Phase-based artificial intelligence or machine learning assisted positioning

Abstract

Aspects presented herein may enable a wireless device (e.g., a UE, a positioning reference unit (PRU), a base station, a transmission reception point (TRP), etc.) to perform phase measurements using artificial intelligence or machine learning (AI / ML) and indicate that the phase measurements are performed using the AI / ML, thereby improving the performance of phase-based AI / ML assisted positioning. In one aspect, a wireless device obtains a first indication of a measurement of at least one of a reference signal carrier phase (RSCP) or a reference signal carrier phase difference (RSCPD) for a set of reference signals (RSs) using AI / ML. The wireless device transmits a second indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs, where the second indication indicates that at least one of the RSCP or the RSCPD for the set of RSs is obtained using the AI / ML.

Description

Qualcomm Ref. No. 2405929WO 1PHASE-BASED ARTIFICIAL INTELLIGENCE OR MACHINE LEARNING ASSISTED POSITIONINGCROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims the benefit of Greece Patent Application No. 20240100803, entitled “PHASE-BASED ARTIFICIAL INTELLIGENCE OR MACHINE LEARNING ASSISTED POSITIONING” and filed on November 13, 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), massive129025-2434WO01Qualcomm Ref. No. 2405929WO 2machine type communications (mMTC), and ultra-reliable low latency communications (URLLC). Some aspects of 5G NR may be based on the 4G Long Term Evolution (LTE) standard. There exists a need for further improvements in 5G NR technology. These improvements may also be applicable to other multi-access technologies and the telecommunication standards that employ these technologies.

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

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

[0007] In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus obtains a first indication of a measurement of at least one of a reference signal carrier phase (RSCP) or a reference signal carrier phase difference (RSCPD) for a set of reference signals (RSs) using artificial intelligence (Al) or machine learning (ML) (AI / ML). The apparatus transmits a second indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs, where the second indication indicates that at least one of the RSCP or the RSCPD for the set of RSs is obtained using the AI / ML.

[0008] In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus receives, from a wireless device, a measurement of at least one of an RSCP or an RSCPD for a set of RSs. The apparatus receives, from the wireless device, an indication indicating that the measurement of at least one of the RSCP or the RSCPD for the set of RSs is obtained using AI / ML.129025-2434WO01Qualcomm Ref. No. 2405929WO 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. 5 A 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.129025-2434WO01Qualcomm Ref. No. 2405929WO 4

[0021] FIG. 8 A 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 ofinferencingphasemeasurement(s) and quality of the phase measurement(s) in accordance with various aspects of the present disclosure.

[0026] FIG. 11 is a communication flow illustrating an example phase-based AI / ML assisted positioning between aUE and a location server in accordance with various aspects of the present disclosure.

[0027] FIG. 12 is a communication flow illustrating an example phase-based AI / ML assisted positioningbetween a network entity and a location server in accordance with various aspects of the present disclosure.

[0028] FIG. 13 is a communication flow illustrating an example phase-based AI / ML assisted positioningbetween a sidelink UE and a location server 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 diagram illustrating an example of a hardware implementation for an example network entity.

[0033] FIG. 18 is a flowchart of a method of wireless communication.

[0034] FIG. 19 is a diagram illustrating an example of a hardware implementation for an example network entity.129025-2434WO01Qualcomm Ref. No. 2405929WO 5DETAILED DESCRIPTION

[0035] Aspects presented herein may improve the overall performance and efficiency of artificial intelligence (Al) or machine learning (ML) (AI / ML) positioning related operations (e.g., training, inferencing, data collection, etc.) by enabling phase-based AI / ML assisted positioning. For example, aspects presented herein may enable a UE or a network entity to adopt an AI / ML assisted approach to learn and provide enhanced phase measurements to be used for positioning. Aspects presented herein provide AI / ML model input and / or output design and related signaling for the phasebased AI / ML assisted positioning. Aspects presented herein also provide various reporting related to the phase-based AI / ML assisted positioning, which may include reporting for AI / ML model measurements, material information of surrounding area, and / or phase error information, etc.

[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 hereinmay be practiced. The detailed description includes specific details for the purpose of providing a thorough understanding of various concepts. However, these concepts may be practiced without these specific details. In some instances, well known structures and components are shown in block diagram form in order to avoid obscuring such concepts.

