Reference resource enhancements for ai / ML positioning

Abstract

Aspects presented herein may improve the overall performance and accuracy of artificial intelligence (AI) or machine learning (ML) (AI / ML) positioning by enabling a user equipment (UE) to communicate with a network regarding reference resources the UE uses for AI / ML positioning, such that the network is able to know which reference resources are used for which AI / ML models. In one aspect, a UE communicates, with a network entity, an indication of a set of reference transmission reception points (TRPs) or resources for AI / ML, where the AI / ML is used in association with positioning. The UE performs at least one of the positioning or a set of measurements for the positioning with the AI / ML using at least one reference TRP or resource in the set of reference TRPs or resources.

Description

Qualcomm Ref. No. 2406551WO 1REFERENCE RESOURCE ENHANCEMENTS FOR AI / ML POSITIONINGCROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims the benefit of Greek Patent Application No. 20240100844, entitled “REFERENCE RESOURCE ENHANCEMENTS FOR AI / ML POSITIONING” and filed on November 26, 2024, 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.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), massive machine type communications (mMTC), and ultra-reliable low latency129025-2466WO01Qualcomm Ref. No. 2406551WO 2 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 positioning protocols and techniques that enable mobile network operators to provide high-accuracy location services to their subscribers. For example, 5G NR include various standards for network-based positioning that use signals and features of the 5G network 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 communicates, with a network entity, an indication of a set of reference transmission reception points (TRPs) or resources for artificial intelligence (Al) or machine learning (ML) (AI / ML), where the AI / ML is used in association with positioning. The apparatus performs at least one of the positioning or a set of measurements for the positioning with the AI / ML using at least one reference TRP or resource in the set of reference TRPs or resources.

[0008] In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus communicates, with a user equipment (UE), an indication of a set of reference transmission reception points (TRPs) or resources for artificial intelligence (Al) or machine learning (ML) (AI / ML), where the AI / ML is used in association with positioning. The apparatus receives, from the UE, at least one of a position of the UE or a set of measurements for positioning of the UE obtained based on at least one reference TRP or resource in the set of reference TRPs or resources.129025-2466WO01Qualcomm Ref. No. 2406551WO 3

[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.

[0017] FIG. 5A is a diagram illustrating an example of direct artificial intelligence (Al) / machine learning (ML) (AI / ML) positioning in accordance with various aspects of the present disclosure.

[0018] FIG. 5B is a diagram illustrating an example of AI / ML assisted positioning in accordance with various aspects of the present disclosure.

[0019] FIG. 6 is a diagram illustrating an example of different configurations for AI / ML assisted positioning in accordance with various aspects of the present disclosure.

[0020] FIG. 7 is a diagram illustrating an example of UE-based positioning with UE-side AI / ML model, direct AI / ML or AI / ML assisted positioning in accordance with various aspects of the present disclosure.129025-2466WO01Qualcomm Ref. No. 2406551WO 4

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

[0025] FIG. 10 is a diagram illustrating an example assistance data that includes reference positioning reference signal (PRS) information in accordance with various aspects of the present disclosure.

[0026] FIG. 11 is a diagram illustrating an example information element (IE) PRS identification (ID) information that includes reference PRS information in accordance with various aspects of the present disclosure.

[0027] FIG. 12 is a communication flow illustrating an example of configuring reference resource(s) for AI / ML in accordance with various aspects of the present disclosure.

[0028] FIG. 13 is a diagram illustrating an example measurement report structure that may be used by a UE for providing reference transmission reception point(s) (TRP(s)) or resource(s) it uses for AI / ML model(s) / functionalities in accordance with various aspects of the present disclosure.

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

[0030] FIG. 15 is a flowchart of a method of wireless communication.

[0031] FIG. 16 is a diagram illustrating an example of a hardware implementation for an example apparatus and / or 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 DESCRIPTION129025-2466WO01Qualcomm Ref. No. 2406551WO 5

[0034] Aspects presented herein may improve the overall performance and accuracy of artificial intelligence (Al) or machine learning (ML) (AI / ML) positioing by enabling a user equipment (UE) to communicate with a network regarding reference resources (e.g., reference positioning reference signal(s) (PRS(s)) or transmission reception point(s) (TRP(s)) the UE uses for AI / ML positioning (and optionally for non- AI / ML positioning), such that the network is able to know which reference resources are used for which AI / ML models. Then, the network may ensure specified AI / ML model(s) are used for corresponding reference references or vice versa, thereby promotning a consistency between different AI / ML operations (e.g., between data collection, measurement, inference, and / or training, etc.).

[0035] Reference TRPs may be different for different AI / ML models. Aspects presented herein provide signaling and configuration associated with the reference TRPs resource information for an AI / ML model. In one example, an existing DL-PRS-ID- Info structure may provide an indication of the reference for an AI / ML model. In another example, a new reference structure may provide an indication of the reference for an AI / ML model. In another example, an AI / ML model may be trained / monitored with multiple reference TRPs / resources. Priority among reference TRPs / resources may be provided by a Icoatoin management function (LMF). The LMF or a base station (BS) may switch TRPs / resources at any time during positioning. A UE may recommend reference TRPs / resources to an LMF. The LMF / UE may indicate reference TRP and TRP resources sets for one or more of AI / ML (e.g., data collection, training, monitoring, inference). In another example, UE capabilities may indicate the number of TRP and TRP resources sets supported for AI / ML data collection, training, monitoring, inference etc. In another example, a device (UE or BS / TRP) may be configured with at least two reference TRPs, one for AIML and the other for non- AIML measurements and assistance.

[0036] 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 herein may 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.129025-2466WO01Qualcomm Ref. No. 2406551WO 6

[0037] Several aspects of telecommunication systems are presented with reference to 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 as “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.

[0038] 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.

[0039] 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 implemented in software, the functions may be 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, magnetic129025-2466WO01Qualcomm Ref. No. 2406551WO 7 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.

[0040] While aspects, implementations, and / or use cases are described in 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 / or use cases described herein may be implemented across many differing platform 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 / or use 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 incorporating one 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.

[0041] 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 an129025-2466WO01Qualcomm Ref. No. 2406551WO 8 aggregated or disaggregated architecture. For example, a BS (such as a Node B (NB), evolved NB (eNB), NR BS, 5G NB, access point (AP), a transmission reception point (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.

[0042] 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).

[0043] 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.

[0044] 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) Framework129025-2466WO01Qualcomm Ref. No. 2406551WO 9105, 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 or more 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, the UE 104 may be simultaneously served by multiple RUs 140.

[0045] Each of the units, i.e., the CUs 110, the DUs 130, the RUs 140, as well as the Near- 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.

[0046] 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, the CU 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.

[0047] 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 DU129025-2466WO01Qualcomm Ref. No. 2406551WO 10130 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 for forward 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.

[0048] 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.

[0049] The SMO Framework 105 may be configured to support RAN deployment and provisioning of non-virtualized and virtualized network elements. For non-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 140 and Near-RT RICs 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 SMO129025-2466WO01Qualcomm Ref. No. 2406551WO 11Framework 105 can communicate directly with one or more RUs 140 via an 01 interface. The SMO Framework 105 also may include a Non-RT RIC 115 configured to support functionality of the SMO Framework 105.

[0050] 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. The Near-RT RIC 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.

[0051] 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-RT RIC 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).

[0052] At least one of the CU 110, the DU 130, and the RU 140 may be referred to as a base station 102. Accordingly, a base station 102 may include one or more of the 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 a UE 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 group129025-2466WO01Qualcomm Ref. No. 2406551WO 12 known as a closed subscriber group (CSG). The communication links between the RUs 140 and the UEs 104 may include uplink (UL) (also referred to as reverse link) transmissions from a UE 104 to an RU 140 and / or downlink (DL) (also referred to as forward link) transmissions from an RU 140 to a UE 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 F MHz (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 respect to DL and UL (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).

[0053] 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. The D2D 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.

[0054] 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 or the 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.129025-2466WO01Qualcomm Ref. No. 2406551WO 13

[0055] The electromagnetic spectrum is often subdivided, based on frequency / wavelength, into various classes, bands, channels, etc. In 5GNR, two initial operating bands have been 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” band in 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.

[0056] The frequencies between FR1 and FR2 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 5GNR operation beyond 52.6 GHz. For example, three higher operating bands have been identified as frequency range designations FR2-2 (52.6 GHz - 71 GHz), FR4 (71 GHz - 114.25 GHz), and FR5 (114.25 GHz - 300 GHz). Each of these higher frequency bands falls within the EHF band.

[0057] With the above aspects in mind, unless specifically stated otherwise, the term “sub-6 GHz” 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.

[0058] 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 more129025-2466WO01Qualcomm Ref. No. 2406551WO 14 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 / UE 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.

[0059] 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, 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).

[0060] 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 positioning129025-2466WO01Qualcomm Ref. No. 2406551WO 15 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 UE 104. The NG-RAN may utilize one or more positioning methods in order to determine the position of the UE 104. Positioning the 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, NR signals (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.

[0061] 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.). The UE 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.129025-2466WO01Qualcomm Ref. No. 2406551WO 16

[0062] Referring again to FIG. 1, in certain aspects, the UE 104 may have a reference resource processing component 198 that may be configured to communicate, with a network entity, an indication of a set of reference TRPs or resources for AI / ML, where the AI / ML is used in association with positioning; and perform at least one of the positioning or a set of measurements for the positioning with the AI / ML using at least one reference TRP or resource in the set of reference TRPs or resources. In certain aspects, the one or more location servers 168 may have a reference resource configuration component 197 that may be configured to communicate, with a UE, an indication of a set of reference TRPs or resources for AI / ML, where the AI / ML is used in association with positioning; and receive, from the UE, at least one of a position of the UE or a set of measurements for positioning of the UE obtained based on at least one reference TRP or resource in the set of reference TRPs or resources. In certain aspects, the base station 102 may have a reference resource configuration component 199 that may be configured to provide reference resource related configurations to the UE 104.

[0063] FIG. 2A is a diagram 200 illustrating an example of a first subframe within a 5G NR 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 5G NR subframe. The 5G 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 and UL. 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 2-61 include a mix of DL, UL, and flexible symbols. UEs are configured with the slot format (dynamically through DL control information (DCI), or semi-129025-2466WO01Qualcomm Ref. No. 2406551WO 17 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.

[0064] FIGs. 2A-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

[0065] For normal CP (14 symbols / slot), different numerologies p 0 to 4 allow for 1, 2, 4, 8, and 16 slots, respectively, per subframe. For extended CP, the numerology 2 allows for 4 slots per subframe. Accordingly, for normal CP and numerology p, there are 14 symbols / slot and 2^ slots / subframe. The subcarrier spacing may be equal to 2 / z*129025-2466WO01Qualcomm Ref. No. 2406551WO 1815 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 / duration is 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).

[0066] 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.

[0067] 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 R for one particular configuration, but other DM-RS configurations are possible) and channel state information reference signals (CSI-RS) for channel estimation at the UE. The RS may also include beam measurement RS (BRS), beam refinement RS (BRRS), and phase tracking RS (PT-RS).

[0068] 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 a physical 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 a129025-2466WO01Qualcomm Ref. No. 2406551WO 19 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)ZPBCH 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.

[0069] 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.

[0070] 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.

[0071] 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 layer129025-2466WO01Qualcomm Ref. No. 2406551WO 202 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.

[0072] 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, and MIMO 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 combined together using an Inverse Fast Fourier Transform (IFFT) to produce a physical channel carrying a time domain OFDM symbol stream. The OFDM stream is spatially precoded to produce multiple spatial streams. Channel estimates from a channel129025-2466WO01Qualcomm Ref. No. 2406551WO 21 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.

[0073] 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. The RX processor 356 may perform spatial processing on the information to recover any spatial streams destined for the UE 350. 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 be 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.

[0074] 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 IP packets. The controller / processor 359 is also responsible for error detection using an ACK and / or NACK protocol to support HARQ operations.

[0075] Similar to the functionality described in connection with the DL transmission by the base station 310, the controller / processor 359 provides RRC layer functionality129025-2466WO01Qualcomm Ref. No. 2406551WO 22 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.

[0076] 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 354Tx may modulate an RF carrier with a respective spatial stream for transmission.

[0077] The UL transmission is processed at the base station 310 in a manner similar to that described in connection with the receiver function at the 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.

[0078] 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.

[0079] 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 reference resource processing component 198 of FIG. 1.129025-2466WO01Qualcomm Ref. No. 2406551WO 23

[0080] 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 reference resource configuration component 199 of FIG. 1.

