular baseband processors) 1524 / application processor(s) 1506 when executing software. The cellular baseband processor(s) 1524 / application processor(s) 1506 may be a component of the UE 350 and may include the at least one memory 360 and / or at least one of the TX processor 368, the RX processor 356, and the controller / processor 359. In one configuration, the apparatus 1504 may be at least one processor chip (modem and / or application) and include just the cellular baseband processor(s) 1524 and / or the application processor(s) 1506, and in another configuration, the apparatus 1504 may be the entire UE (e.g., see UE 350 of FIG. 3) and include the additional modules of the apparatus 1504.

[0182] As discussed supra, the measurement scheme indication component 198 may be configured to receive, from a network entity, a request to perform a set of measurements for an AI / ML input, where the request includes a list of desired measurement schemes. The measurement scheme indication component 198 may also be configured to perform the set of measurements for the AI / ML input using at least one measurement scheme in the list of desired measurement schemes. The measurement scheme indication component 198 may also be configured to transmit, to the network entity, the set of measurements for the AI / ML input and an indication of the at least one measurement scheme. The measurement scheme indication component 198 may be within the cellular baseband processor(s) 1524, the129025-2490W001application processor(s) 1506, orboththecellularbasebandprocessor(s) 1524 and the application processor(s) 1506. The measurement scheme indication component 198 may be one or more hardware components specifically configured to carry out the stated processes / algorithm, implemented by one or more processors configured to perform the stated processes / algorithm, stored within a computer-readable medium for implementation by one or more processors, or some combination thereof. When multiple processors are implemented, the multiple processors may perform the stated processes / algorithm individually or in combination. As shown, the apparatus 1504 may include a variety of components configured for various functions. In one configuration, the apparatus 1504, and in particular the cellular baseband processors) 1524 and / orthe application processor(s) 1506, may includemeans for receiving, from a network entity, a request to perform a set of measurements for an AI / ML input, where therequestincludesalistof desired measurement schemes. Theapparatus 1504 may further include means for performing the set of measurements for the AI / ML input using at least one measurement scheme in the list of desired measurement schemes. The apparatus 1504 may further include means for transmitting, to the network entity, the set of measurements for the AI / ML input and an indication of the at least one measurement scheme.

[0183] In one configuration, the request to perform the set of measurements for the AI / ML input is specific to a band, a PFL, a TRP, an RS resource set, or an RS resource.

[0184] In another configuration, the request further indicates a set of parameters to be applied for each measurement scheme in the list of desired measurement schemes.

[0185] In another configuration, the means for performing the set of measurements for the AI / ML input using the at least one measurement scheme may include configuring the apparatus 1504 to receive a setof RSs, and measure the setof RSs using the at least one measurement scheme.

[0186] In another configuration, the apparatus 1504 may further include means for transmitting, to the network entity prior to reception of the request, a second indication of capabilities related to a set of measurement schemes for the AI / ML input. In some implementations, the reception of the request is based on transmission of the second indication. In some implementations, the set of measurement schemes indicates at least one of: either a sample-based measurement or a path-based measurement is supported at a time, or both the sample-based measurement or the path-based129025-2490W001measurement are supported. In some implementations, the set of measurement schemes further includes at least one of the sample-based measurement or the pathbased measurement. In some implementations, the capabilities related to the set of measurement schemes further includes limitation information for each measurement scheme in the set of measurement schemes. In some implementations, the apparatus 1504 may further include means for transmitting, to the network entity prior to the reception of the request, a third indication of processing capabilities related to processing the set of measurement schemes for the AI / ML input. In some implementations, the apparatus 1504 may further include means for receiving, from the network entity, a second request to provide the set of measurement schemes supported by the wireless device for the AI / ML input, where transmission of the second indication is based on the second request.

[0187] In some implementations, the apparatus 1504 may further include means for transmitting, to the network entity prior to the reception of the request, a third indication of a set of applicable measurement schemes for the AI / ML input, where the list of desired measurement schemes is based on the setof applicable measurement schemes.

[0188] In another configuration, the apparatus 1504 may further include means for receiving from the network entity, a priority associated with each measurement scheme in the list of desired measurement schemes, where performance of the set of measurements for the AI / ML input using the at least one measurement scheme in the list of desired measurement schemes is based on the priority associated with the at least one measurement scheme.

[0189] In another configuration, the apparatus 1504 may further include means for receiving from the network entity, a condition associated with the at least one measurement scheme, where performance of the set of measurements for the AI / ML input using the at least one measurement scheme in the list of desired measurement schemes is based on the condition associated with the at least one measurement scheme being satisfied.

[0190] In another configuration, the apparatus 1504 corresponds to a UE, and the network entity corresponds to an LMF, an NWDAF, an AI / ML management function, or a sensing management function.