[0037] Several aspects of telecommunication systems are presented with referenceto various apparatus and methods. These apparatus and methods are described in the following detailed description and illustrated in the accompanying drawings by various blocks, components, circuits, processes, algorithms, etc. (collectively referred to 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), central129025-2434WO01Qualcomm Ref. No. 2405929WO 6processing 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, magnetic disk storage, other magnetic storage devices, combinations of the types of computer- readable media, or any other medium that can be used to store computer executable code in the form of instructions or data structures that can be accessed by a computer.

[0040] While aspects, implementations, and / or use cases are describedin this application by illustration to some examples, additional or different aspects, implementations and / or use cases may come about in many different arrangements and scenarios. Aspects, implementations, and / oruse cases described herein may be implemented across many differingplatform types, devices, systems, shapes, sizes, and packaging arrangements. For example, aspects, implementations, and / or use cases may come about via integrated chip implementations and other non-module-component based devices (e.g., end-user devices, vehicles, communication devices, computing devices, industrial equipment, retail / purchasing devices, medical devices, artificial intelligence (Al)-enabled devices, etc.). While some examples may or may not be129025-2434WO01Qualcomm Ref. No. 2405929WO 7specifically 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 incorp oratingone or more techniques herein. In some practical settings, devices incorporating described aspects and features may also include additional components and features for implementation and practice of claimed and described aspect. For example, transmission and reception of wireless signals necessarily includes a number of components for analog and digital purposes (e.g., hardware components including antenna, RF-chains, power amplifiers, modulators, buffer, processor(s), interleaver, adders / summers, etc.). Techniques described herein may be practiced in a wide variety of devices, chip-level components, systems, distributed arrangements, aggregated or disaggregated components, end-user devices, etc. of varying sizes, shapes, and constitution.

[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 an aggregated or disaggregated architecture. For example, a BS (such as a Node B (NB), evolved NB (eNB), NR BS, 5GNB, access point (AP), a transmission reception 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 RU129025-2434WO01Qualcomm Ref. No. 2405929WO 8can 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 0-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) Framework 105, or both). A CU 110 may communicate with one or more DUs 130 via respective midhaul links, such as an Fl interface. The DUs 130 may communicate with one 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, theUE 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 RIC s 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 transmit129025-2434WO01Qualcomm Ref. No. 2405929WO 9signals 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, theCU 110 can be logically split into one or more CU-UP units and one or more CU-CP units. The CU-UP unit can communicate bidirectionally with the CU-CP unit via an interface, such as an El interface when implemented in an 0-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 DU 130 may host one or more of a radio link control (RLC) layer, a medium access control (MAC) layer, and one or more high physical (PHY) layers (such as modules 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, based129025-2434WO01Qualcomm Ref. No. 2405929WO 10at 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-virtualizedandvirtualizednetwork elements. Fornon-virtualized network elements, the SMO Framework 105 may be configured to support the deployment of dedicatedphysical 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 andNear-RTRICs 125. In some implementations, the SMO Framework 105 can communicate with a hardware aspect of a 4G RAN, such as an open eNB (O- eNB) 111, via an 01 interface. Additionally, in some implementations, the SMO Framework 105 can communicate directly with one or more RUs 140 via an 01 interface. The SMO Framework 105 also may include aNon-RTRIC 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. TheNear-RTRIC 125 may be configured to include a logical function that enables near-real-time control and optimization of RAN elements and resources via dataset collection and actions over an interface (such as via an E2 interface) connecting one or more CUs 110, one or more DUs 130, or both, as well as an O-eNB, with the Near-RT RIC 125.129025-2434WO01Qualcomm Ref. No. 2405929WO 11

[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-RTRIC 115 or the Near-RT RIC 125 may be configured to tune RAN behavior or performance. For example, the Non-RT RIC 115 may monitor long-term trends and patterns for performance and employ AI / ML models to perform corrective actions through the SMO Framework 105 (such as reconfiguration via 01) or via creation of RAN management policies (such as Al policies).