[0081] FIG. 4 is a diagram 400 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. The UE 404 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 TPRS TX. 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 server(s) 168) or the UE 404 may determine the RTT 414 based on ||TSRS_RX - TPRS TX| - |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 - TPRS _TX|) 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 at the 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.

[0082] 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 sweeping may 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,”129025-2466WO01Qualcomm Ref. No. 2406551WO 24 and a new Information Element (IE) may be configured for SRS for positioning in RRC signaling.

[0083] 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 reference point for the DL 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. For FR1 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 corresponding to 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.

[0084] 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 1st 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.

[0085] 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 the positioning server, and the resulting measurements are used along with the azimuth angle of departure (A-AoD), the zenith angle of departure (Z-AoD), and other129025-2466WO01Qualcomm Ref. No. 2406551WO 25 configuration information to locate the UE 404 in relation to the neighboring TRPs 402, 406.

[0086] 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.

[0087] 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.

[0088] UL-AoA positioning may 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 / positioning entity / server to be used in the computation of the UE’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 may be described as “UE-based,” “UE-based positioning,” and / or “UE-based position calculation.”

[0089] 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, to supplement / complement measurements, and / or to substitute / provide for missing information.129025-2466WO01Qualcomm Ref. No. 2406551WO 26

[0090] 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 refer to a particular geographical or a relative place.

[0091] 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.

[0092] “DL reference signal time difference (DL RSTD)” 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 corresponding start 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 subframe129025-2466WO01Qualcomm Ref. No. 2406551WO 27 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.

[0093] “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 not be lower than the corresponding DL PRS-RSRP of any of the individual receiver branches.

[0094] “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 1st 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

[0095] “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.

[0096] “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 transmission129025-2466WO01Qualcomm Ref. No. 2406551WO 28 point (TP) j and the reference TP i. 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.

[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. For example, an AI / ML model may be trained to determine the position of a UE based on DL-AoA, DL-TDOA, channel impulse response (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 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.).

[0098] 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 positioning measurements 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-129025-2466WO01Qualcomm Ref. No. 2406551WO 29 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 referring to an underlying model (physical and / or logical). The AI / ML functionality may 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 output may refer to a specific measurement type / 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.”

[0100] FIG. 5A is a diagram 500A 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, a UE may receive and measure PRSs transmitted from one or more base stations, and the UE may determine its position using an AI / ML model based on the PRS measurements. In another example, an LMF may receive PRS measurements from a UE or SRS measurements from a base station, and the LMF may determine the position of the UE using an AI / ML model based on the PRS / SRS measurements.129025-2466WO01Qualcomm Ref. No. 2406551WO 30

[0101] FIG. 5B is a diagram 500B 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 assist the measurement of reference signals (e.g., positioning reference 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 the UE based on a non- AI / ML mechanism / algorithm, or based on using an AI / ML model to determine the position of the UE. For example, a UE may receive and measure PRSs transmitted from one or more base stations, and the UE may transmit the PRS measurements to an LMF. The PRS measurements may include intermediate measurements, such as timing and / or angle of the PRSs, whether the PRSs are received based on a line-of- sight (LOS) condition or a non-line-of-sight (NLOS) condition, etc. Then, the LMF may determine the position of the UE based on the PRS measurements (e.g., the intermediate measurements) with or without using an AI / ML model. Similarly, a base station may receive and measure SRSs transmitted from a UE, and the baes station may transmit the SRS measurements to an LMF. Then, the LMF may determine the position of the UE based on the SRS measurements (e.g., the intermediate measurements) with or without using an AI / ML model.

[0102] FIG. 6 is a diagram 600 illustrating an example of different configurations for AI / ML assisted positioning in accordance with various aspects of the present disclosure. In one example, as shown at 610, for AI / ML assisted positioning, a same AI / ML model may be used for multiple transmission reception points (TRPs), where one AI / ML model may be configured for each TRP (referring to as a “single- TRP” setting). For example, a UE 602 may receive a set of positioning reference signals from N TRPs (e.g., from a first TRP, a second TRP, ..., and up to an N* TRP), and measure the channel impulse response (CIR) for the set of positioning reference signals from each TRP. Then, the UE 602 may input the measured CIR for each TRP to an AI / ML model (e.g., AI / ML Model A) configured for / associated with each TRP, where the AI / ML model may infer the time of arrival (ToA) of the positioning reference signal for the corresponding TRP based on the corresponding CIR. In other words, CIR of the first TRP is input to an AI / ML model A associated with the first TRP, CIR of the second129025-2466WO01Qualcomm Ref. No. 2406551WO 31TRP is input to an AI / ML model A associated with the second TRP, and CIR of the N111TRP is input to an AI / ML model A associated with the N111TRP, etc.

[0103] In another example, as shown at 612, different AI / ML models may be used for multiple TRPs, where one AI / ML model may be configured for each TRP (e.g., also the “single-TRP” setting but each TRP may use a different AI / ML model). For example, CIR of the first TRP may be input to a first AI / ML model (e.g., AI / ML Model Bi) for inferring the ToA of the first TRP, CIR of the second TRP may be input to a second AI / ML model (e.g., AI / ML Model B2 that is different from AI / ML Model Bi) for inferring the ToA of the second TRP, and CIR of the N111TRP may be input to an N111AI / ML model (e.g., AI / ML Model BN that is different from AI / ML Model Bi and AI / ML Model B2) for inferring the ToA of the AI / ML Model Bi TRP, etc.

[0104] In another example, as shown at 614, one AI / ML model may be used for multiple TRPs (referring to as a “multi-TRP” setting). For example, CIRs from the N TRPs may be input to one AI / ML model (e.g., AI / ML Model C), and the AI / ML model may infer the ToA for each TRP. For AI / ML assisted positioning, different model input realizations may have different implications on accuracy, generalization, robustness, as well as model complexity and life cycle management (LCM).

[0105] FIG. 7 is a diagram 700 illustrating an example of UE-based positioning with UE-sideAI / 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, such as measuring the reference signal received power (RSRP), channel impulse response (CIR), DL-AoD, reference signal time difference (RSTD), time of arrival (ToA), 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) ” Note the base station 706 may include a single base station, one or multiple TRPs of a base station, multiple base stations, or multiple TRPs from multiple base stations, etc. 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 may129025-2466WO01Qualcomm Ref. No. 2406551WO 32 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.

[0106] FIG. 8A is a diagram 800A illustrating an example of UE-assisted / LMF-based positioning with 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 a base station 706 with the assistance of the at least one AI / ML model 708, which may be referred to as “PRS-based measurement s) ” Note the base station 706 may include a single base station, one or multiple TRPs of a base station, multiple base stations, or multiple TRPs from multiple base stations, etc. Then, the UE 702 may transmit the PRS-based measurements) 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).

[0107] FIG. 8B is a diagram 800B illustrating an example of UE-assisted / LMF-based positioning with 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) to the location server 704, such as an LMF. In response, the location server 704 may use the at least one AI / ML model 708 to determine the position of the UE 702 based on the PRS-based measurement(s) from the UE 702.

[0108] FIG. 9A is a diagram 900A illustrating an example of network (e.g., NG-RAN) node assisted positioning with 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 to129025-2466WO01Qualcomm Ref. No. 2406551WO 33 assist measurement s) of uplink (UL) reference signals, such as sounding reference signals (SRSs). Note the base station 706 may include a single base station, one or multiple TRPs of a base station, multiple base stations, or multiple TRPs from multiple base stations, etc. 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 (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 transmit the SRS-based measurement(s) to the 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) from the base station 706 (with or without suing an AI / ML model).

[0109] 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, 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) from the base station 706, the location server 704 may use the at least one AI / ML model 708 to determine the position of the UE 702. For purposes of the present disclosure, positioning described in connection with FIGs. 7, 8A, and 8B may be referred to as AI / ML positioning based on DL reference signals, and positioning described in connection with FIGs. 9A and 9B may be referred to as AI / ML positioning based on UL reference signals.

[0110] Table 2 below provides an example list of positioning methods that may be supported by a UE and / or a network entity.129025-2466WO01Qualcomm Ref. No. 2406551WO 34Table 2 - Example of supported UE positioning methods[OHl] In some implementations, for direct AI / ML positioning as described in connection with FIGs. 8B and 9B, type(s) of measurement(s) that may be used as (suitable / potential) input for AI / ML model inference considering performance 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. 8A and 9A, 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 information / high resolution of RSTD, etc. In129025-2466WO01Qualcomm Ref. No. 2406551WO 35 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.

[0112] For network-based positioning discussed in connection with FIG. 4, some positioning methods / mechanisms may specify a UE / target to perform positioning measurements with at least one reference resource, such as a reference positioning reference signal (PRS), a reference transmission reception point (TRP), etc. For example, a reference PRS may refer to a set of positioning signals transmitted from known and / or predefined location(s) (e.g., from antenna reference points (s) / TRP(s) / base station(s)) that are used as a benchmark for some positioning methods / mechanisms, such as for time difference of arrival (TDOA) and angle of arrival (AoA) positioning techniques. Similarly, a reference TRP may refer to a TRP (typically with location and timing characteristics well defined) whose signals are transmitted and used as reference points for positioning.

[0113] FIG. 10 is a diagram 1000 illustrating an example assistance data that includes reference PRS information in accordance with various aspects of the present disclosure. A location server (e.g., an LMF) may provide assistance data (AD) to a UE to assist the UE with the positioning. Thus, in the context of positioning, assistance data may refer to information provided by the network that is capable of assisting a UE in accurately determining its position and / or to reduce the time it takes for the UE to calculate its position, improve the accuracy, and enhance the performance of positioning algorithms, especially in challenging environments such as urban areas or indoors.

[0114] For example, as shown at 1002, a location server may use an information element (IE) DL-PRS-AssistanceData to provide DL-PRS assistance data to a UE. As shown at 1004, the DL-PRS assistance data may include a DL-PRS-Referencelnfo field that specifies the IDs of the assistance data reference TRP. In other words, this DL-PRS- Referencelnfo field may define the “assistance data reference” TRP whose DL-PRS configuration is included in a DL-PRS assistance data list (e.g., in the IE nr-DL-PRS- AssistanceDataLisf). The DL-PRS SFN0 offset nr-DL-PRS-SFNO-Offset's)' and DL- PRS expected RSTD nr-DL-PRS-expectedRSTD's) in the nr-DL-PRS- AssistanceDataList may be provided relative to the “assistance data reference” TRP.129025-2466WO01Qualcomm Ref. No. 2406551WO 36Note that in some examples, the “RSTD reference” TRP may or may not be the same as the “assistance data reference” TRP provided by nr-DL-PRS-Referencelnfo in IE NR-DL-PRS-AssistanceData.

[0115] FIG. 11 is a diagram 1100 illustrating an example IE PRS ID information that includes reference PRS information in accordance with various aspects of the present disclosure. As shown at 1102, a location server may use an IE DL-PRS-ID-Info to provide the IDs of the reference TRP’s DL-PRS resources to a UE. As shown at 1104, a DL-PRS-ResourcelD-List field may be used for providing a list of DL-PRS resource IDs under the same DL-PRS resource set.

[0116] AI / ML positioning (e.g., as discussed in conenction with FIGs. 5A and 5B) have shown an excellent positioning accuracy, such as in stringent NLOS conditions and challenging environments. However, an AI / ML positioning model / functionality (e.g., referring to an AI / ML model / functioality used for positioning) may be sensitive to changes in the wireless environment (e.g., changes in clutter settings) and / or changes in network (NW) conditions (e.g., changes in referecne signal (RS) configurations, network synchronziation errors, timing errors at the network side, changes in tranmission (TX) power, etc.). Thus, in some scenarios, it may be useful to have the UE or network entityies to perform positioning measurement(s) without AI / ML (which may be referred to as legacy meaurement(s) for purposes of differentiation) along with AI / ML positioning methods (along with AI / ML-based positioning measurements). Such configuration may be useful for the fallback and better positioning results, and in some cases, the UE / network may be able to use the best of two measurements given an opportunity.