[0191] The means may be the measurement scheme indication component 198 of the apparatus 1504 configured to perform the functions recited by the means. As129025-2490W001described supra, the apparatus 1504 may include the TX processor 368, the RX processor 356, and the controller / processor 359. As such, in one configuration, the means may be the TX processor 368, the RX processor 356, and / or the controller / processor 359 configured to perform the functions recited by the means.

[0192] FIG. 16 is a diagram 1600 illustrating an example of a hardware implementation for a network entity 1602. The network entity 1602 may be aBS, a component of aBS, or may implement BS functionality. The network entity 1602 may include at least one of a CU 1610, a DU 1630, or an RU 1640. For example, depending on the layer functionality handled by the measurement scheme indication component 199, the network entity 1602 may include the CU 1610; both the CU 1610 and the DU 1630; each of the CU 1610, the DU 1630, and the RU 1640; the DU 1630; both the DU 1630 and the RU 1640; or the RU 1640. The CU 1610 may include at least one CU processor 1612. The CU processor(s) 1612 may include on-chip memory 1612'. In some aspects, the CU 1610 may further include additional memory modules 1614 and a communications interface 1618. The CU 1610 communicates with the DU 1630 through a midhaul link, such as an Fl interface. The DU 1630 may include at least one DU processor 1632. The DU processor(s) 1632 may include on-chip memory 1632'. In some aspects, the DU 1630 may further include additional memory modules 1634 and a communications interface 1638. TheDU 1630 communicates with the RU 1640 through a fronthaul link. The RU 1640 may include at least one RU processor 1642. The RU processor(s) 1642 may include on-chip memory 1642'. In some aspects, the RU 1640 may further include additional memory modules 1644, one or more transceivers 1646, antennas 1680, and a communications interface 1648. The RU 1640 communicates with the UE 104. The on-chip memory 1612', 1632', 1642' and the additional memory modules 1614, 1634, 1644 may each be considered a computer-readable medium / memory. Each computer-readable medium / memory may be non-transitory. Each of the processors 1612, 1632, 1642 is responsible for general processing, including the execution of software stored on the computer- readable medium / memory. The software, when executed by the corresponding processor(s) causes the processor(s) to perform the various functions described supra. The computer-readable medium / memory may also be used for storing data that is manipulated by the processor(s) when executing software.129025-2490W001

[0193] As discussed supra, the measurement scheme indication component 199 may be configured to receive, from a network entity (e.g., a second network entity), a request to perform a set of measurements for an AI / ML input, where the request includes a list of desired measurement schemes. The measurement scheme indication component 199 may also be configured to perform the set of measurements for the AI / ML input using at least one measurement scheme in the list of desired measurement schemes. The measurement scheme indication component 199 may also be configured to transmit, to the network entity, the set of measurements for the AI / ML input and an indication of the at least one measurement scheme. The measurement scheme indication component 199 may be within one or more processors of one or more of the CU 1610, DU 1630, and the RU 1640. The measurement scheme indication component 199 may be one or more hardware components specifically configured to carry out the stated processes / algorithm, implemented by one or more processors configured to perform the stated processes / algorithm, stored within a computer- readable medium for implementationby one or more processors, or some combination thereof. When multiple processors are implemented, the multiple processors may perform the stated processes / algorithm individually or in combination. The network entity 1602 may include a variety of components configured for various functions. In one configuration, the network entity 1602 may include means for receiving, from a network entity (e.g., a second network entity), a request to perform a set of measurements for an AI / ML input, where the request includes a list of desired measurement schemes. The network entity 1602 may further include means for performing the set of measurements for the AI / ML input using at least one measurement scheme in the list of desired measurement schemes. The network entity 1602 may further include means for transmitting, to the network entity, the set of measurements for the AI / ML input and an indication of the at least one measurement scheme.

[0194] In one configuration, the request to perform the set of measurements for the AI / ML input is specific to a band, a PFL, a TRP, an RS resource set, or an RS resource.

[0195] In another configuration, the requestfurther indicates a set of parameters to be applied for each measurement scheme in the list of desired measurement schemes.

[0196] In another configuration, the means for performing the set of measurements for the AI / ML input using the at least one measurement scheme may include configuring the129025-2490W001network entity 1602 to receive a set of RSs, and measure the set of RSs using the at least one measurement scheme.

[0197] In another configuration, the network entity 1602 may further include means for transmitting, to the network entity priorto reception ofthe request, a second indication of capabilities related to a set of measurement schemes for the AI / ML input. In some implementations, the reception of the request is based on transmission of the second indication. In some implementations, the set of measurement schemes indicates at least one of: either a sample-based measurement or a path-based measurement is supported at a time, or both the sample-based measurement or the path-based measurement are supported. In some implementations, the set of measurement schemes further includes at least one of the sample-based measurement or the pathbased measurement. In some implementations, the capabilities related to the set of measurement schemes further includes limitation information for each measurement scheme in the set of measurement schemes. In some implementations, the network entity 1602 may further include means for transmitting, to the network entity priorto the reception of the request, a third indication of processing capabilities related to processing the set of measurement schemes for the AI / ML input. In some implementations, the network entity 1602 may further include means for receiving from the network entity, a second request to provide the set of measurement schemes supported by the wireless device for the AI / ML input, where transmission of the second indication is based on the second request.