[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, abase station 102 may include one ormore ofthe CU 110, the DU 130, and the RU 140 (each component indicated with dotted lines to signify that each component may or may not be included in the base station 102). The base station 102 provides an access point to the core network 120 for aUE 104. The base station 102 may include macrocells (high power cellular base station) and / or small cells (low power cellular base station). The small cells include femtocells, picocells, and microcells. A network that includes both small cell and macrocells may be known as a heterogeneous network. A heterogeneous network may also include Home Evolved Node Bs (eNBs) (HeNBs), which may provide service to a restricted group known as a closed subscriber group (CSG). The communication links between the RUs 140 and the UEs 104 may include uplink (UL) (also referred to as reverse link) transmissions fromaUE 104 to an RU 140 and / or downlink (DL) (also referred to as forward link) transmissions from an RU 140 to aUE 104. The communication links may use multiple-input and multiple-output (MIMO) antenna technology, including spatial multiplexing, beamforming, and / or transmit diversity. The communication links may be through one or more carriers. The base station 102 / UEs 104 may use spectrum up to fMHz (e.g., 5, 10, 15, 20, 100, 400, etc. MHz) bandwidth per carrier allocated in a carrier aggregation of up to a total of Fx MHz (x component carriers) used for transmission in each direction. The carriers may or may not be adjacent to each other. Allocation of carriers may be asymmetric with respect to DL andUL (e.g., more or fewer carriers may be allocated for DL than for UL). The component carriers may include a primary component carrier and one or more secondary component129025-2434WO01Qualcomm Ref. No. 2405929WO 12carriers. 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. TheD2D communication link 158 may use one or more sidelink channels, such as a physical sidelink broadcast channel (PSBCH), a physical sidelink discovery channel (PSDCH), a physical sidelink shared channel (PSSCH), and a physical sidelink control channel (PSCCH). D2D communication may be through a variety of wireless D2D communications systems, such as for example, Bluetooth™ (Bluetooth is a trademark of the Bluetooth Special Interest Group (SIG)), Wi-Fi™ (Wi-Fi is a trademark of the Wi-Fi Alliance) based on the Institute of Electrical and Electronics Engineers (IEEE) 802.11 standard, LTE, or NR.

[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 orthe like. When communicating in an unlicensed frequency spectrum, the UEs 104 / AP 150 may perform a clear channel assessment (CCA) prior to communicating in order to determine whether the channel is available.

[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” bandin documents and articles, despite being different from the extremely high frequency (EHF) band (30 GHz - 300 GHz) which is identified by the International Telecommunications Union (ITU) as a “millimeter wave” band.

[0056] The frequencies between FR1 andFR2 are often referred to as mid-band frequencies.Recent 5G NR studies have identified an operating band for these mid-band frequencies as frequency range designation FR3 (7.125 GHz - 24.25 GHz). Frequency bands falling within FR3 may inherit FR1 characteristics and / or FR2129025-2434WO01Qualcomm Ref. No. 2405929WO 13characteristics, 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 op erating bands have been identified as frequency range designations FR2-2 (52.6 GHz - 71 GHz), FR4 (71 GHz- 114.25 GHz), andFR5 (114.25 GHz- 300 GHz). Each of these hi^ier frequency bands falls within the EHF band.

[0057] With the above aspects in mind, unless specifically stated otherwise, the term “sub-6GHz” or the like if used herein may broadly represent frequencies that may be less than 6 GHz, may be within FR1 , or may include mid-band frequencies. Further, unless specifically stated otherwise, the term “millimeter wave” or the like if used herein may broadly represent frequencies that may include mid-band frequencies, may be within FR2, FR4, FR2-2, and / or FR5, or may be within the EHF band.

[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 more receive directions. The base station 102 / UE 104 may perform beam training to determine the best receive and transmit directions for each of the base station 102 / 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. The129025-2434WO01Qualcomm Ref. No. 2405929WO 14set 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 sub scription management. The one or more location servers 168 are illustrated as including a Gateway Mobile Location Center (GMLC) 165 and a Location Management Function (LMF) 166. However, generally, the one or more location servers 168 may include one or more location / positioning servers, which may include one or more of the GMLC 165, the LMF 166, a position determination entity (PDE), a serving mobile location center (SMLC), a mobile positioning center (MPC), or the like. The GMLC 165 and the LMF 166 support UE location services. The GMLC 165 provides an interface for clients / applications (e.g., emergency services) for accessing UE positioning information. The LMF 166 receives measurements and assistance information from the NG-RAN and the UE 104 via the AMF 161 to compute the position of the UE 104. The NG-RAN may utilize one ormore positioningmethods in orderto determine the position of the UE 104. Positioningthe UE 104 may involve signal measurements, a position estimate, and an optional velocity computation based on the measurements. The signal measurements may be made by the UE 104 and / or the base station 102 serving the UE 104. The signals measured may be based on one ormore of a satellite positioning system (SPS) 170 (e.g., one or more of a Global Navigation Satellite System (GNSS), global position system (GPS), non-terrestrial network (NTN), or other satellite position / location system), LTE signals, wireless local area network (WLAN) signals, Bluetooth signals, a terrestrial beacon system (TBS), sensor-based information (e.g., barometric pressure sensor, motion sensor), NR enhanced cell ID (NRE-CID) methods, NRsignals(e.g., multi-round trip time (Multi-RTT), DL angle-129025-2434WO01Qualcomm Ref. No. 2405929WO 15of-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.). TheUE 104 may also be referred to as a station, a mobile station, a subscriber station, a mobile unit, a subscriber unit, a wireless unit, a remote unit, a mobile device, a wireless device, a wireless communications device, a remote device, a mobile subscriber station, an access terminal, a mobile terminal, a wireless terminal, a remote terminal, a handset, a user agent, a mobile client, a client, or some other suitable terminology. In some scenarios, the term UE may also apply to one or more companion devices such as in a device constellation arrangement. One or more of these devices may collectively access the network and / or individually access the network.