[0117] As discussed above, some positioning methods / mechanisms such as DL-TDOA positioning and multi-RTT positioning may specify the UE to have information related to reference DL-PRS (e.g., the nr-DL-PRS-Referencelnfo). Life cycle managements (LCM) for AI / ML model(s) specific to theses positioning methods may also specify to have reference TRP for the AI / ML model measurements / data collection, inference, and / or testing. However, UE side models (e.g., as discussed in connection with FIGs. 7 and 8A) and / or network side models (e.g., as discussed in connection with FIGs. 8B and 9B) may have different assumptions / knowledges about reference resource (or TRP). AI / ML model(s) at one side may also have different reference resources depending on how they have been developed or configured. In129025-2466WO01Qualcomm Ref. No. 2406551WO 37 some implementations, AI / ML-enhanced measurements may have different reference resource (or TRP) than non-AI / ML ones. For example, an LMF may have different reference TRPs for AI / ML and non-AI / ML measurement reporting and related assistance data.

[0118] Aspects presented herein may improve the overall performance and accuracy of AI / ML positioing by enabling a UE to communicate with a network regarding reference resources (e.g., reference PRS(s) / TRP(s)) the UE uses for AI / ML positioning (and optionally for non-AI / ML positioning), such that the network is able to know which reference resources are used for which AI / ML models. Then, the network may ensure specified AI / ML model(s) are used for corresponding reference references or vice versa, thereby promotning a consistency between different AI / ML operations (e.g., between data collection / measurement, inference, training, etc.).

[0119] For example, in one aspect of the present disclosure, a DL-PRS ID information field may be used for providing an indication of a reference for an AI / ML model. In another aspect, a dedicated / new reference structure may provide an indication of the reference for an AI / ML model. In another aspect, an AI / ML model may be trained / monitored with multiple reference TRPs / resources, where priority among reference TRPs / resources may be provided by an LMF. An LMF / BS may have the capability to switch TRPs / resources at any time during positioning, and a UE may have the capability to recommend reference TRPs / resources to the LMF. In some exampels, the LMF / UE may indicate reference TRP and TRP resources sets for one or more of AI / ML (e.g., for AI / ML data collection, training, monitoring, and / or inference, etc.). In another aspect, a UE may provide UE capabilities that indicate the number of TRP and TRP resources sets supported for AI / ML data collection, training, monitoring, inference etc. In another aspect, a device (UE or BS / TRP) may be configured with at least two referenece TRPs, one for AI / ML measurements and the other for non-AIML measurements and assistance.

[0120] FIG. 12 is a communication flow 1200 illustrating an example of configuring reference resource(s) for AI / ML in accordance with various aspects of the present disclosure. The numberings associated with the communication flow 1200 do not specify a particular temporal order and are merely used as references for the communication flow 1200. Aspects presented herein may enable a network entity to configured (dedicated) reference resources for AI / ML performed at a UE (e.g., for129025-2466WO01Qualcomm Ref. No. 2406551WO 38AI / ML positioning) and / or enable the UE to inform the network entity which reference resources the UE uses for AI / ML positioning, thereby promoting a common understanding between the UE and the network entity regarding reference resources used in association with AI / ML.

[0121] At 1210, a UE 1202 may communicate, with a network entity 1204 (e.g., a location server, a location management function (LMF), a sensing management function, an AI / ML management function, network data analytics functions (NWDAF) (NWDAF), an operation, administration, maintenance (0AM) entity, an over-the-top (OTT) server, etc.), an indication of a set of reference TRPs, a set of reference resources, and / or a set of resource sets (collectively as “reference TRP(s) / resource(s)” hereafter) for AI / ML, such as AI / ML used in association with positioning. Depending on implementations, the AI / ML may include a physical AI / ML model, a logical AI / ML model, an AI / ML functionality, or a combination thereof. For example, a set of reference TRPs / resources may be configured and dedicated for at least one AI / ML model / functionality. In other words, a reference TRP / resource may be configured to be AI / ML model specific.

[0122] In one aspect of the present disclosure, as shown at 1212, the network entity 1204 may provide, to the UE 1202, a set of reference TRPs / resources for each AI / ML model / functionality, such as via a part of an assistance data configuration / report. For example, the network entity 1204 may be configured to use an existing DL-PRS ID information message structure (e.g., the DL-PRS-ID-Info lE / structure as discussed in connection with FIG. 11) to provide the reference TRP(s) / resource(s) for the AI / ML model(s) / functionalities. Such configuration may be suitable when one AI / ML model / functionality is configured / assigned for one positioning method (e.g., one AI / ML model / functionality for TDOA positioning, one AI / ML model / functionality for RTT positioning, one AI / ML model / functionality for AoA positioning, etc.), and / or when one AI / ML model / functionality is configured to be trained, monitored, and / or inferenced with one reference TRP / resource.

[0123] In another aspect of the present disclosure, as shown at 1214, the UE 1202 may provide, to the network entity 1204, a set of reference TRPs / resources it uses for each AI / ML model / functionality, such as via a part of a capability report, a measurement report, or an assistance data request.129025-2466WO01Qualcomm Ref. No. 2406551WO 39

[0124] FIG. 13 is a diagram 1300 illustrating an example measurement report structure that may be used by a UE for providing reference TRP(s) / resource(s) it uses for AI / ML model(s) / functionalities in accordance with various aspects of the present disclosure. As shown at 1302, in some implementations, the UE 1202 may be configured to use a dedicated field (e.g., a dl-PRS-Referencelnfo AIML DL-PRS-ID-Info field) in a measurement information / report message (e.g., via IE TDOA- SignalMeasurementlnformation) to provide reference TRP(s) / resource(s) it uses for AI / ML model(s) / functionalities to the network entity 1204. Such configuration may be suitable when multiple AI / ML models / functionalities are configured / assigned for one positioning method (e.g., two AI / ML models / functionalities for TDOA positioning, three AI / ML models / functionalities for RTT positioning, one AI / ML model / functionality for AoA positioning, etc.), and / or when an AI / ML model / functionality is configured to be trained, monitored, and / or inferenced with a reference TRP / resource.

[0125] Depending on implementations, one reference TRP / resource or multiple reference TRPs / resources may be configured for one AI / ML model / functionality and / or one positioning method (e.g., one or multiple reference TRPs / resources for one AI / ML model / functionality for one positioning method, one or multiple reference TRPs / resources for multiple AI / ML models / functionalities for one positioning method, one or multiple reference TRPs / resources for multiple AI / ML models / functionalities for multiple positioning methods, etc.). As such, an AI / ML model / functionality may be trained and / or monitored with multiple reference TRPs / resources. Similarly, one TRP resource set or multiple TRP resource sets may be configured for one AI / ML model / functionality and / or one positioning method, such that an AI / ML model / functionality may be trained and / or monitored with multiple TRP resource sets.

[0126] Referring back to FIG. 12, in some implementations, when multiple reference TRPs / resources are configured or provided for an AI / ML model / functionality, the multiple reference TRPs / resources may be associated with a set of priorities. For example, at 1216, the network entity 1204 may provide, to the UE 1202, a set of priorities associated with the multiple reference TRPs / resources. In response, the UE 1202 may be configured to select and use the multiple reference TRPs / resources based on their associated priorities. For example, the UE 1202 may prioritize selecting / using129025-2466WO01Qualcomm Ref. No. 2406551WO 40 a reference TRP / resource with a higher priority in the multiple reference TRPs / resources compared to a reference TRP / resource with a lower priority in the multiple reference TRPs / resources. In another example, at 1216, the UE 1202 may provide, to the network entity 1204, a set of priorities associated with the multiple reference TRPs / resources. In response, the network entity 1204 may be configured to select and use the multiple reference TRPs / resources (e.g., for the UE 1202) based on their associated priorities. For example, the network entity 1204 may prioritize selecting / using a reference TRP / resource with a higher priority in the multiple reference TRPs / resources compared to a reference TRP / resource with a lower priority in the multiple reference TRPs / resources.

[0127] In some implementations, when multiple reference TRPs / resources are configured or provided for an AI / ML model / functionality, the UE 1202, the network entity 1204, and / or a base station (e.g., a gNB) or a TRP may have the capability to activate, deactivate, and / or switch reference TRP(s) / resource(s) at a given time, such as during one or more positioning sessions. For example, at 1218, the network entity 1204 or a base station / TRP may transmit, to the UE 1202, an indication to activate, deactivate, and / or switch one or more reference TRPs / resources, where the indication may be transmitted via a medium access control (MAC) control element (CE) (MAC-CE) or downlink control information (DCI), etc. In response, the UE 1202 may activate, deactivate, and / or switch one or more reference TRPs / resources used for the AI / ML based on the indication. For example, if the network entity 1204 indicates the UE 1202 to activate a specified reference TRP / resource, the UE 1202 may use the specified reference TRP / resource in subsequent AI / ML positioning (e.g., in one or more subsequent AI / ML positioning sessions). However, if the network entity 1204 indicates the UE 1202 to deactivate a specified reference TRP / resource, the UE 1202 may be refrained from using the specified reference TRP / resource in subsequent AI / ML positioning. Similarly, if the network entity 1204 indicates the UE 1202 to switch from a first reference TRP / resource to a second reference TRP / resource, the UE 1202 may use the second reference TRP / resource and not the first reference TRP / resource in subsequent AI / ML positioning. In another example, at 1218, the UE 1202 may transmit, to the network entity 1204, an indication to activate, deactivate, and / or switch one or more reference TRPs / resources. In response, the network entity 1204 may activate, deactivate, and / or switch one or more reference TRPs / resources129025-2466WO01Qualcomm Ref. No. 2406551WO 41 used for the AI / ML based on the indication. For example, if the UE 1202 indicates the network entity 1204 to activate a specified reference TRP / resource, the network entity 1204 may use the specified reference TRP / resource in subsequent AI / ML positioning (e.g., in one or more subsequent AI / ML positioning sessions). However, if the UE 1202 indicates the network entity 1204 to deactivate a specified reference TRP / resource, the network entity 1204 may be refrained from using the specified reference TRP / resource in subsequent AI / ML positioning. Similarly, if the UE 1202 indicates the network entity 1204 to switch from a first reference TRP / resource to a second reference TRP / resource, the network entity 1204 may use the second reference TRP / resource and not the first reference TRP / resource in subsequent AI / ML positioning. For purposes of the present disclosure, AI / ML positioning may refer to performing a positioning operation using at least one AI / ML model / functionality, which may include determining the position of a UE using AI / ML (e.g., as described in connection with FIGs. 7 and 8B, etc.) or performing positioning measurements using AI / ML (e.g., as described in connection with FIGs. 7 and 8A, etc.).

[0128] In some examples, as shown at 1220, when multiple reference TRPs / resources are configured or provided for an AI / ML model / functionality, the UE 1202 and / or the network entity 1204 may include the capability to provide a set of suitable / recommend reference TRPs / resources for the AI / ML positioning. In other words, the UE 1202 and / or the network entity 1204 may recommend reference TRP(s) / resource(s) to the network entity 1204. In response, the network entity 1204 and / or the UE 1202 may configure (or activate / switch) reference TRP(s) / resource(s) based on the set of suitable / recommend reference TRPs / resources.

[0129] In another aspect of the present disclosure, at 1222, the UE 1202 and the network entity 1204 may communicate with each other regarding AI / ML life cycle management (LCM) function(s) and / or phase(s) for reference TRP(s) / resource(s). For example, the UE 1202 may indicate to the network entity 1204 and / or the network entity 1204 may indicate to the UE 1202 at least one of (1) a list of reference TRPs / resources for AI / ML data collection, (2) a list of reference TRPs / resources for AI / ML training, (3) a list of reference TRPs / resources for AI / ML monitoring, or (4) a list of reference TRPs / resources for AI / ML inference, etc. For example, the network entity 1204 may request the UE 1202 to use one set of reference TRPs / resources for129025-2466WO01Qualcomm Ref. No. 2406551WO 42AI / ML data collection and another set of reference TRPs / resources for AI / ML inference use cases.

[0130] In another aspect of the present disclosure, the UE 1202, the network entity 1204, and / or a base station / TRP (not shown in the diagram) may have the capability to train AI / ML model(s) / functionalities with specified reference TRP(s) / resource(s). For example, at 1224, the network entity 1204 may transmit / indicate, to the UE 1202, a list of reference TRPs / resources for performing at least one AI / ML operation (e.g., AI / ML data collection, training, monitoring, inferencing, etc.) for at least one AI / ML model / functionality. In response, at 1226, the UE 1202 may perform the at least one AI / ML operation for the at least one AI / ML model / functionality using the list of reference TRPs / resources. In another example, at 1224, the UE 1202 may transmit / indicate, to network entity 1204, a list of recommended reference TRPs / resources for performing at least one AI / ML operation for at least one AI / ML model / functionality. In response, at 1228, the network entity 1204 may perform the at least one AI / ML operation for the at least one AI / ML model / functionality using the list of recommended reference TRPs / resources. In another example, at 1224, the UE 1202 may transmit / indicate, to network entity 1204, a list of reference TRPs / resources it uses for performing at least one AI / ML operation for at least one AI / ML model / functionality if the network entity 1204 is not aware of the reference TRPs / resources used by the UE 1202 for performing the at least one AI / ML operation for the at least one AI / ML model / functionality. Similarly, at 1224, the network entity 1204 may transmit / indicate, to the UE 1202, a list of reference TRPs / resources it uses for performing at least one AI / ML operation for at least one AI / ML model / functionality if the UE 1202 is not aware of the reference TRPs / resources used by the network entity 1204 for performing the at least one AI / ML operation for the at least one AI / ML model / functionality. As such, the entity for performing the AI / ML operation(s) may include the UE 1202, the network entity 1204 (e.g., an LMF, an NWDAF, an 0AM entity, an OTT server, etc.), and / or a base station / TRP, etc.