[0198] In some implementations, the network entity 1602 may further include means for transmitting, to the network entity prior to the reception of the request, a third indication of a set of applicable measurement schemes for the AI / ML input, where the list of desired measurement schemes is based on the set of applicable measurement schemes.

[0199] In another configuration, the network entity 1602 may further include means for receiving, from the network entity, a priority associated with each measurement scheme in the list of desired measurement schemes, where performance of the set of measurements for the AI / ML input using the at least one measurement scheme in the list of desired measurement schemes is based on the priority associated with the at least one measurement scheme.129025-2490W001

[0200] In another configuration, the network entity 1602 may further include means for receiving, from the network entity, a condition associated with the at least one measurement scheme, where performance of the set of measurements for the AI / ML input using the at least one measurement scheme in the list of desired measurement schemes is based on the condition associated with the at least one measurement scheme being satisfied.

[0201] In another configuration, the network entity 1602 corresponds to a base station or a TRP, and the network entity corresponds to an LMF, an NWDAF, an AI / ML management function, or a sensing management function.

[0202] The means may be the measurement scheme indication component 199 of the network entity 1602 configured to perform the functions recited by the means. As described supra, the network entity 1602 may include the TX processor 316, the RX processor 370, and the controller / processor 375. As such, in one configuration, the means may bethe TX processor 316, the RX processor 370, and / orthe controller / processor 375 configured to perform the functions recited by the means.

[0203] FIG. 17 is a flowchart 1700 of wireless communication. The method may be performed by a network entity (e.g. , the one or more location servers 168 ; the location server704; the network entity 1204, 1860). The method may enable the network entity to request a wireless device to provide measurements observed from the time-domain channel response (e.g., the sample-based measurements).

[0204] At 1702, the network entity may transmit, to a wireless device, a request to perform a set of measurements for an AI / ML input, where the request includes a list of desired measurement schemes, such as described in connection with FIG. 12. For example, at 1216, the network entity 1204 may transmit, to the wireless device 1202, a request for a set of measurements that is to be used as an input for the AI / ML at the network entity 1204, where the request may indicate or configure at least one measurement scheme to be used for the set of measurements (e.g., selected from the ones supported / applicable by the wireless device 1202). The transmission of the request may be performed by, e.g., the measurement scheme configuration component 197, the network processor(s) 1812, and / orthe network interface 1880 of the network entity 1860 in FIG. 18.

[0205] At 1704, the network entity may receive, from the wireless device, the set of measurements for the AI / ML input and an indication of at least one measurement129025-2490W001scheme associated with the wireless device for the set of measurements, such as described in connection with FIG. 12. For example, at 1222, the network entity 1204 may receive, from the wireless device 1202, the set of measurements to (e.g., the measurements corresponding to the AI / ML input at the network entity 1204). In addition, the set of measurements may also include a set of indications / indicators on the measurement scheme(s) and / ortype(s)usedforobtainingthe set of measurements. The reception of the set of measurements may be performed by, e.g., the measurement scheme configuration component 197, the network processor(s) 1812, and / or the network interface 1880 of the network entity 1860 in FIG. 18.

[0206] In one example, the network entity may receive, from the wireless device prior to transmission of the request, a second indication of capabilities related to a set of measurement schemes for the AI / ML input. In some implementations, the transmission of the request is based on reception of the second indication. In some implementations, the network entity may transmit, to the wireless device, a second request to provide the set of measurement schemes supported by the wireless device for the AI / ML input, where reception of the second indication is based on the second request. In some implementations, the network entity may receive, from the wireless device prior to the transmission of the request, a third indication of a set of applicable measurement schemes for the AI / ML input, where the list of desired measurement schemes is based on the set of applicable measurement schemes. In some implementations, the set of measurement schemes indicates at least one of: either a sample-based measurementor a path-based measurement is supported at a time, or both the sample-based measurement or the path-based measurement are supported. In some implementations, the set of measurement schemes further includes at least one of the sample-based measurement or the path-based measurement. In some implementations, the capabilities related to the set of measurement schemes further includes limitation information for each measurement scheme in the set of measurement schemes. In some implementations, the network entity may receive, from the wireless device prior to the transmission of the request, a third indication of processing capabilities related to processing the set of measurement schemes for the AI / ML input.