[0062] Referring again to FIG. 1 , in certain aspects, the UE 104 may have an AI / ML phase measurement component 198 that may be configured to obtain a first indication of a measurement of at least one of a reference signal carrier phase (RSCP) or a reference signal carrier phase difference (RSCPD) for a set of reference signals (RSs) using artificial intelligence (Al) or machine learning (ML) (AI / ML); and transmit a second indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs, where the second indication indicates that at least one of the RSCP or the RSCPD for the set of RSs is obtained using the AI / ML. In certain aspects, the base station 102 may have an AI / ML phase measurement component 199 that may be configured to obtain a first indication of a measurement of at least one of an RSCP or an RSCPD for a set of RSs using AI / ML; and transmit a second indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs, where the second indication indicates that at least one of the RSCP or the RSCPD for the set of RSs is obtained using the AI / ML. In certain aspects, the one or more location servers129025-2434WO01Qualcomm Ref. No. 2405929WO 16168 may have an AI / ML phase measurement configuration component 197 that may be configured to receive, from a wireless device, a measurement of at least one of an RSCP or an RSCPD for a set of RSs; and receive, from the wireless device, an indication indicating that the measurement of at least one of the RSCP or the RSCPD for the set of RSs is obtained using AI / ML.

[0063] FIG. 2 A is a diagram 200 illustrating an example of a first subframe within a 5G R frame structure. FIG. 2B is a diagram 230 illustrating an example of DL channels within a 5G NR subframe. FIG. 2C is a diagram 250 illustrating an example of a second subframe within a 5G NR frame structure. FIG. 2D is a diagram 280 illustrating an example of UL channels within a 5 G NR subframe. The 5 G NR frame structure may be frequency division duplexed (FDD) in which for a particular set of subcarriers (carrier system bandwidth), subframes within the set of subcarriers are dedicated for either DL or UL, or may be time division duplexed (TDD) in which for a particular set of subcarriers (carrier system bandwidth), subframes within the set of subcarriers are dedicated for both DL andUL. In the examples provided by FIGs. 2A, 2C, the 5G NR frame structure is assumed to be TDD, with subframe 4 being configured with slot format 28 (with mostly DL), where D is DL, U is UL, and F is flexible for use between DL / UL, and subframe 3 being configured with slot format 1 (with all UL). While subframes 3, 4 are shown with slot formats 1, 28, respectively, any particular subframe may be configured with any of the various available slot formats 0-61. Slot formats 0, 1 are all DL, UL, respectively. Other slot formats 2-61 include a mix of DL, UL, and flexible symbols. UEs are configured with the slot format (dynamically through DL control information (DCI), or semi- 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. 2 A-2D illustrate a frame structure, and the aspects of the present disclosure may be applicable to other wireless communication technologies, which may have a different frame structure and / or different channels. A frame (10 ms) may be divided into 10 equally sized subframes (1 ms). Each subframe may include one or more time slots. Subframes may also include mini-slots, which may include 7, 4, or 2 symbols. Each slot may include 14 or 12 symbols, depending on whether the cyclic prefix (CP) is normal or extended. For normal CP, each slot may include 14 symbols, and for129025-2434WO01Qualcomm Ref. No. 2405929WO 17extended 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 allowfor 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.Llsi ots / sub frame. The subcarrier spacing may be equal to 2^ * 15 kHz, where . is the numerology 0 to 4. As such, the numerology p=0 has a subcarrier spacing of 15 kHz and the numerology p=4 has a subcarrier spacing of 240 kHz. The symbol length / 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).129025-2434WO01Qualcomm Ref. No. 2405929WO 18