[0131] Depending on implementations, the performance of at least one AI / ML operation for the AI / ML model(s) / functionalities may be based on: (1) performing the at least one AI / ML operation for one or more AI / ML model(s) / functionalities with a mixture of reference TRPs / resources (e.g., measurements associated with the reference TRP(s) / resource(s) are used as input for the AI / ML model(s) / functionalities), (2)129025-2466WO01Qualcomm Ref. No. 2406551WO 43 performing the at least one AI / ML operation for each AI / ML models / functionality in multiple AI / ML models / functionalities with a specific reference TRPs / resource or a specific set of reference TRPs / resources, and / or (3) performing the at least one AI / ML operation for one or more AI / ML model(s) / functionalities with input that includes index / ID(s) of the reference TRP(s) / resource(s) (may be referred to as model input indexing), etc.

[0132] In another aspect of the present disclosure, as shown at 1230, if the UE 1202 has capability to support multiple reference TRPs / resources for AI / ML positioning methods, the UE 1202 may be configured to indicate such capability to the network entity 1204. For example, at 1230, the UE 1202 may indicate, to the network entity 1204, one or more of (1) a maximum number of reference TRP(s) / resource(s) supported for AI / ML data collection (e.g., one to a maximum number N), (2) a maximum number of reference TRP(s) / resource(s) supported for AI / ML training (e.g., one to a maximum number N), (3) a maximum number of reference TRP(s) / resource(s) supported for AI / ML monitoring (e.g., one to a maximum number N), or (4) a maximum number of reference TRP(s) / resource(s) supported for AI / ML inference (e.g., one to a maximum number N), etc. Depending on implementations, this signaling may be a separated signaling as shown at 1230, or it may be indicated with other signaling, such as signaling described in connection with 1214 and 1220. Based on the capability of the UE 1202, the network entity 1204 may determine which and / or how many reference TRP(s) / resource(s) to be configured for the UE 1202 for AI / ML positioning (e.g., via signaling at 1212, 1218, and / or 1224, etc.). It may also be beneficial for the network entity 1204 to be aware of the UE 1204’ s capability for supporting multiple reference TRPs / resources for AI / ML positioning methods as this capability may have impact on positioning session latency and measurement period.

[0133] At 1232, based on the communication related to reference TRP(s) / resource(s) for AI / ML (e.g., discussed in connection with 1210 to 1224), the UE 1202 may perform positioning and / or positioning measurements with AI / ML using the communicated reference TRP(s) / resource(s). In some examples, as shown at 1234, the UE 1202 may also transmit, to the network entity 1204, the position of the UE 1202 (e.g., determined from the positioning at 1232) and / or the positioning measurements.

[0134] As discussed above, the UE 1202 and the network entity 1204 may communicate with each other regarding (recommended / suitable) reference TRP(s) / resource(s) to be used129025-2466WO01Qualcomm Ref. No. 2406551WO 44 for AI / ML. Thus, in some implementations, a reference TRP / resource may be configured to be AI / ML model / functionality specific (which may be applicable to both the UE-side AI / ML model / functionality and the network-side AI / ML model / functionality). For example, the network entity 1204 may provide, to the UE 1202, a list of reference TRPs / resources such as discussed in connection with 1212, the UE 1202 may: (1) switch between the list of reference TRPs / resources based on triggered conditions or explicit signaling (e.g., the UE 1202 may switch from a first reference TRP / resource to a second reference TRP / resource when the signal-to-noise ratio (SNR) of the first reference TRP / resource exceeds an SNR threshold); (2) use / select the reference TRP(s) / resource(s) for AI / ML based on their associated priorities (e.g., as discussed in connection with 1216); (3) perform or receive scheduling and selection of the of the reference TRP(s) / resource(s); and / or (4) obtain provision(s) for the UE 1202 to report which reference TRP(s) / resource(s) are used by the UE 1202 for a giving positioning session, etc.

[0135] In another example, the UE 1202 may be configured to report reference TRP(s) / resource(s) it uses with a time stamp. For example, if the UE 1202 is configured to report reference TRP(s) / resource(s) it uses for AI / ML to the network entity 1204 at 1214, the report may include a list of reference TRP(s) / resource(s) used by the UE 1202 at different times. Similarly, as discussed above, reference TRP(s) / resource(s) may be configured to be dependent on data collection for training, monitoring, and inference. In addition, the signaling (for reference TRP(s) / resource(s)) discussed in connection with FIG. 12 may occur during AI / ML training data collection, monitoring data collection, and / or inference.

[0136] In another example, a device (e.g., the UE 1202 or a base station / TRP) may be configured with at least two reference TRPs / resources, where at least one reference TRP / resource is dedicated for AI / ML positioning / measurement / assistance, and at least one reference TRP / resource is dedicated for non-AI / ML positioning / measurement / assistance. As such, when the device is configured to perform AI / ML positioning, the device may use the at least one reference TRP / resource dedicated for the AI / ML positioning / measurement / assistance. On the other hand, when the device is configured to perform non-AI / ML positioning, the device may use the at least one reference TRP / resource dedicated for the non-AI / ML positioning / measurement / assistance.129025-2466WO01Qualcomm Ref. No. 2406551WO 45

[0137] FIG. 14 is a flowchart 1400 of wireless communication. The method may be performed by a user equipment (UE) (e.g., the UE 104, 404, 602, 702, 1202; the apparatus 1604). The method may enable the UE to communicate with a network entity regarding reference resources (e.g., reference PRS(s) / TRP(s)) the UE uses for AI / ML positioning (and optionally for non-AI / ML positioning), such that the network entity is able to know which reference resources are used for which AI / ML models, thereby improving the overall performance and accuracy of AI / ML positioing.

[0138] At 1402, the UE may communicate, with a network entity, an indication of a set of reference TRPs or resources for AI / ML, where the AI / ML is used in association with positioning, such as described in connection with FIG. 12. For example, at 1210, a UE 1202 may communicate, with a network entity 1204, an indication of a set of reference TRPs, a set of reference resources, and / or a set of resource sets (collectively as “reference TRP(s) / resource(s)” hereafter) for AI / ML, such as AI / ML used in association with positioning. The communication of the indication may be performed by, e.g., the reference resource processing component 198, the transceiver(s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 of the apparatus 1604 in FIG. 16.

[0139] In one example, the AI / ML includes one AI / ML model configured for one positioning method, and the one AI / ML model is trained, monitored, or inferenced with one reference TRP. In some implementations, to communicate, with the network entity, the indication of the set of reference TRPs or resources for the AI / ML, the UE may be configured to communicate, with the network entity, the indication of the set of reference TRPs or resources for the one AI / ML model via a PRS ID information message.

[0140] In another example, the AI / ML includes multiple AI / ML models configured for one positioning method, and the multiple AI / ML models are trained, monitored, or inferenced with one or more reference TRPs. In some implementations, to communicate, with the network entity, the indication of the set of reference TRPs or resources for the AI / ML, the UE may be configured to communicate, with the network entity, the indication of the set of reference TRPs or resources for the multiple AI / ML models via a dedicated reference structure message.129025-2466WO01Qualcomm Ref. No. 2406551WO 46

[0141] In another example, the set of reference TRPs or resources are associated with a priority, and the UE may receive, from the network entity or an LMF, a second indication of the priority associated with the set of reference TRPs or resources.

[0142] In another example, communication of the indication is based on a set of capabilities of the UE, where the set of capabilities includes at least one of: a maximum number of TRPs or TRP resources sets supported for AI / ML data collection, a maximum number of TRPs or TRP resources sets supported for AI / ML training, a maximum number of TRPs or TRP resources sets supported for AI / ML monitoring, or a maximum number of TRPs or TRP resources sets supported for AI / ML inference.

[0143] In another example, one or more reference TRPs or resources in the set of reference TRPs or resources are AI / ML model specific.

[0144] In another example, to communicate the indication of the set of reference TRPs or resources for the AI / ML, the UE may be configured to communicate the indication of the set of reference TRPs or resources for the AI / ML during a training data collection, a monitoring data collection, or an inference.

[0145] In another example, the UE may receive, from the network entity, a configuration for a set of additional reference TRPs or resources for non-AI / ML positioning or non- AI / ML measurements.

[0146] In another example, the AI / ML corresponds to at least one physical AI / ML model, at least one logical AI / ML model, or at least one AI / ML functionality.

[0147] At 1412, the UE may perform at least one of the positioning or a set of measurements for the positioning with the AI / ML using at least one reference TRP or resource in the set of reference TRPs or resources, such as described in connection with FIG. 12. For example, at 1232, based on the communication related to reference TRP(s) / resource(s) for AI / ML (e.g., discussed in connection with 1210 to 1224), the UE 1202 may perform positioning and / or positioning measurements with AI / ML using the communicated reference TRP(s) / resource(s). The positioning and / or the set of measurements for the positioning may be performed by, e.g., the reference resource processing component 198, the transceiver s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 of the apparatus 1604 in FIG. 16.

[0148] In one example, the UE may transmit, to the network entity, at least one of a position of the UE from the positioning or a measurement for positioning of the UE from the set of measurements, such as described in connection with FIG. 12. For example, at129025-2466WO01Qualcomm Ref. No. 2406551WO 471234, the UE 1202 may also transmit, to the network entity 1204, the position of the UE 1202 (e.g., determined from the positioning at 1232) and / or the positioning measurements. The transmission of the position and / or the measurement may be performed by, e.g., the reference resource processing component 198, the transceiver(s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 of the apparatus 1604 in FIG. 16.

[0149] In another example, the UE may transmit, to the network entity, a list of recommended reference TRPs or resources for at least one AI / ML operation, such as described in connection with FIG. 12. For example, at 1224, the UE 1202 may transmit / indicate, to network entity 1204, a list of recommended reference TRPs / resources for performing at least one AI / ML operation for at least one AI / ML model / functionality. In response, at 1228, the network entity 1204 may perform the at least one AI / ML operation for the at least one AI / ML model / functionality using the list of recommended reference TRPs / resources. The transmission of the list of recommended reference TRPs or resources may be performed by, e.g., the reference resource processing component 198, the transceiver(s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 of the apparatus 1604 in FIG. 16.

[0150] In another example, the UE may receive, from the network entity, a list of reference TRPs or resources for at least one AI / ML operation (e.g., AI / ML data collection, training, monitoring, inferencing, etc.), and perform the at least one AI / ML operation for the AI / ML based on the list of reference TRPs or resources, such as described in connection with FIG. 12. For example, at 1224, the UE 1202 may receive, from the network entity 1204, a list of reference TRPs / resources for performing at least one AI / ML operation (e.g., AI / ML data collection, training, monitoring, inferencing, etc.) for at least one AI / ML model / functionality. In response, at 1226, the UE 1202 may perform the at least one AI / ML operation for the at least one AI / ML model / functionality using the list of reference TRPs / resources. The reception of the list of reference TRPs and / or resources and / or the performance of the at least one AI / ML operation may be performed by, e.g., the reference resource processing component 198, the transceiver(s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 of the apparatus 1604 in FIG. 16. In some implementations, to perform the at least one AI / ML operation for the AI / ML based129025-2466WO01Qualcomm Ref. No. 2406551WO 48 on the list of reference TRPs or resources, the UE may be configured to at least one of: perform the at least one AI / ML operation for one AI / ML model with a plurality of reference TRPs or resources in the list of reference TRPs or resources, perform the at least one AI / ML operation for multiple AI / ML models with each AI / ML model in the multiple AI / ML model using one reference TRP or resource in the list of reference TRPs or resources, or perform the at least one AI / ML operation for the AI / ML based on the list of reference TRPs or resources and a set of index or IDs associated with the list of reference TRPs or resources.