[0207] In another example, the request to perform the set of measurements for the AI / ML input is specific to a band, a PFL, a TRP, an RS resource set, or an RS resource.129025-2490W001

[0208] In another example, the request further indicates a set of parameters to be applied for each measurement scheme in the list of desired measurement schemes.

[0209] In another example, the network entity may transmit, to the wireless device, a priority associated with each measurement scheme in the list of desired measurement schemes.

[0210] In another example, the network entity may transmit, to the wireless device, a condition associated with the at least one measurement scheme.

[0211] In another example, the network entity corresponds to an LMF, an NWDAF, an AI / ML management function, or a sensing management function, and the wireless device corresponds to a UE, a base station, or a TRP.

[0212] FIG. 18 is a diagram 1800 illustrating an example of a hardware implementation for a network entity 1860. In one example, the network entity 1860 may be within the core network 120. The network entity 1860 may include at least one network processor 1812. The network processor(s) 1812 may include on-chip memory 1812'. In some aspects, the network entity 1860 may further include additional memory modules 1814. The network entity 1860communicatesviathenetworkinterfacel880 directly (e.g., backhaul link) or indirectly (e.g., through a RIC) with the CU 1802. The on-chip memory 1812' and the additional memory modules 1814 may each be considered a computer-readable medium / memory. Each computer-readable medium / memory may be non-transitory. The network processor(s) 1812 is responsible for general processing, including the execution of software stored on the computer- readable medium / memory. The software, when executed by the corresponding processor(s) causes the processor(s) to perform the various functions described supra. The computer-readable medium / memory may also be used for storing data that is manipulated by the processor(s) when executing software.

[0213] As discussed supra, the measurement scheme configuration component 197 may be configured to transmit, to a wireless device, a request to perform a set of measurements for an AI / ML input, where the request includes a list of desired measurement schemes. The measurement scheme configuration component 197 may also be configured to receive, from the wireless device, the set of measurements for the AI / ML input and an indication of at least one measurement scheme associated with the wireless device for the set of measurements. The measurement scheme configuration component 197 may be within the network processor(s) 1812. The129025-2490W001measurement scheme configuration component 197 may be one or more hardware components specifically configured to carry out the stated processes / algorithm, implemented by one or more processors configured to perform the stated processes / algorithm, stored within a computer-readable medium for implementation by one or more processors, or some combination thereof. When multiple processors are implemented, the multiple processors may perform the stated processes / algorithm individually or in combination. The network entity 1860 may include a variety of components configured forvarious functions. In one configuration, the networkentity 1860 may include means for transmitting, to a wireless device, a request to perform a set of measurements for an AI / ML input, where the request includes a list of desired measurement schemes. The network entity 1860 may further include means for receiving, from the wireless device, the set of measurements for the AI / ML input and an indication of at least one measurement scheme associated with the wireless device for the set of measurements.

[0214] In one configuration, the network entity 1860 may further include means for receiving, from the wireless device prior to transmission of the request, a second indication of capabilities related to a set of measurement schemes for the AI / ML input. In some implementations, the transmission of the request is based on reception of the second indication. In some implementations, the network entity 1860 may further include means for transmitting, to the wireless device, a second request to provide the set of measurement schemes supported by the wireless device for the AI / ML input, where reception of the second indication is based on the second request. In some implementations, the network entity 1860 may further include means for receiving from the wireless device prior to the transmission of the request, a third indication of a set of applicable measurement schemes for the AI / ML input, where the list of desired measurement schemes is based on the set of applicable measurement schemes. In some implementations, the set of measurement schemes indicates at least one of either a sample-based measurementor a path-based measurement is supported at a time, or both the sample-based measurement or the path-based measurement are supported. In some implementations, the set of measurement schemes further includes at least one of the sample-based measurement or the path-based measurement. In some implementations, the capabilities related to the set of measurement schemes further includes limitation information for each measurement scheme in the set of129025-2490W001measurement schemes. In some implementations, the network entity 1860 may further include means for receiving, from the wireless device prior to the transmission of the request, a third indication of processing capabilities related to processing the set of measurement schemes for the AI / ML input.

[0215] In another configuration, the request to perform the set of measurements for the AI / ML inputis specific to a band, aPFL, aTRP, an RS resource set, or an RS resource.

[0216] In another configuration, the request further indicates a set of parameters to be applied for each measurement scheme in the list of desired measurement schemes.

[0217] In another configuration, the network entity 1860 may further include means for transmitting, to the wireless device, a priority associated with each measurement scheme in the list of desired measurement schemes.

[0218] In another configuration, the network entity 1860 may further include means for transmitting, to the wireless device, a condition associated with the at least one measurement scheme.

[0219] In another configuration, the network entity 1860 corresponds to an LMF, an NWD AF, an AI / ML management function, or a sensing management function, and the wireless device corresponds to a UE, a base station, or a TRP.