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

[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 a physical layer cell identity group number and radio frame timing. Based on the physical layer identity and the physical layer cell identity group number, the UE can determine a physical cell identifier (PCI). Based on the PCI, the UE can determine the locations of the DM-RS. The physical broadcast channel (PBCH), which carries a master information block (MIB), may be logically grouped with the PSS and SSS to form a synchronization signal (SS) / PBCH block (also referred to as SS block (SSB)). The MIB provides a number of RBs in the system bandwidth and a system frame number (SFN). The physical downlink shared channel (PDSCH) carries user129025-2434WO01Qualcomm Ref. No. 2405929WO 19data, 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 layer 2 functionality. Layer 3 includes a radio resource control (RRC) layer, and layer 2 includes a service data adaptation protocol (SDAP) layer, a packet data convergence protocol (PDCP) layer, a radio link control (RLC) layer, and a medium access control (MAC) layer. The controller / processor 375 provides RRC layer functionality associated with broadcasting of system information (e.g., MIB, SIBs), RRC connection control (e.g., RRC connection paging, RRC connection establishment, RRC connection modification, and RRC connection release), inter radio access technology (RAT) mobility, and measurement configuration forUE measurement129025-2434WO01Qualcomm Ref. No. 2405929WO 20reporting; 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) processors 16 and the receive (RX) processor 370 implement layer 1 functionality associated with various signal processing functions. Layer 1, which includes a physical (PHY) layer, may include error detection on the transport channels, forward error correction (FEC) coding / decoding of the transport channels, interleaving, rate matching, mapping onto physical channels, modulation / demodulation of physical channels, andMIMO antenna processing The TX processor 316 handles mapping to signal constellations based on various modulation schemes (e.g., binary phase-shift keying (BPSK), quadrature phase-shift keying (QPSK), M-phase-shift keying (M-PSK), M-quadrature amplitude modulation (M-QAM)). The coded and modulated symbols may then be split into parallel streams. Each stream may then be mapped to an OFDM subcarrier, multiplexed with a reference signal (e.g., pilot) in the time and / or frequency domain, and then combined together using an Inverse Fast Fourier Transform (IFFT) to produce a physical channel carryingatime domain OFDMsymbol stream. The OFDM stream is spatially precoded to produce multiple spatial streams. Channel estimates from a channel estimator 374 may be used to determine the coding and modulation scheme, as well as for spatial processing. The channel estimate may be derived from a reference signal and / or channel condition feedback transmitted by the UE 350. Each spatial stream may then be provided to a different antenna 320 via a separate transmitter 318Tx. Each transmitter 318Tx may modulate a radio frequency (RF) carrier with a respective spatial stream for transmission.

[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 and129025-2434WO01Qualcomm Ref. No. 2405929WO 21provides the information to the receive (RX) processor 356. The TX processor 368 and the RX processor 356 implement layer 1 functionality associated with various signal processing functions. TheRX processor 356 may perform spatial processing on the information to recover any spatial streams destined 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 b e based on channel estimates computed by the channel estimator 358. The soft decisions are then decoded and deinterleaved to recover the data and control signals that were originally transmitted by the base station 310 on the physical channel. The data and control signals are then provided to the controller / processor 359, which implements layer 3 and layer 2 functionality.

[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 functionality associated with system information (e.g., MIB, SIBs) acquisition, RRC connections, and measurement reporting; PDCP layer functionality associated with header compression / decompression, and security (ciphering, deciphering, integrity protection, integrity verification); RLC layer functionality associated with the transfer of upper layer PDUs, error correction through ARQ, concatenation, segmentation, and reassembly of RLC SDUs, re-segmentation of RLC data PDUs, and reordering of RLC data PDUs; and MAC layer functionality associated with mapping between logical channels and transport channels, multiplexing of MAC SDUs onto TBs,129025-2434WO01Qualcomm Ref. No. 2405929WO 22demultiplexing 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 354 Tx 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 atthe UE 350. Each receiver 318Rx receives a signal through its respective antenna 320. Each receiver 318Rx recovers information modulated onto an RF carrier and provides the information to a RX processor 370.

[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 AI / ML phase measurement component 198 of FIG. 1.

[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 AI / ML phase measurement component 199 of FIG. 1.