[0151] In another example, the UE may communicate, with the network entity for an AI / ML LCM function or phase of a reference TRP in the set of TRPs, at least one of a first list of reference TRPs or TRP resources sets for AI / ML data collection, a second list of reference TRPs or TRP resources sets for AI / ML training, a third list of reference TRPs or TRP resources sets for AI / ML monitoring, or a fourth list of reference TRPs or TRP resources sets for AI / ML inference, such as described in connection with FIG. 12. For example, at 1222, the UE 1202 and the network entity 1204 may communicate with each other regarding AI / ML LCM function(s) and / or phase(s) for reference TRP(s) / resource(s). The communication may be performed by, e.g., the reference resource processing component 198, the transceiver(s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 of the apparatus 1604 in FIG. 16.

[0152] In another example, the UE may select the at least one reference TRP or resource from the set of reference TRPs or resources for performing at least one of the positioning or the set of measurements for the positioning with the AI / ML based on at least one of a priority associated with the at least one reference TRP or resource, a scheduling or selection associated with the at least one reference TRP or resource, or a provision to use the at least one reference TRP or resource for reporting, such as described in connection with FIG. 12. For example, at 1216, the UE 1202 may receive, from the network entity 1204, a set of priorities associated with the multiple reference TRPs / resources. In response, the UE 1202 may be configured to select and use the multiple reference TRPs / resources based on their associated priorities. For example, the UE 1202 may prioritize selecting / using a reference TRP / resource with a higher priority in the multiple reference TRPs / resources compared to a reference TRP / resource with a lower priority in the multiple reference TRPs / resources. The129025-2466WO01Qualcomm Ref. No. 2406551WO 49 selection of at least one reference TRP or resource may be performed by, e.g., the reference resource processing component 198, the transceiver s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 of the apparatus 1604 in FIG. 16.

[0153] In another example, the UE may receive, from the network entity, a request to activate at least one additional reference TRP or resource during a positioning session, and perform, based on reception of the request to activate the at least one additional reference TRP or resource, at least one of the positioning or the set of measurements for the positioning with the AI / ML using the at least one additional reference TRP or resource.

[0154] In another example, the UE may receive, from the network entity, a request to deactivate one or more reference TRPs or resources in the set of reference TRPs or resources during a positioning session, and perform, based on reception of the request, at least one of the positioning or the set of measurements for the positioning with the AI / ML without using the one or more reference TRPs or resources.

[0155] In another example, to perform at least one of the positioning or the set of measurements for the positioning with the AI / ML using the at least one reference TRP or resource in the set of reference TRPs or resources, the UE may be configured to switch from at least a first reference TRP or resource in the set of reference TRPs or resources to at least a second reference TRP or resource in the set of reference TRPs or resources based on at least one trigger condition or explicit signaling, and perform at least one of the positioning or the set of measurements for the positioning with the AI / ML using the second reference TRP or resource in the set of reference TRPs or resources.

[0156] In another example, the UE may transmit, to the network entity, a second indication of the at least one reference TRP or resource used for performing at least one of the positioning or the set of measurements for the positioning, where the second indication includes a timestamp of when the at least one reference TRP or resource is used.

[0157] In another example, the UE may select the at least one reference TRP or resource from the set of reference TRPs or resources for performing at least one of the positioning or the set of measurements for the positioning with the AI / ML based on whether the AI / ML is associated with data collection for AI / ML training, monitoring, or inference.129025-2466WO01Qualcomm Ref. No. 2406551WO 50

[0158] FIG. 15 is a flowchart 1500 of wireless communication. The method may be performed by a user equipment (UE) (e.g., the UE 104, 404, 602, 702, 1202; the apparatus 1604). The method may enable the UE to communicate with a network entity regarding reference resources (e.g., reference PRS(s) / TRP(s)) the UE uses for AI / ML positioning (and optionally for non-AI / ML positioning), such that the network entity is able to know which reference resources are used for which AI / ML models, thereby improving the overall performance and accuracy of AI / ML positioing.

[0159] At 1502, the UE may communicate, with a network entity, an indication of a set of reference TRPs or resources for AI / ML, where the AI / ML is used in association with positioning, such as described in connection with FIG. 12. For example, at 1210, a UE 1202 may communicate, with a network entity 1204, an indication of a set of reference TRPs, a set of reference resources, and / or a set of resource sets (collectively as “reference TRP(s) / resource(s)” hereafter) for AI / ML, such as AI / ML used in association with positioning. The communication of the indication may be performed by, e.g., the reference resource processing component 198, the transceiver(s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 of the apparatus 1604 in FIG. 16.

[0160] In one example, the AI / ML includes one AI / ML model configured for one positioning method, and the one AI / ML model is trained, monitored, or inferenced with one reference TRP. In some implementations, to communicate, with the network entity, the indication of the set of reference TRPs or resources for the AI / ML, the UE may be configured to communicate, with the network entity, the indication of the set of reference TRPs or resources for the one AI / ML model via a PRS ID information message.

[0161] In another example, the AI / ML includes multiple AI / ML models configured for one positioning method, and the multiple AI / ML models are trained, monitored, or inferenced with one or more reference TRPs. In some implementations, to communicate, with the network entity, the indication of the set of reference TRPs or resources for the AI / ML, the UE may be configured to communicate, with the network entity, the indication of the set of reference TRPs or resources for the multiple AI / ML models via a dedicated reference structure message.129025-2466WO01Qualcomm Ref. No. 2406551WO 51

[0162] In another example, the set of reference TRPs or resources are associated with a priority, and the UE may receive, from the network entity or an LMF, a second indication of the priority associated with the set of reference TRPs or resources.

[0163] In another example, communication of the indication is based on a set of capabilities of the UE, where the set of capabilities includes at least one of: a maximum number of TRPs or TRP resources sets supported for AI / ML data collection, a maximum number of TRPs or TRP resources sets supported for AI / ML training, a maximum number of TRPs or TRP resources sets supported for AI / ML monitoring, or a maximum number of TRPs or TRP resources sets supported for AI / ML inference.

[0164] In another example, one or more reference TRPs or resources in the set of reference TRPs or resources are AI / ML model specific.

[0165] In another example, to communicate the indication of the set of reference TRPs or resources for the AI / ML, the UE may be configured to communicate the indication of the set of reference TRPs or resources for the AI / ML during a training data collection, a monitoring data collection, or an inference.

[0166] In another example, the UE may receive, from the network entity, a configuration for a set of additional reference TRPs or resources for non-AI / ML positioning or non- AI / ML measurements.

[0167] In another example, the AI / ML corresponds to at least one physical AI / ML model, at least one logical AI / ML model, or at least one AI / ML functionality.

[0168] At 1512, the UE may perform at least one of the positioning or a set of measurements for the positioning with the AI / ML using at least one reference TRP or resource in the set of reference TRPs or resources, such as described in connection with FIG. 12. For example, at 1232, based on the communication related to reference TRP(s) / resource(s) for AI / ML (e.g., discussed in connection with 1210 to 1224), the UE 1202 may perform positioning and / or positioning measurements with AI / ML using the communicated reference TRP(s) / resource(s). The positioning and / or the set of measurements for the positioning may be performed by, e.g., the reference resource processing component 198, the transceiver s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 of the apparatus 1604 in FIG. 16.

[0169] In one example, as shown at 1514, the UE may transmit, to the network entity, at least one of a position of the UE from the positioning or a measurement for positioning of the UE from the set of measurements, such as described in connection with FIG. 12.129025-2466WO01Qualcomm Ref. No. 2406551WO 52For example, at 1234, the UE 1202 may also transmit, to the network entity 1204, the position of the UE 1202 (e.g., determined from the positioning at 1232) and / or the positioning measurements. The transmission of the position and / or the measurement may be performed by, e.g., the reference resource processing component 198, the transceiver(s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 of the apparatus 1604 in FIG. 16.

[0170] In another example, as shown at 1504, the UE may transmit, to the network entity, a list of recommended reference TRPs or resources for at least one AI / ML operation, such as described in connection with FIG. 12. For example, at 1224, the UE 1202 may transmit / indicate, to network entity 1204, a list of recommended reference TRPs / resources for performing at least one AI / ML operation for at least one AI / ML model / functionality. In response, at 1228, the network entity 1204 may perform the at least one AI / ML operation for the at least one AI / ML model / functionality using the list of recommended reference TRPs / resources. The transmission of the list of recommended reference TRPs or resources may be performed by, e.g., the reference resource processing component 198, the transceiver(s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 of the apparatus 1604 in FIG. 16.

[0171] In another example, as shown at 1506, the UE may receive, from the network entity, a list of reference TRPs or resources for at least one AI / ML operation (e.g., AI / ML data collection, training, monitoring, inferencing, etc.), and perform the at least one AI / ML operation for the AI / ML based on the list of reference TRPs or resources, such as described in connection with FIG. 12. For example, at 1224, the UE 1202 may receive, from the network entity 1204, a list of reference TRPs / resources for performing at least one AI / ML operation (e.g., AI / ML data collection, training, monitoring, inferencing, etc.) for at least one AI / ML model / functionality. In response, at 1226, the UE 1202 may perform the at least one AI / ML operation for the at least one AI / ML model / functionality using the list of reference TRPs / resources. The reception of the list of reference TRPs and / or resources and / or the performance of the at least one AI / ML operation may be performed by, e.g., the reference resource processing component 198, the transceiver s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 of the apparatus 1604 in FIG. 16. In some implementations, to perform the at least one AI / ML operation for the AI / ML129025-2466WO01Qualcomm Ref. No. 2406551WO 53 based on the list of reference TRPs or resources, the UE may be configured to at least one of: perform the at least one AI / ML operation for one AI / ML model with a plurality of reference TRPs or resources in the list of reference TRPs or resources, perform the at least one AI / ML operation for multiple AI / ML models with each AI / ML model in the multiple AI / ML model using one reference TRP or resource in the list of reference TRPs or resources, or perform the at least one AI / ML operation for the AI / ML based on the list of reference TRPs or resources and a set of index or identifiers (IDs) associated with the list of reference TRPs or resources.

[0172] In another example, as shown at 1508, the UE may communicate, with the network entity for an AI / ML LCM function or phase of a reference TRP in the set of TRPs, at least one of a first list of reference TRPs or TRP resources sets for AI / ML data collection, a second list of reference TRPs or TRP resources sets for AI / ML training, a third list of reference TRPs or TRP resources sets for AI / ML monitoring, or a fourth list of reference TRPs or TRP resources sets for AI / ML inference, such as described in connection with FIG. 12. For example, at 1222, the UE 1202 and the network entity 1204 may communicate with each other regarding AI / ML LCM function(s) and / or phase(s) for reference TRP(s) / resource(s). The communication may be performed by, e.g., the reference resource processing component 198, the transceiver(s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 of the apparatus 1604 in FIG. 16.

[0173] In another example, as shown at 1510, the UE may select the at least one reference TRP or resource from the set of reference TRPs or resources for performing at least one of the positioning or the set of measurements for the positioning with the AI / ML based on at least one of a priority associated with the at least one reference TRP or resource, a scheduling or selection associated with the at least one reference TRP or resource, or a provision to use the at least one reference TRP or resource for reporting, such as described in connection with FIG. 12. For example, at 1216, the UE 1202 may receive, from the network entity 1204, a set of priorities associated with the multiple reference TRPs / resources. In response, the UE 1202 may be configured to select and use the multiple reference TRPs / resources based on their associated priorities. For example, the UE 1202 may prioritize selecting / using a reference TRP / resource with a higher priority in the multiple reference TRPs / resources compared to a reference TRP / resource with a lower priority in the multiple reference TRPs / resources. The129025-2466WO01Qualcomm Ref. No. 2406551WO 54 selection of at least one reference TRP or resource may be performed by, e.g., the reference resource processing component 198, the transceiver s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 of the apparatus 1604 in FIG. 16.

[0174] In another example, the UE may receive, from the network entity, a request to activate at least one additional reference TRP or resource during a positioning session, and perform, based on reception of the request to activate the at least one additional reference TRP or resource, at least one of the positioning or the set of measurements for the positioning with the AI / ML using the at least one additional reference TRP or resource.

[0175] In another example, the UE may receive, from the network entity, a request to deactivate one or more reference TRPs or resources in the set of reference TRPs or resources during a positioning session, and perform, based on reception of the request, at least one of the positioning or the set of measurements for the positioning with the AI / ML without using the one or more reference TRPs or resources.