[0220] The means may be the measurement scheme configuration component 197 of the network entity 1860 configured to perform the functions recited by the means.

[0221] It is understood that the specific order or hierarchy of blocks in the processes / flowcharts disclosed is an illustration of example approaches. Based upon design preferences, it is understood that the specific order or hierarchy of blocks in the processes / flowcharts maybe rearranged. Further, some blocks may be combined or omitted. The accompanying method claims present elements of the various blocks in a sample order, and are not limited to the specific order or hierarchy presented.

[0222] The previous description is provided to enable any person skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects. Thus, the claims are not limited to the aspects described herein, but are to be accorded the full scope consistent with the language claims. Reference to an element in the singular does not mean “one and only one” unless specifically so stated, but rather “one or more.” Terms such as “if,” “when,” and “while” do not imply an immediate temporal relationship or reaction. That is,129025-2490W001these phrases, e.g., “when,” do notimply an immediate action in response to or during the occurrence of an action, but simply imply that if a condition is met then an action will occur, butwithoutrequiringa specific or immediate time constraint for the action to occur. The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any aspect described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects. Unless specifically stated otherwise, the term “some” refers to one or more. Combinations such as “at least one of A, B, or C,” “one or more of A, B, or C,” “at least one of A, B, and C,” “one or more of A, B, and C,” and “A, B, C, or any combination thereof’ include any combination of A, B, and / or C, and may include multiples of A, multiples of B, or multiples of C. Specifically, combinations such as “at least one of A, B, or C,” “one or more of A, B, or C,” “at least one of A, B, and C,” “one or more of A, B, and C,” and “A, B, C, or any combination thereof’ may be A only, B only, C only, A and B, A and C, B and C, or A and B and C, where any such combinations may contain one or more member or members of A, B, orC. Sets should be interpreted as a set of elements where the elements number one or more. Accordingly, for a set of X, X would include one or more elements. When at least one processor (i.e., a set of one or more processors P) is configured to perform a set of functions F, each processor of P may be configured to perform a subset S of F, where S £ F. Accordingly, each processor of the at least one processor may be configured to perform a particular subset of the set of functions, where the subset is the full set, a proper subset of the set, or an empty subset of the set. A processor may be referred to as processor circuitry. A memory / memory module may be referred to as memory circuitry. If a first apparatus receives datafrom ortransmits data to a second apparatus, the data may be received / transmitted directly between the first and second apparatuses, or indirectly between the first and second apparatuses through a set of apparatuses. A device configured to “output” data or “provide” data, such as a transmission, signal, or message, may transmit the data, for example with a transceiver, or may send the data to a device that transmits the data. A device configured to “obtain” data, such as a transmission, signal, or message, may receive, for example with a transceiver, or may obtain the data from a device that receives the data. Information stored in a memory includes instructions and / or data. All structural and functional equivalents to the elements of the various aspects described throughout129025-2490W001this disclosure that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and are encompassed by the claims. Moreover, nothing disclosed herein is dedicated to the public regardless of whether such disclosure is explicitly recited in the claims. The words “module,” “mechanism,” “element,” “device,” and the like may not be a substitute for the word “means.” As such, no claim element is to be construed as a means plus function unless the element is expressly recited using the phrase “means for.”

[0223] As used herein, the phrase “based on” shall not be construed as a reference to a closed set of information, one or more conditions, one or more factors, or the like. In other words, the phrase “based on A” (where “A” may be information, a condition, a factor, or the like) shall be construed as “based at least on A” unless specifically recited differently.

[0224] The following aspects are illustrative only and may be combined with other aspects or teachings described herein, without limitation.

[0225] Aspect 1 is a method of wireless communication at a wireless device, comprising:receiving, from a network entity, a request to perform a set of measurements for an artificial intelligence (Al) or machine learning (ML) (AI / ML) input, wherein the request includes a list of desired measurement schemes; performing the set of measurements for the AI / ML input using at least one measurement scheme in the list of desired measurement schemes; and transmitting, to the network entity, the set of measurements for the AI / ML input and an indication of the at least one measurement scheme.

[0226] Aspect 2 is the method of aspect 1 , further comprising: transmitting, to the network entity prior to reception of the request, a second indication of capabilities related to a set of measurement schemes for the AI / ML input.

[0227] Aspect 3 is the method of aspect 1 or aspect 2, wherein the reception of the request is based on transmission of the second indication.

[0228] Aspect 4 is the method of any of aspects 1 to 3, further comprising: receiving, from the network entity, a second request to provide the set of measurement schemes supported by the wireless device for the AI / ML input, wherein transmission of the second indication is based on the second request.

[0229] Aspect 5 is the method of any of aspects 1 to 4, further comprising: transmitting, to the network entity prior to the reception of the request, a third indication of a set of129025-2490W001applicable measurement schemes for the AI / ML input, wherein the list of desired measurement schemes is based on the set of applicable measurement schemes.