[0081] FIG. 4 is a diagram 400 illustrating an example of a UE positioningbased on reference signal measurements (which may also be referred to as “network-based positioning”) in accordance with variousaspectsofthe present disclosure. The UE404 may transmit UL SRS 412 at time TSRS_TX and receive DL positioning reference signals (PRS) (DL PRS) 410 at time TPRSRX- 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 before129025-2434WO01Qualcomm Ref. No. 2405929WO 23receiving the DLPRS 410. In both cases, a positioning server(e.g., location servers) 168) or the UE 404 may determine the RTT 414 based on ||TSRS _RX - TPRSTX| - |TSRS TX - TPRS _RX||- Accordingly, multi-RTT positioning may make use of the UE Rx-Tx time difference measurements (i.e., |TSRS_TX- TPRS_RX|) and DLPRS reference signal received power (RSRP) (DL PRS-RSRP) of downlink signals received from multiple TRPs 402, 406 and measured by the UE 404, and the measured TRP Rx-Tx time difference measurements (i.e., |TSRS_RX - TPRSTX|) and UL SRS-RSRP at multiple TRPs 402, 406 of uplink signals transmitted from UE 404. The UE 404 measures the UE Rx-Tx time difference measurements (and / or DL PRS-RSRP of the received signals) using assistance data received from the positioning server, and the TRPs 402, 406 measure the gNB Rx-Tx time difference measurements (and / or UL SRS-RSRP of the received signals) using assistance data received from the positioning server. The measurements may be used atthe positioning server or the UE 404 to determine the RTT, which is used to estimate the location of the UE 404. Other methods are possible for determining the RTT, such as for example using DL-TDOA and / or UL-TDOA measurements.

[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” 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 referencepointfortheDL PRS- RSRP may be the antenna connector of the UE. For FR2, DL PRS-RSRP may be measured based on the combined signal from antenna elements corresponding to a given receiver branch. ForFRl and FR2, if receiver diversity is in use by the UE, the reported DL PRS-RSRP value may not be lower than the corresponding DL PRS-129025-2434WO01Qualcomm Ref. No. 2405929WO 24RSRP of any of the individual receiver branches. Similarly, UL SRS-RSRP may be defined as linear average of the power contributions (in [W]) of the resource elements carrying sounding reference signals (SRS). UL SRS-RSRP may be measured over the configured resource elements within the considered measurement frequency bandwidth in the configured measurement time occasions. In some examples, for FR1 , the reference point for the UL SRS-RSRP may be the antenna connector of the base station (e.g., gNB). For FR2, UL SRS-RSRP may be measured based on the combined signal from antenna elements correspondingto a given receiver branch. For FR1 and FR2, if receiver diversity is in use by the base station, the reported UL SRS- RSRP value may not be lower than the corresponding UL SRS-RSRP of any of the individual receiver branches.

[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 1 st path delay is the power contribution corresponding to the first detected path in time. In some examples, PRS path Phase measurement may refer to the phase associated with an i- th path of the channel derived using a PRS resource.

[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 other 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 the129025-2434WO01Qualcomm Ref. No. 2405929WO 25received 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-AoApositioningmay make use of the measured azimuth angle of arrival (A-AoA) and zenith angle of arrival (Z-AoA) at multiple TRPs 402, 406 of uplink signals transmitted from the UE 404. The TRPs 402, 406 measure the A-AoA and the Z-AoA of the received signals using assistance data received from the positioning server, and the resulting measurements are used along with other configuration information to estimate the location of the UE 404. For purposes of the present disclosure, a positioning operation in which measurements are provided by a UE to a base station / positioningentity / serverto be used in the computation of theUE’s position may be described as “UE-assisted,” “UE-assisted positioning,” and / or “UE-assisted position calculation,” while a positioning operation in which a UE measures and computes its own position maybe described as“UE-based ,” “UE-based positioning,” and / or “UE-based position calculation.”

[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.

[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 with129025-2434WO01Qualcomm Ref. No. 2405929WO 26“UL” or “DL” to distinguish the direction. For example, “UL-DMRS” may be differentiated from “DL-DMRS.” In addition, the term “location” and “position” may be used interchangeably throughout the specification, which may referto a particular geographical or a relative place.

[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 (DLRSTD)” is the DL relative timing difference between the Transmission Point (TP) j and the reference TP z, defined as TsubframeRxj - TsubframeRxi, where: TsubframeRxj is the time when the UE receives the start of one subframe from TP j. TsubframeRxi is the time when the UE receives the 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 subframe from a TP. For frequency range 1, the reference point for the DL RSTD may be the antenna connector of the UE. For frequency range 2, the reference point for the DL RSTD may be the antenna of the UE.