[0176] In another example, to perform at least one of the positioning or the set of measurements for the positioning with the AI / ML using the at least one reference TRP or resource in the set of reference TRPs or resources, the UE may be configured to switch from at least a first reference TRP or resource in the set of reference TRPs or resources to at least a second reference TRP or resource in the set of reference TRPs or resources based on at least one trigger condition or explicit signaling, and perform at least one of the positioning or the set of measurements for the positioning with the AI / ML using the second reference TRP or resource in the set of reference TRPs or resources.

[0177] In another example, the UE may transmit, to the network entity, a second indication of the at least one reference TRP or resource used for performing at least one of the positioning or the set of measurements for the positioning, where the second indication includes a timestamp of when the at least one reference TRP or resource is used.

[0178] In another example, the UE may select the at least one reference TRP or resource from the set of reference TRPs or resources for performing at least one of the positioning or the set of measurements for the positioning with the AI / ML based on whether the AI / ML is associated with data collection for AI / ML training, monitoring, or inference.129025-2466WO01Qualcomm Ref. No. 2406551WO 55

[0179] FIG. 16 is a diagram 1600 illustrating an example of a hardware implementation for an apparatus 1604. The apparatus 1604 may be a UE, a component of a UE, or may implement UE functionality. In some aspects, the apparatus 1604 may include at least one cellular baseband processor 1624 (also referred to as a modem) coupled to one or more transceivers 1622 (e.g., cellular RF transceiver). The cellular baseband processor(s) 1624 may include at least one on-chip memory 1624'. In some aspects, the apparatus 1604 may further include one or more subscriber identity modules (SIM) cards 1620 and at least one application processor 1606 coupled to a secure digital (SD) card 1608 and a screen 1610. The application processor(s) 1606 may include on-chip memory 1606'. In some aspects, the apparatus 1604 may further include a Bluetooth module 1612, a WLAN module 1614, an ultrawide band (UWB) module 1638 (e.g., a UWB transceiver), an SPS module 1616 (e.g., GNSS module), one or more sensors 1618 (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 1626, a power supply 1630, and / or a camera 1632. The Bluetooth module 1612, the UWB module 1638, the WLAN module 1614, and the SPS module 1616 may include an on-chip transceiver (TRX) (or in some cases, just a receiver (RX)). The Bluetooth module 1612, the WLAN module 1614, and the SPS module 1616 may include their own dedicated antennas and / or utilize the antennas 1680 for communication. The cellular baseband processor(s) 1624 communicates through the transceiver(s) 1622 via one or more antennas 1680 with the UE 104 and / or with an RU associated with a network entity 1602. The cellular baseband processor(s) 1624 and the application processor(s) 1606 may each include a computer-readable medium / memory 1624', 1606', respectively. The additional memory modules 1626 may also be considered a computer-readable medium / memory. Each computer-readable medium / memory 1624', 1606', 1626 may be non -transitory. The cellular baseband processor(s) 1624 and the application processor(s) 1606 are each responsible for general processing, including the execution of software stored on the computer-readable medium / memory. The software, when executed by the cellular baseband processor(s) 1624 / application processor(s) 1606, causes the cellular baseband processor(s) 1624 / application processor(s) 1606 to129025-2466WO01Qualcomm Ref. No. 2406551WO 56 perform the various functions described supra. The cellular baseband processor(s) 1624 and the application processor(s) 1606 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) 1624 and the application processor(s) 1606 may be configured to perform a first subset of the various functions described supra without information stored in 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 processor(s) 1624 / application processor(s) 1606 when executing software. The cellular baseband processor(s) 1624 / application processor(s) 1606 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 1604 may be at least one processor chip (modem and / or application) and include just the cellular baseband processor(s) 1624 and / or the application processor(s) 1606, and in another configuration, the apparatus 1604 may be the entire UE (e.g., see UE 350 of FIG. 3) and include the additional modules of the apparatus 1604.

[0180] As discussed supra, the reference resource processing component 198 may be configured to communicate, with a network entity, an indication of a set of reference TRPs or resources for AI / ML, where the AI / ML is used in association with positioning. The reference resource processing component 198 may also be configured to perform at least one of the positioning or a set of measurements for the positioning with the AI / ML using at least one reference TRP or resource in the set of reference TRPs or resources. The reference resource processing component 198 may be within the cellular baseband processor(s) 1624, the application processor(s) 1606, or both the cellular baseband processor(s) 1624 and the application processor(s) 1606. The reference resource processing 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 / algorithm129025-2466WO01Qualcomm Ref. No. 2406551WO 57 individually or in combination. As shown, the apparatus 1604 may include a variety of components configured for various functions. In one configuration, the apparatus 1604, and in particular the cellular baseband processor(s) 1624 and / or the application processor(s) 1606, may include means for communicating, with a network entity, an indication of a set of reference TRPs or resources for AI / ML, where the AI / ML is used in association with positioning. The apparatus 1604 may further include means for performing at least one of the positioning or a set of measurements for the positioning with the AI / ML using at least one reference TRP or resource in the set of reference TRPs or resources.

[0181] In one configuration, the AI / ML includes one AI / ML model configured for one positioning method, and the one AI / ML model is trained, monitored, or inferenced with one reference TRP. In some implementations, the means for communicating, with the network entity, the indication of the set of reference TRPs or resources for the AI / ML may include configuring the apparatus 1604 to communicate, with the network entity, the indication of the set of reference TRPs or resources for the one AI / ML model via a PRS ID information message.

[0182] In another configuration, the AI / ML includes multiple AI / ML models configured for one positioning method, and the multiple AI / ML models are trained, monitored, or inferenced with one or more reference TRPs. In some implementations, the means for communicating, with the network entity, the indication of the set of reference TRPs or resources for the AI / ML may include configuring the apparatus 1604 to communicate, with the network entity, the indication of the set of reference TRPs or resources for the multiple AI / ML models via a dedicated reference structure message.

[0183] In another configuration, the set of reference TRPs or resources are associated with a priority, and the apparatus 1604 may further include means for receiving, from the network entity or an LMF, a second indication of the priority associated with the set of reference TRPs or resources.

[0184] In another configuration, communication of the indication is based on a set of capabilities of the UE, where the set of capabilities includes at least one of a maximum number of TRPs or TRP resources sets supported for AI / ML data collection, a maximum number of TRPs or TRP resources sets supported for AI / ML training, a maximum number of TRPs or TRP resources sets supported for AI / ML129025-2466WO01Qualcomm Ref. No. 2406551WO 58 monitoring, or a maximum number of TRPs or TRP resources sets supported for AI / ML inference.

[0185] In another configuration, one or more reference TRPs or resources in the set of reference TRPs or resources are AI / ML model specific.

[0186] In another configuration, the means for communicating the indication of the set of reference TRPs or resources for the AI / ML may include configuring the apparatus 1604 to communicate the indication of the set of reference TRPs or resources for the AI / ML during a training data collection, a monitoring data collection, or an inference.

[0187] In another configuration, the apparatus 1604 may further include means for receiving, from the network entity, a configuration for a set of additional reference TRPs or resources for non- AI / ML positioning or non-AI / ML measurements.

[0188] In another configuration, the AI / ML corresponds to at least one physical AI / ML model, at least one logical AI / ML model, or at least one AI / ML functionality.

[0189] In another configuration, the apparatus 1604 may further include means for transmitting, to the network entity, at least one of a position of the UE from the positioning or a measurement for positioning of the UE from the set of measurements.

[0190] In another configuration, the apparatus 1604 may further include means for transmitting, to the network entity, a list of recommended reference TRPs or resources for at least one AI / ML operation.

[0191] In another configuration, the apparatus 1604 may further include means for receiving, from the network entity, a list of reference TRPs or resources for at least one AI / ML operation, and means for performing the at least one AI / ML operation for the AI / ML based on the list of reference TRPs or resources. In some implementations, the means for performing the at least one AI / ML operation for the AI / ML based on the list of reference TRPs or resources may include configuring the apparatus 1604 to at least one of perform the at least one AI / ML operation for one AI / ML model with a plurality of reference TRPs or resources in the list of reference TRPs or resources, perform the at least one AI / ML operation for multiple AI / ML models with each AI / ML model in the multiple AI / ML model using one reference TRP or resource in the list of reference TRPs or resources, or perform the at least one AI / ML operation for the AI / ML based on the list of reference TRPs or resources and a set of index or IDs associated with the list of reference TRPs or resources.129025-2466WO01Qualcomm Ref. No. 2406551WO 59

[0192] In another configuration, the apparatus 1604 may further include means for communicating, with the network entity for an AI / ML LCM function or phase of a reference TRP in the set of TRPs, at least one of a first list of reference TRPs or TRP resources sets for AI / ML data collection, a second list of reference TRPs or TRP resources sets for AI / ML training, a third list of reference TRPs or TRP resources sets for AI / ML monitoring, or a fourth list of reference TRPs or TRP resources sets for AI / ML inference.

[0193] In another configuration, the apparatus 1604 may further include means for selecting the at least one reference TRP or resource from the set of reference TRPs or resources for performing at least one of the positioning or the set of measurements for the positioning with the AI / ML based on at least one of a priority associated with the at least one reference TRP or resource, a scheduling or selection associated with the at least one reference TRP or resource, or a provision to use the at least one reference TRP or resource for reporting.

[0194] In another configuration, the apparatus 1604 may further include means for receiving, from the network entity, a request to activate at least one additional reference TRP or resource during a positioning session, and means for performing, based on reception of the request to activate the at least one additional reference TRP or resource, at least one of the positioning or the set of measurements for the positioning with the AI / ML using the at least one additional reference TRP or resource.

[0195] In another configuration, the apparatus 1604 may further include means for receiving, from the network entity, a request to deactivate one or more reference TRPs or resources in the set of reference TRPs or resources during a positioning session, and means for performing, based on reception of the request, at least one of the positioning or the set of measurements for the positioning with the AI / ML without using the one or more reference TRPs or resources.

[0196] In another configuration, the means for performing at least one of the positioning or the set of measurements for the positioning with the AI / ML using the at least one reference TRP or resource in the set of reference TRPs or resources may include configuring the apparatus 1604 to switch from at least a first reference TRP or resource in the set of reference TRPs or resources to at least a second reference TRP or resource in the set of reference TRPs or resources based on at least one trigger condition or explicit signaling, and perform at least one of the positioning or the set129025-2466WO01Qualcomm Ref. No. 2406551WO 60 of measurements for the positioning with the AI / ML using the second reference TRP or resource in the set of reference TRPs or resources.

[0197] In another configuration, the apparatus 1604 may further include means for transmitting, to the network entity, a second indication of the at least one reference TRP or resource used for performing at least one of the positioning or the set of measurements for the positioning, where the second indication includes a timestamp of when the at least one reference TRP or resource is used.

[0198] In another configuration, the apparatus 1604 may further include means for selecting the at least one reference TRP or resource from the set of reference TRPs or resources for performing at least one of the positioning or the set of measurements for the positioning with the AI / ML based on whether the AI / ML is associated with data collection for AI / ML training, monitoring, or inference.

[0199] The means may be the reference resource processing component 198 of the apparatus 1604 configured to perform the functions recited by the means. As described supra, the apparatus 1604 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.

[0200] 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 server 704; the network entity 1204, 1860). The method may enable the network entity to communicate with a UE regarding reference resources (e.g., reference PRS(s) / TRP(s)) used or to be used by the UE for AI / ML positioning (and optionally for non-AI / ML positioning), such that the network entity is able to know which reference resources are used for which AI / ML models, thereby improving the overall performance and accuracy of AI / ML positioing.

[0201] At 1702, the network entity may communicate, with a user equipment (UE), an indication of a set of TRPs or resources for AI / ML, where the AI / ML is used in association with positioning, such as described in connection with FIG. 12. For example, at 1210, a network entity 1204 may communicate, with a UE 1202, an indication of a set of reference TRPs, a set of reference resources, and / or a set of resource sets (collectively as “reference TRP(s) / resource(s)” hereafter) for AI / ML, such as AI / ML used in association with positioning. The communication of the129025-2466WO01Qualcomm Ref. No. 2406551WO 61 indication may be performed by, e.g., the reference resource configuration component 197, the network processor(s) 1812, and / or the network interface 1880 of the network entity 1860 in FIG. 18.