[0230] Aspect 6 is the method of any of aspects 1 to 5, wherein the set of measurement schemes indicates at least one of: either a sample-based measurement or a path-based measurement is supported at a time, or both the sample-based measurementor the path-based measurement are supported.

[0231] Aspect 7 is the method of any of aspects 1 to 6, wherein the set of measurement schemes further includes at least one of the sample-based measurement or the pathbased measurement.

[0232] Aspect 8 is the method of any of aspects 1 to 7, wherein the capabilities related to the set of measurement schemes further includes limitation information for each measurement scheme in the set of measurement schemes.

[0233] Aspect 9 is the method of any of aspects 1 to 8, further comprising: transmitting, to the network entity prior to the reception of the request, a third indication of processing capabilities related to processing the set of measurement schemes for the AI / ML input.

[0234] Aspect 10 is the method of any of aspects 1 to 9, wherein the request to perform the set ofmeasurementsforthe AI / ML inputis specifictoaband, a positioningfrequency layer (PFL), a transmission reception point (TRP), a reference signal (RS) resource set, or an RS resource.

[0235] Aspect 11 is the method of any of aspects 1 to 10, wherein the request further indicates a set of parameters to be applied for each measurement scheme in the list of desired measurement schemes.

[0236] Aspect 12 is the method of any of aspects 1 to 11, further comprising: receiving from the network entity, a priority associated with each measurement scheme in the list of desired measurement schemes, wherein performance of the set of measurements for the AI / ML input using the at least one measurement scheme in the list of desired measurement schemes is based on the priority associated with the at least one measurement scheme.

[0237] Aspect 13 is the method of any of aspects 1 to 12, further comprising: receiving from the network entity, a condition associated with the at least one measurement scheme, wherein performance of the set of measurements for the AI / ML input using the at129025-2490W001least one measurement scheme in the list of desired measurement schemes is based on the condition associated with the at least one measurement scheme being satisfied.

[0238] Aspect 14 is the method of any of aspects 1 to 13, wherein performing the set of measurements for the AI / ML input using the at least one measurement scheme comprises: receiving a set of reference signals (RSs); and measuring the set of RSs using the at least one measurement scheme.

[0239] Aspect 15 is the method of any of aspects 1 to 14, wherein the wireless device correspondsto a user equipment (UE), abase station, or a transmission reception point (TRP), and wherein the network entity corresponds to a location management function (LMF), a network data analytics function (NWD AF), an AI / ML management function, or a sensing management function.

[0240] Aspect 16 is an apparatus for wireless communication at a wireless device, including:at least one memory; and at least one processor coupled to the at least one memory and, based at least in part on stored information that is stored in the at least one memory, the at least one processor, individually or in any combination, is configured to implement any of aspects 1 to 15.

[0241] Aspect 17 is the apparatus of aspect 16, further including at least one transceiver or at least one network interface coupled to the at least one processor.

[0242] Aspect 18 is an apparatus for wireless communication at a wireless device including means for implementing any of aspects 1 to 15.

[0243] Aspect 19 is a computer-readable medium (e.g., a non-transitory computer-readable medium) storing computer executable code, where the code when executed by a processor causes the processor to implement any of aspects 1 to 15.

[0244] Aspect 20 is a method of wireless communication at a network entity, comprising:transmitting, to a wireless device, a request to perform a set of measurements for an artificial intelligence (Al) or machine learning (ML) (AI / ML) input, wherein the request includes a list of desired measurement schemes; and receiving, from the wireless device, the set of measurements for the AI / ML input and an indication of at least one measurement scheme associated with the wireless device for the set of measurements.

[0245] Aspect21 is the method of aspect20, further comprising: receiving, from the wireless device prior to transmission of the request, a second indication of capabilities related to a set of measurement schemes for the AI / ML input.129025-2490W001

[0246] Aspect 22 is the method of aspect 20 or aspect 21 , wherein the transmission of the request is based on reception of the second indication.

[0247] Aspect 23 is the method of any of aspects 20 to 22, further comprising: transmitting to the wireless device, a second request to provide the set of measurement schemes supported by the wireless device for the AI / ML input, wherein reception of the second indication is based on the second request.

[0248] Aspect 24 is the method of any of aspects 20 to 23, further comprising: receiving from the wireless device prior to the transmission of the request, a third indication of a set of applicable measurement schemes for the AI / ML input, wherein the list of desired measurement schemes is based on the set of applicable measurement schemes.

[0249] Aspect 25 is the method of any of aspects 20 to 24, wherein the set of measurement schemes indicates at least one of: either a sample-based measurement or a path-based measurement is supported at a time, or both the sample-based measurementor the path-based measurement are supported.