[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.129025-2434WO01Qualcomm Ref. No. 2405929WO 27

[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 1 st path delay is the power contribution corresponding to the first detected path in time. For frequency range 1 , the reference point for the DL PRS- RSRPP may be the antenna connector of the UE. For frequency range 2, DL PRS- RSRPP may be measured based on the combined signal from antenna elements corresponding to a given receiver branch. For frequency range 1 and 2, if receiver diversity is in use by the UE for DL PRS-RSRPP measurements, the reported DL PRS-RSRPP value included in the higher layer parameter NR-DL-AoD-MeasElement for the first and additional measurements may be provided for the same receiver branch(es) as applied for DL PRS-RSRP measurements

[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 transmission point(TP) j and the reference TPz. If UE reports RSCPD measurements together with RSTD measurements in a measurement report element, the reference TP for RSCPD is the same as the reference TP reported for RSTD. For frequency range 1, the reference point for the DL RSCPD may be the antenna connector of the UE. For frequency range 2, the reference point for the DL RSCPD may be the antenna of the UE.

[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)129025-2434WO01Qualcomm Ref. No. 2405929WO 28fingerprinting, 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 performingpositioningrelated 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 anLMF, determines the position for the UEbased on the positioningmeasurements 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, networkbased 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, an129025-2434WO01Qualcomm Ref. No. 2405929WO 29“AI / ML functionality” may refer to employing AI / ML to positioning without referringto 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 outputmay referto a specific measurementtype / location information and / or quantity. The one or more model(s) can be logical or physical. Depending on the context, sometimes the term “AI / ML model” may be used interchangeably with the term “AI / ML functionality.”

[0100] FIG. 5 A 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.

[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., aUE, a network entity / node such as abase station, etc.) may use at least one AI / ML model to assistthe measurement of reference signals (e.g., positioningreference signals such as PRS, SRS, etc.). Then, the entity / node may transmit the reference signal measurements to a location server, such as an LMF. In response, the location server may determine the position of 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-129025-2434WO01Qualcomm Ref. No. 2405929WO 30sight (LOS) condition ora 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 withoutusing 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 NthTRP), and measure the channel impulse response (CIR) for the set of positioning reference signals from each TRP. Then, theUE 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 second TRP is input to an AI / ML model A associated with the second TRP, and CIR of the NthTRP is input to an AI / ML model A associated with the NthTRP, 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 BQ 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 B2that is different from AI / ML Model BQ for inferring the ToA of the second TRP, and CIR of the NthTRP may be input to an NthAI / ML model (e.g., AI / ML Model BNthat 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 TRPs129025-2434WO01Qualcomm Ref. No. 2405929WO 31may be input to one AI / ML model(e.g., AI / ML Model C), andthe AI / ML modelmay inferthe 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-side AI / ML model, direct AI / ML or AI / ML assisted positioning in accordance with various aspects of the present disclosure. In one implementation, a UE 702 may be associated with at least one AI / ML model 708, and the UE 702 may use the at least one AI / ML model 708 to perform the direct AI / ML positioning and / or the assisted AI / ML positioning based on downlink (DL) reference signals, such as positioning reference signals (PRSs). For example, the UE 702 may receive and measure a set of PRSs transmitted from a base station 706, 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 measurements)” and / or “PRS-based measurement(s).” In some examples, the UE 702 may use the at least one AI / ML model 708 for measuring the set of PRSs (e.g., for assisted AI / ML positioning). In some examples, based on the PRS measurement(s), the UE 702 may use the at least one AI / ML model 708 for determining its position (e.g., for direct AI / ML positioning). Note in this assisted AI / ML positioning example, the UE 702 may use the at least one AI / ML model 708 for performing PRS measurements, and the UE 702 may determine its position based on the PRS measurements without the assistance of an AI / ML model.

[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).” Then, the UE 702 may transmit the PRS-based measurement(s) to a location server 704, such as an LMF. In129025-2434WO01Qualcomm Ref. No. 2405929WO 32response, 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 900 A 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 abase station 706, may be associated with atleastone AI / ML model 708, and the base station 706 may use the at least one AI / ML model 708 to assist measurement(s) of uplink (UL) reference signals, such as sounding reference signals (SRSs). For example, the UE 702 may transmit a set of SRSs to the b ase 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 atleastone 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 measurethe set of SRSs. Then, the base station 706 may transmit the SRS-based measurement(s) to the location server 704,129025-2434WO01Qualcomm Ref. No. 2405929WO 33such 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, 8 A, and 8B may be referred to as AI / ML positioningbased on DL reference signals, and positioning described in connection with FIGs. 9 A 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.Table 2 - Example of supported UE positioning methods