[0202] At 1704, the network entity may receive, from the UE, at least one of a position of the UE or a set of measurements for positioning of the UE obtained based on at least one reference TRP or resource in the set of reference TRPs or resources, such as described in connection with FIG. 12. For example, at 1234, the network entity 1204 may receive, from the UE 1202, the position of the UE 1202 and / or the positioning measurements. The reception of the position of the UE or the set of measurements may be performed by, e.g., the reference resource configuration component 197, the network processor(s) 1812, and / or the network interface 1880 of the network entity 1860 in FIG. 18.

[0203] In one example, the AI / ML includes one AI / ML model configured for one positioning method, and the one AI / ML model is trained, monitored, or inferenced with one reference TRP. In some implementations, to communicate, with the UE, the indication of the set of reference TRPs or resources for the AI / ML, the network entity may be configured to communicate, with the UE, the indication of the set of reference TRPs or resources for the one AI / ML model via a PRS ID information message.

[0204] In another example, the AI / ML includes multiple AI / ML models configured for one positioning method, where the multiple AI / ML models are trained, monitored, or inferenced with one or more reference TRPs. In some implementations, to communicate, with the UE, the indication of the set of reference TRPs or resources for the AI / ML, the network entity may be configured to communicate, with the UE, the indication of the set of reference TRPs or resources for the multiple AI / ML models via a dedicated reference structure message.

[0205] In another example, the set of reference TRPs or resources are associated with a priority, the network entity may transmit, to the UE, a second indication of the priority associated with the set of reference TRPs or resources.

[0206] In another example, the network entity may transmit, to the UE, a request to activate at least one additional reference TRP or resource or to deactivate one or more reference TRPs or resources in the set of reference TRPs or resources during a positioning session129025-2466WO01Qualcomm Ref. No. 2406551WO 62

[0207] In another example, the network entity may communicate, with the UE for an AI / ML LCM function or phase of a reference TRP in the set of TRPs, at least one of: a first list of reference TRPs or TRP resources sets for AI / ML data collection, a second list of reference TRPs or TRP resources sets for AI / ML training, a third list of reference TRPs or TRP resources sets for AI / ML monitoring, or a fourth list of reference TRPs or TRP resources sets for AI / ML inference.

[0208] In another example, the network entity may transmit, to the UE, a list of reference TRPs or resources for at least one AI / ML operation.

[0209] In another example, the network entity may receive, from the UE, a list of recommended reference TRPs or resources for at least one AI / ML operation.

[0210] In another example, to communicate the indication of the set of reference TRPs or resources for the AI / ML, the network entity may be configured to communicate the indication of the set of reference TRPs or resources for the AI / ML during a training data collection, a monitoring data collection, or an inference.

[0211] In another example, the AI / ML corresponds to at least one physical AI / ML model, at least one logical AI / ML model, or at least one AI / ML functionality.

[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 1860 communicates via the network interface 1880 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 reference resource configuration component 197 may be configured to communicate, with a UE, an indication of a set of reference TRPs or129025-2466WO01Qualcomm Ref. No. 2406551WO 63 resources for AI / ML, where the AI / ML is used in association with positioning. The reference resource configuration component 197 may also be configured to receive, from the UE, at least one of a position of the UE or a set of measurements for positioning of the UE obtained based on at least one reference TRP or resource in the set of reference TRPs or resources. The reference resource configuration component 197 may be within the network processor(s) 1812. The reference resource 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 for various functions. In one configuration, the network entity 1860 may include means for communicating, with a UE, an indication of a set of reference TRPs or resources for AI / ML, where the AI / ML is used in association with positioning. The network entity 1860 may further include means for receiving, from the UE, at least one of a position of the UE or a set of measurements for positioning of the UE obtained based on at least one reference TRP or resource in the set of reference TRPs or resources.

[0214] In one configuration, the AI / ML includes one AI / ML model configured for one positioning method, and the one AI / ML model is trained, monitored, or inferenced with one reference TRP. In some implementations, the means for communicating, with the UE, the indication of the set of reference TRPs or resources for the AI / ML may include configuring the network entity 1860 to communicate, with the UE, the indication of the set of reference TRPs or resources for the one AI / ML model via a PRS ID information message.

[0215] In another example, the AI / ML includes multiple AI / ML models configured for one positioning method, where the multiple AI / ML models are trained, monitored, or inferenced with one or more reference TRPs. In some implementations, the means for communicating, with the UE, the indication of the set of reference TRPs or resources for the AI / ML may include configuring the network entity 1860 to communicate, with129025-2466WO01Qualcomm Ref. No. 2406551WO 64 the UE, the indication of the set of reference TRPs or resources for the multiple AI / ML models via a dedicated reference structure message.

[0216] In another example, the set of reference TRPs or resources are associated with a priority, the network entity 1860 may further include means for transmitting, to the UE, a second indication of the priority associated with the set of reference TRPs or resources.

[0217] In another example, the network entity 1860 may further include means for transmitting, to the UE, a request to activate at least one additional reference TRP or resource or to deactivate one or more reference TRPs or resources in the set of reference TRPs or resources during a positioning session

[0218] In another example, the network entity 1860 may further include means for communicating, with the UE for an AI / ML LCM function or phase of a reference TRP in the set of TRPs, at least one of: a first list of reference TRPs or TRP resources sets for AI / ML data collection, a second list of reference TRPs or TRP resources sets for AI / ML training, a third list of reference TRPs or TRP resources sets for AI / ML monitoring, or a fourth list of reference TRPs or TRP resources sets for AI / ML inference.

[0219] In another example, the network entity 1860 may further include means for transmitting, to the UE, a list of reference TRPs or resources for at least one AI / ML operation.

[0220] In another example, the network entity 1860 may further include means for receiving, from the UE, a list of recommended reference TRPs or resources for at least one AI / ML operation.

[0221] In another example, the means for communicating the indication of the set of reference TRPs or resources for the AI / ML may include configuring the network entity 1860 to communicate the indication of the set of reference TRPs or resources for the AI / ML during a training data collection, a monitoring data collection, or an inference.

[0222] In another example, the AI / ML corresponds to at least one physical AI / ML model, at least one logical AI / ML model, or at least one AI / ML functionality.

[0223] The means may be the reference resource configuration component 197 of the network entity 1860 configured to perform the functions recited by the means.129025-2466WO01Qualcomm Ref. No. 2406551WO 65

[0224] 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 may be 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.

[0225] 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, these phrases, e.g., “when,” do not imply 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, but without requiring a 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, or C. 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.129025-2466WO01Qualcomm Ref. No. 2406551WO 66Accordingly, 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 data from or transmits 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 throughout this 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.”

[0226] 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.

[0227] The following aspects are illustrative only and may be combined with other aspects or teachings described herein, without limitation.

[0228] Aspect 1 is a method of wireless communication at a user equipment (UE), comprising: communicating, with a network entity, an indication of a set of reference transmission reception points (TRPs) or resources for artificial intelligence (Al) or machine learning (ML) (AI / ML), wherein the AI / ML is used in association with positioning; and performing at least one of the positioning or a set of measurements129025-2466WO01Qualcomm Ref. No. 2406551WO 67 for the positioning with the AI / ML using at least one reference TRP or resource in the set of reference TRPs or resources.

[0229] Aspect 2 is the method of aspect 1, further comprising: transmitting, to the network entity, at least one of a position of the UE from the positioning or a measurement for positioning of the UE from the set of measurements.

[0230] Aspect 3 is the method of aspect 1 or aspect 2, wherein the AI / ML includes one AI / ML model configured for one positioning method, wherein the one AI / ML model is trained, monitored, or inferenced with one reference TRP, and wherein communicating, with the network entity, the indication of the set of reference TRPs or resources for the AI / ML comprises: communicating, with the network entity, the indication of the set of reference TRPs or resources for the one AI / ML model via a positioning reference signal (PRS) identification (ID) information message.

[0231] Aspect 4 is the method of any of aspects 1 to 3, wherein the AI / ML includes multiple AI / ML models configured for one positioning method, wherein the multiple AI / ML models are trained, monitored, or inferenced with one or more reference TRPs, and wherein communicating, with the network entity, the indication of the set of reference TRPs or resources for the AI / ML comprises: communicating, with the network entity, the indication of the set of reference TRPs or resources for the multiple AI / ML models via a dedicated reference structure message.

[0232] Aspect 5 is the method of any of aspects 1 to 4, wherein the set of reference TRPs or resources are associated with a priority, the method further comprising: receiving, from the network entity or a location management function (LMF), a second indication of the priority associated with the set of reference TRPs or resources.

[0233] Aspect 6 is the method of any of aspects 1 to 5, further comprising: receiving, from the network entity, a request to activate at least one additional reference TRP or resource during a positioning session; and performing, based on reception of the request to activate the at least one additional reference TRP or resource, at least one of the positioning or the set of measurements for the positioning with the AI / ML using the at least one additional reference TRP or resource.

[0234] Aspect 7 is the method of any of aspects 1 to 6, further comprising: receiving, from the network entity, a request to deactivate one or more reference TRPs or resources in the set of reference TRPs or resources during a positioning session; and performing, based on reception of the request, at least one of the positioning or the set of129025-2466WO01Qualcomm Ref. No. 2406551WO 68 measurements for the positioning with the AI / ML without using the one or more reference TRPs or resources.

[0235] Aspect 8 is the method of any of aspects 1 to 7, further comprising: communicating, with the network entity for an AI / ML life cycle management (LCM) function or phase of a reference TRP in the set of TRPs, at least one of: a first list of reference TRPs or TRP resources sets for AI / ML data collection, a second list of reference TRPs or TRP resources sets for AI / ML training, a third list of reference TRPs or TRP resources sets for AI / ML monitoring, or a fourth list of reference TRPs or TRP resources sets for AI / ML inference.

[0236] Aspect 9 is the method of any of aspects 1 to 8, further comprising: receiving, from the network entity, a list of reference TRPs or resources for at least one AI / ML operation; and performing the at least one AI / ML operation for the AI / ML based on the list of reference TRPs or resources.

[0237] Aspect 10 is the method of any of aspects 1 to 9, wherein performing the at least one AI / ML operation for the AI / ML based on the list of reference TRPs or resources includes at least one of: perform the at least one AI / ML operation for one AI / ML model with a plurality of reference TRPs or resources in the list of reference TRPs or resources, perform the at least one AI / ML operation for multiple AI / ML models with each AI / ML model in the multiple AI / ML model using one reference TRP or resource in the list of reference TRPs or resources, or perform the at least one AI / ML operation for the AI / ML based on the list of reference TRPs or resources and a set of index or identifiers (IDs) associated with the list of reference TRPs or resources.

[0238] Aspect 11 is the method of any of aspects 1 to 10, further comprising: transmitting, to the network entity, a list of recommended reference TRPs or resources for at least one AI / ML operation.

[0239] Aspect 12 is the method of any of aspects 1 to 11, wherein communication of the indication is based on a set of capabilities of the UE, wherein the set of capabilities includes at least one of: a maximum number of TRPs or TRP resources sets supported for AI / ML data collection, a maximum number of TRPs or TRP resources sets supported for AI / ML training, a maximum number of TRPs or TRP resources sets supported for AI / ML monitoring, or a maximum number of TRPs or TRP resources sets supported for AI / ML inference.129025-2466WO01Qualcomm Ref. No. 2406551WO 69

[0240] Aspect 13 is the method of any of aspects 1 to 12, wherein one or more reference TRPs or resources in the set of reference TRPs or resources are AI / ML model specific.

[0241] Aspect 14 is the method of any of aspects 1 to 13, wherein performing at least one of the positioning or the set of measurements for the positioning with the AI / ML using the at least one reference TRP or resource in the set of reference TRPs or resources comprises: switching from at least a first reference TRP or resource in the set of reference TRPs or resources to at least a second reference TRP or resource in the set of reference TRPs or resources based on at least one trigger condition or explicit signaling; and performing at least one of the positioning or the set of measurements for the positioning with the AI / ML using the second reference TRP or resource in the set of reference TRPs or resources.

[0242] Aspect 15 is the method of any of aspects 1 to 14, further comprising: selecting the at least one reference TRP or resource from the set of reference TRPs or resources for performing at least one of the positioning or the set of measurements for the positioning with the AI / ML based on at least one of: a priority associated with the at least one reference TRP or resource, a scheduling or selection associated with the at least one reference TRP or resource, or a provision to use the at least one reference TRP or resource for reporting.

[0243] Aspect 16 is the method of any of aspects 1 to 15, further comprising: transmitting, to the network entity, a second indication of the at least one reference TRP or resource used for performing at least one of the positioning or the set of measurements for the positioning, wherein the second indication includes a timestamp of when the at least one reference TRP or resource is used.