[0250] Aspect 26 is the method of any of aspects 20 to 25, wherein the set of measurement schemes further includes at least one of the sample-based measurement or the pathbased measurement.

[0251] Aspect 27 is the method of any of aspects 20 to 26, wherein the capabilities related to the set of measurement schemes further includes limitation information for each measurement scheme in the set of measurement schemes.

[0252] Aspect 28 is the method of any of aspects 20 to 27, further comprising: receiving from the wireless device prior to the transmission of the request, a third indication of processing capabilities related to processing the set of measurement schemes for the AI / ML input.

[0253] Aspect 29 is the method of any of aspects 20 to 28, wherein the request to perform the set of measurements for the AI / ML input is specific to a band, a positioning frequency layer (PFL), a transmission reception point (TRP), a reference signal (RS) resource set, or an RS resource.

[0254] Aspect 30 is the method of any of aspects 20 to 29, wherein the request further indicates a set of parameters to be applied for each measurement scheme in the list of desired measurement schemes.129025-2490W001

[0255] Aspect 31 is the method of any of aspects 20 to 30, further comprising: transmitting to the wireless device, a priority associated with each measurement scheme in the list of desired measurement schemes.

[0256] Aspect 32 is the method of any of aspects 20 to 31, further comprising: transmitting to the wireless device, a condition associated with the at least one measurement scheme.

[0257] Aspect 33 is the method of any of aspects 20 to 32, wherein the network entity corresponds to a location management function (LMF), a network data analytics function (NWDAF), an AI / ML management function, or a sensing management function, and wherein the wireless device corresponds to a user equipment (UE), a base station, or a transmission reception point (TRP).

[0258] Aspect 34 is an apparatus for wireless communication at a network entity, including:at least one memory; and at least one processor coupled to the at least one memory and, based at least in part on stored information that is stored in the at least one memory, the at least one processor, individually or in any combination, is configured to implement any of aspects 20 to 33.

[0259] Aspect 35 is the apparatus of aspect 34, further including at least one network interface coupled to the at least one processor.

[0260] Aspect 36 is an apparatus for wireless communication at a network entity including means for implementing any of aspects 20 to 33.

[0261] Aspect 37 is a computer-readable medium (e.g., a non-transitory computer-readable medium) storing computer executable code, where the code when executed by a processor causes the processor to implement any of aspects 20 to 33.129025-2490W001

Claims

CLAIMSWHAT IS CLAIMED IS:

1. An apparatus for wireless communication at a wireless device, comprising: at least one memory; andat least one processor coupled to the at least one memory, wherein the at least one processor is configured to:receive, from a network entity, a request to perform a set of measurements for an artificial intelligence (Al) or machine learning (ML) (AI / ML) input, wherein the request includes a list of desired measurement schemes;perform the set of measurements for the AI / ML input using at least one measurement scheme in the list of desired measurement schemes; and transmit, to the network entity, the set of measurements for the AI / ML input and an indication of the at least one measurement scheme.

2. The apparatus of claim 1 , wherein the at least one processor is further configured to:transmit, to the network entity priorto reception of the request, a second indication of capabilities related to a set of measurement schemes for the AI / ML input.

3. The apparatus of claim 2, wherein the reception of the request is based on transmission of the second indication.

4. The apparatus of claim 2, wherein the at least one processor is further configured to:receive, from the network entity, a second request to provide the set of measurement schemes supported by the wireless device for the AI / ML input, wherein transmission of the second indication is based on the second request.

5. The apparatus of claim 2, wherein the at least one processor is further configured to:transmit, to the network entity prior to the reception of the request, a third indication of a set of applicable measurement schemes for the AI / ML input, wherein the129025-2490W001list of desired measurement schemes is based on the set of applicable measurement schemes.

6. The apparatus of claim 2, wherein the set of measurement schemes indicates at least one of:either a sample-based measurement or a path -based measurement is supported at a time, orboth the sample-based measurement or the path-based measurement are supported.

7. The apparatus of claim 6, wherein the set of measurement schemes further includes at least one of the sample-based measurement or the path-based measurement.

8. The apparatus of claim 2, wherein the capabilities related to the set of measurement schemes further includes limitation information for each measurement scheme in the set of measurement schemes.

9. The apparatus of claim 2, wherein the at least one processor is further configured to:transmit, to the network entity prior to the reception of the request, a third indication of processing capabilities related to processingthe set of measurement schemes for the AI / ML input.

10. The apparatus of claim 1 , wherein the request to perform the set of measurements for the AI / ML input is specific to a band, a positioning frequency layer (PFL), a transmission reception point (TRP), a reference signal (RS) resource set, or an RS resource.

11. The apparatus of claim 1, wherein the request further indicates a set of parameters to be applied for each measurement scheme in the list of desired measurement schemes.

12. The apparatus of claim 1, wherein the at least one processor is further configured to:129025-2490W001receive, from the network entity, a priority associated with each measurement scheme in the list of desired measurement schemes, wherein performance of the set of measurements for the AI / ML input using the at least one measurement scheme in the list of desired measurement schemes is based on the priority associated with the at least one measurement scheme.

13. The apparatus of claim 1 , wherein the at least one processor is further configured to:receive, from the network entity, a condition associated with the at least one measurement scheme, wherein performance of the set of measurements for the AI / ML input using the at least one measurement scheme in the list of desired measurement schemes is based on the condition associated with the at least one measurement scheme being satisfied.

14. The apparatus of claim 1, wherein to perform the set of measurements for the AI / ML input using the at least one measurement scheme, the at least one processor is configured to:receive a set of reference signals (RSs); andmeasure the set of RSs using the at least one measurement scheme.

15. The apparatus of claim 1, wherein the wireless device corresponds to a user equipment (UE), a base station, or a transmission reception point (TRP), and wherein the network entity corresponds to a location management function (LMF), a network data analytics function (NWDAF), an AI / ML management function, ora sensingmanagement function.

16. A method of wireless communication at a wireless device, comprising:receiving, from a network entity, a request to perform a set of measurements for an artificial intelligence (Al) or machine learning (ML) (AI / ML) input, wherein the request includes a list of desired measurement schemes;performing the set of measurements for the AI / ML input using at least one measurement scheme in the list of desired measurement schemes; and129025-2490W001transmitting, to the network entity, the set of measurements for the AI / ML input and an indication of the at least one measurement scheme.

17. An apparatus for wireless communication at a network entity, comprising: at least one memory; andat least one processor coupled to the at least one memory, wherein the at least one processor is configured to:transmit, to a wireless device, a request to perform a set of measurements for an artificial intelligence (Al) or machine learning (ML) (AI / ML) input, wherein the request includes a list of desired measurement schemes; and receive, from the wireless device, the set of measurements for the AI / ML input and an indication of at least one measurement scheme associated with the wireless device for the set of measurements.

18. The apparatusof claim 17, wherein theatleastoneprocessoris further configured to:receive, from the wireless device prior to transmission of the request, a second indication of capabilities related to a set of measurement schemes for the AI / ML input.

19. The apparatus of claim 18, wherein the transmission of the request is based on reception of the second indication.

20. The apparatusof claim 18, wherein the at least one processor is further configured to:transmit, to the wireless device, a second request to provide the set of measurement schemes supported by the wireless device for the AI / ML input, wherein reception of the second indication is based on the second request.

21. The apparatusof claim 18, wherein the at least one processor is further configured to:receive, from the wireless device prior to the transmission of the request, a third indication of a set of applicable measurement schemes for the AI / ML input, wherein the129025-2490W001list of desired measurement schemes is based on the set of applicable measurement schemes.

22. The apparatus of claim 18, wherein the set of measurement schemes indicates at least one of:either a sample-based measurement or a path -based measurement is supported at a time, orboth the sample-based measurement or the path-based measurement are supported.

23. The apparatus of claim 22, wherein the set of measurement schemes further includes at least one of the sample-based measurement or the path-based measurement.

24. The apparatus of claim 18, wherein the capabilities related to the set of measurement schemes further includes limitation information for each measurement scheme in the set of measurement schemes.

25. The apparatusof claim 18, wherein the at least one processor is further configured to:receive, from the wireless device prior to the transmission of the request, a third indication of processing capabilities related to processingthe set of measurement schemes for the AI / ML input.

26. The apparatus of claim 17, wherein the requestto perform the set of measurements for the AI / ML input is specific to a band, a positioning frequency layer (PFL), a transmission reception point (TRP), a reference signal (RS) resource set, or an RS resource.

27. The apparatus of claim 17, wherein the request further indicates a set of parameters to be applied for each measurement scheme in the list of desired measurement schemes.129025-2490W00128. The apparatusof claim 17, wherein theatleastoneprocessoris further configured to:transmit, to the wireless device, at least one of (1) a priority associated with each measurement scheme in the list of desired measurement schemes, or (2) a condition associated with the at least one measurement scheme.

29. The apparatus of claim 17, wherein the network entity corresponds to a location management function (LMF), a network data analytics function (NWDAF), an AI / ML management function, or a sensing management function, and wherein the wireless device corresponds to a user equipment (UE), a base station, or a transmission reception point (TRP).

30. A method of wireless communication at a network entity, comprising:transmitting, to a wireless device, a request to perform a set of measurements for an artificial intelligence (Al) or machine learning (ML) (AI / ML) input, wherein the request includes a list of desired measurement schemes; andreceiving, from the wireless device, the set of measurements for the AI / ML input and an indication of at least one measurement scheme associated with the wireless device for the set of measurements.129025-2490W001

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