[0244] Aspect 17 is the method of any of aspects 1 to 16, further comprising: selecting the at least one reference TRP or resource from the set of reference TRPs or resources for performing at least one of the positioning or the set of measurements for the positioning with the AI / ML based on whether the AI / ML is associated with data collection for AI / ML training, monitoring, or inference.

[0245] Aspect 18 is the method of any of aspects 1 to 17, wherein communicating the indication of the set of reference TRPs or resources for the AI / ML comprises: communicating the indication of the set of reference TRPs or resources for the AI / ML during a training data collection, a monitoring data collection, or an inference.129025-2466WO01Qualcomm Ref. No. 2406551WO 70

[0246] Aspect 19 is the method of any of aspects 1 to 18, further comprising: receiving, from the network entity, a configuration for a set of additional reference TRPs or resources for non-AI / ML positioning or non-AI / ML measurements.

[0247] Aspect 20 is the method of any of aspects 1 to 19, wherein the AI / ML corresponds to at least one physical AI / ML model, at least one logical AI / ML model, or at least one AI / ML functionality.

[0248] Aspect 21 is an apparatus for wireless communication at a user equipment (UE), 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 20.

[0249] Aspect 22 is the apparatus of aspect 21, further including at least one transceiver coupled to the at least one processor.

[0250] Aspect 23 is an apparatus for wireless communication at a user equipment (UE) including means for implementing any of aspects 1 to 20.

[0251] Aspect 24 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 20.

[0252] Aspect 25 is a method of wireless communication at a network entity, comprising: communicating, with a user equipment (UE), an indication of a set of reference transmission reception points (TRPs) or resources for artificial intelligence (Al) or machine learning (ML) (AI / ML), wherein the AI / ML is used in association with positioning; and receiving, from the UE, at least one of a position of the UE or a set of measurements for positioning of the UE obtained based on at least one reference TRP or resource in the set of reference TRPs or resources.

[0253] Aspect 26 is the method of aspect 25, wherein the AI / ML includes one AI / ML model configured for one positioning method, wherein the one AI / ML model is trained, monitored, or inferenced with one reference TRP, and wherein communicating, with the UE, the indication of the set of reference TRPs or resources for the AI / ML comprises: communicating, with the UE, the indication of the set of reference TRPs or resources for the one AI / ML model via a positioning reference signal (PRS) identification (ID) information message.129025-2466WO01Qualcomm Ref. No. 2406551WO 71

[0254] Aspect 27 is the method of aspect 25 or aspect 26, wherein the AI / ML includes multiple AI / ML models configured for one positioning method, wherein the multiple AI / ML models are trained, monitored, or inferenced with one or more reference TRPs, and wherein communicating, with the UE, the indication of the set of reference TRPs or resources for the AI / ML comprises: communicating, with the UE, the indication of the set of reference TRPs or resources for the multiple AI / ML models via a dedicated reference structure message.

[0255] Aspect 28 is the method of any of aspects 25 to 27, wherein the set of reference TRPs or resources are associated with a priority, the method further comprising: transmitting, to the UE, a second indication of the priority associated with the set of reference TRPs or resources.

[0256] Aspect 29 is the method of any of aspects 25 to 28, further comprising: transmitting, to the UE, a request to activate at least one additional reference TRP or resource or to deactivate one or more reference TRPs or resources in the set of reference TRPs or resources during a positioning session.

[0257] Aspect 30 is the method of any of aspects 25 to 29, further comprising: communicating, with the UE for an AI / ML life cycle management (LCM) function or phase of a reference TRP in the set of TRPs, at least one of: a first list of reference TRPs or TRP resources sets for AI / ML data collection, a second list of reference TRPs or TRP resources sets for AI / ML training, a third list of reference TRPs or TRP resources sets for AI / ML monitoring, or a fourth list of reference TRPs or TRP resources sets for AI / ML inference.

[0258] Aspect 31 is the method of any of aspects 25 to 30, further comprising: transmitting, to the UE, a list of reference TRPs or resources for at least one AI / ML operation.

[0259] Aspect 32 is the method of any of aspects 25 to 31, further comprising: receiving, from the UE, a list of recommended reference TRPs or resources for at least one AI / ML operation.

[0260] Aspect 33 is the method of any of aspects 25 to 32, wherein communicating the indication of the set of reference TRPs or resources for the AI / ML comprises: communicating the indication of the set of reference TRPs or resources for the AI / ML during a training data collection, a monitoring data collection, or an inference.129025-2466WO01Qualcomm Ref. No. 2406551WO 72

[0261] Aspect 34 is the method of any of aspects 25 to 33, wherein the AI / ML corresponds to at least one physical AI / ML model, at least one logical AI / ML model, or at least one AI / ML functionality.

[0262] Aspect 35 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 25 to 34.

[0263] Aspect 36 is the apparatus of aspect 35, further including at least one network interface coupled to the at least one processor.

[0264] Aspect 37 is an apparatus for wireless communication at a network entity including means for implementing any of aspects 25 to 34.

[0265] Aspect 38 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 25 to 34.129025-2466WO01

Claims

Qualcomm Ref. No. 2406551WO 73CLAIMSWHAT IS CLAIMED IS:

1. An apparatus for wireless communication at a user equipment (UE), comprising: at least one memory; and at least one processor coupled to the at least one memory, wherein the at least one processor is configured to: communicate, with a network entity, an indication of a set of reference transmission reception points (TRPs) or resources for artificial intelligence (Al) or machine learning (ML) (AI / ML), wherein the AI / ML is used in association with positioning; and perform at least one of the positioning or a set of measurements for the positioning with the AI / ML using at least one reference TRP or resource in the set of reference TRPs or resources.

2. The apparatus of claim 1, wherein the at least one processor is further configured to: transmit, to the network entity, at least one of a position of the UE from the positioning or a measurement for positioning of the UE from the set of measurements.

3. The apparatus of claim 1, wherein the AI / ML includes one AI / ML model configured for one positioning method, wherein the one AI / ML model is trained, monitored, or inferenced with one reference TRP, and wherein to communicate, with the network entity, the indication of the set of reference TRPs or resources for the AI / ML, the at least one processor is configured to: communicate, with the network entity, the indication of the set of reference TRPs or resources for the one AI / ML model via a positioning reference signal (PRS) identification (ID) information message.

4. The apparatus of claim 1, wherein the AI / ML includes multiple AI / ML models configured for one positioning method, wherein the multiple AI / ML models are trained, monitored, or inferenced with one or more reference TRPs, and wherein to communicate,129025-2466WO01Qualcomm Ref. No. 2406551WO 74 with the network entity, the indication of the set of reference TRPs or resources for the AI / ML, the at least one processor is configured to: communicate, with the network entity, the indication of the set of reference TRPs or resources for the multiple AI / ML models via a dedicated reference structure message.

5. The apparatus of claim 1, wherein the set of reference TRPs or resources are associated with a priority, wherein the at least one processor is further configured to: receive, from the network entity or a location management function (LMF), a second indication of the priority associated with the set of reference TRPs or resources.

6. The apparatus of claim 1, wherein the at least one processor is further configured to: receive, from the network entity, a request to activate at least one additional reference TRP or resource during a positioning session; and perform, based on reception of the request to activate the at least one additional reference TRP or resource, at least one of the positioning or the set of measurements for the positioning with the AI / ML using the at least one additional reference TRP or resource.

7. The apparatus of claim 1, wherein the at least one processor is further configured to: receive, from the network entity, a request to deactivate one or more reference TRPs or resources in the set of reference TRPs or resources during a positioning session; and perform, based on reception of the request, at least one of the positioning or the set of measurements for the positioning with the AI / ML without using the one or more reference TRPs or resources.

8. The apparatus of claim 1, wherein the at least one processor is further configured to:129025-2466WO01Qualcomm Ref. No. 2406551WO 75 communicate, with the network entity for an AI / ML life cycle management (LCM) function or phase of a reference TRP in the set of TRPs, at least one of: a first list of reference TRPs or TRP resources sets for AI / ML data collection, a second list of reference TRPs or TRP resources sets for AI / ML training, a third list of reference TRPs or TRP resources sets for AI / ML monitoring, or a fourth list of reference TRPs or TRP resources sets for AI / ML inference.

9. The apparatus of claim 1, wherein the at least one processor is further configured to: receive, from the network entity, a list of reference TRPs or resources for at least one AI / ML operation; and perform the at least one AI / ML operation for the AI / ML based on the list of reference TRPs or resources.

10. The apparatus of claim 9, wherein to perform the at least one AI / ML operation for the AI / ML based on the list of reference TRPs or resources, the at least one processor is configured to at least one of: perform the at least one AI / ML operation for one AI / ML model with a plurality of reference TRPs or resources in the list of reference TRPs or resources, perform the at least one AI / ML operation for multiple AI / ML models with each AI / ML model in the multiple AI / ML model using one reference TRP or resource in the list of reference TRPs or resources, or perform the at least one AI / ML operation for the AI / ML based on the list of reference TRPs or resources and a set of index or identifiers (IDs) associated with the list of reference TRPs or resources.

11. The apparatus of claim 1, wherein the at least one processor is further configured to: transmit, to the network entity, a list of recommended reference TRPs or resources for at least one AI / ML operation.129025-2466WO01Qualcomm Ref. No. 2406551WO 7612. The apparatus of claim 1, wherein communication of the indication is based on a set of capabilities of the UE, wherein the set of capabilities includes at least one of: a maximum number of TRPs or TRP resources sets supported for AI / ML data collection, a maximum number of TRPs or TRP resources sets supported for AI / ML training, a maximum number of TRPs or TRP resources sets supported for AI / ML monitoring, or a maximum number of TRPs or TRP resources sets supported for AI / ML inference.

13. The apparatus of claim 1, wherein one or more reference TRPs or resources in the set of reference TRPs or resources are AI / ML model specific.

14. The apparatus of claim 1, wherein to perform at least one of the positioning or the set of measurements for the positioning with the AI / ML using the at least one reference TRP or resource in the set of reference TRPs or resources, the at least one processor is configured to: switch from at least a first reference TRP or resource in the set of reference TRPs or resources to at least a second reference TRP or resource in the set of reference TRPs or resources based on at least one trigger condition or explicit signaling; and perform at least one of the positioning or the set of measurements for the positioning with the AI / ML using the second reference TRP or resource in the set of reference TRPs or resources.

15. The apparatus of claim 1, wherein the at least one processor is further configured to: select the at least one reference TRP or resource from the set of reference TRPs or resources for performing at least one of the positioning or the set of measurements for the positioning with the AI / ML based on at least one of: a priority associated with the at least one reference TRP or resource, a scheduling or selection associated with the at least one reference TRP or resource, or a provision to use the at least one reference TRP or resource for reporting.129025-2466WO01Qualcomm Ref. No. 2406551WO 7716. The apparatus of claim 1, wherein the at least one processor is further configured to: transmit, to the network entity, a second indication of the at least one reference TRP or resource used for performing at least one of the positioning or the set of measurements for the positioning, wherein the second indication includes a timestamp of when the at least one reference TRP or resource is used.

17. The apparatus of claim 1, wherein the at least one processor is further configured to: select the at least one reference TRP or resource from the set of reference TRPs or resources for performing at least one of the positioning or the set of measurements for the positioning with the AI / ML based on whether the AI / ML is associated with data collection for AI / ML training, monitoring, or inference.

18. The apparatus of claim 1, wherein the at least one processor is further configured to: receive, from the network entity, a configuration for a set of additional reference TRPs or resources for non-AI / ML positioning or non- AI / ML measurements.

19. A method of wireless communication at a user equipment (UE), comprising: communicating, with a network entity, an indication of a set of reference transmission reception points (TRPs) or resources for artificial intelligence (Al) or machine learning (ML) (AI / ML), wherein the AI / ML is used in association with positioning; and performing at least one of the positioning or a set of measurements for the positioning with the AI / ML using at least one reference TRP or resource in the set of reference TRPs or resources.

20. An apparatus for wireless communication at a network entity, comprising: at least one memory; and129025-2466WO01Qualcomm Ref. No. 2406551WO 78 at least one processor coupled to the at least one memory, the at least one processor is configured to: communicate, with a user equipment (UE), an indication of a set of reference transmission reception points (TRPs) or resources for artificial intelligence (Al) or machine learning (ML) (AI / ML), wherein the AI / ML is used in association with positioning; and receive, from the UE, at least one of a position of the UE or a set of measurements for positioning of the UE obtained based on at least one reference TRP or resource in the set of reference TRPs or resources.129025-2466WO01

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