[0111] In some implementations, for direct AI / ML positioningas described in connection with FIGs. 8B and 9B, type(s) of measurement(s) that may be used as129025-2434WO01Qualcomm Ref. No. 2405929WO 34(suitable / potential) input for AI / ML model inference consideringperformance impact and associated signaling overhead may include channel impulse response (CIR), power delay profile (PDP), reference signal receive power (RSRP), reference signal received path power (RSRPP), and / or reference signal time difference (RSTD), etc. For AI / ML assisted positioning with UE-assisted and network node-assisted positioning described in connection with FIGs. 8 A and 9 A, respectively, measurement report to carry AI / ML model (suitable / potential) output to a location server such as an LMF may include ToA, path phase, RSTD, line-of-sight(LOS) / non-line-of-sight (NLOS) indicator, RSRPP, and / or soft inf ormation / high resolution of RSTD, etc. In some examples, AI / ML model inference output that may provide performance benefits may include timing estimation (note the report to LMF may be derived based on and maybe different from the model inference output) and / or LOS / NLOS indicator.

[0112] In the context of positioning and localization, phase-based / carrier phase positioning may refer to a process of determining the position of a target (e.g., a UE) based on measuring the phase or the phase difference between signals received from multiple sources or transmitted to multiple receivers (which may collectively be referred to as the “phase measurement(s)” or “carrier phase measurement(s)” hereafter). These phase measurements may typically be used in systems like GNSS, Wi-Fi positioning ultrawide band (UWB), and other wireless-based positioning technologies. A fundamental idea behind phase measurements in positioning is that the phase of a signal may provide highly accurate information about the distance between a transmitter and a receiver. As the phase of a signal is directly related to the distance the signal has traveled, phase measurements may be used to compute the position of a target relative to known reference points (e.g., satellites, base stations, or access points).

[0113] Table 3 below provides an example definition for downlink (DL) reference signal carrier phase (DL RSCP).129025-2434WO01Qualcomm Ref. No. 2405929WO 35Table 3 - Example definition for DL RSCP

[0114] Table 4 below provides an example definition for DL reference signal carrier phase difference (DL RSCPD).Table 4 - Example definition for DL RSCPD

[0115] Table 5 below provides an example definition for uplink (UL) reference signal carrier phase (UL RSCP).129025-2434WO01Qualcomm Ref. No. 2405929WO 36Table 5 - Example definition for UL RSCP

[0116] Table 6 below provides an example definition for synchronization signals (SS) reference signal antenna relative phase (SS-RSARP).129025-2434WO01Qualcomm Ref. No. 2405929WO 37Table 6 - Example definition for SS-RSARP

[0117] Table 7 below provides example phase measurements for various positioning methods.129025-2434WO01Qualcomm Ref. No. 2405929WO 38129025-2434WO01Qualcomm Ref. No. 2405929WO 39

[0118] AI / ML positioning has shown to provide an excellent positioning accuracy in stringent non-line-of-sight (NLOS) conditions compared to non-AI / ML positioning Carrier phase positioning (e.g., positioning with carrier phase method(s)) has also shown excellent performance, but may specify line-of-sight (LOS) conditions and proper phase calibration for ensuring excellent positioning accuracy. As phase information may be a function of reflections, diffractions, refractions, and / or scatteringof underlyingenvironment(includingtheirmaterialtype), AI / MLmay have the capability to enhance carrier phase positioning by learning mapping between multipath information (including phase ofthe multipath) anduseful phase information for positioning.

[0119] Aspects presented herein may improve the overall performance and efficiency of AI / ML positioningrelated operations (e.g., training, inferencing, data collection, etc.) by enabling phase-based AI / ML assisted positioning. For example, aspects presented herein may enable a UE or a network entity to adopt an AI / ML assisted approach to learn and provide enhanced phase measurements to be used for positioning. Aspects presented herein provide AI / ML model input and / or output design and related signaling for the phase-based AI / ML assisted positioning. Aspects presented herein also provide various reporting related to the phase-based AI / ML assisted positioning129025-2434WO01Qualcomm Ref. No. 2405929WO 40which may include reporting for AI / ML model measurements, material information of surrounding area, and / or phase error information, etc.

[0120] FIG. 10 is a diagram 1000 illustrating an example of inferencing phase measurement(s) and quality of the phase measurement(s) in accordance with various aspects of the present disclosure. As discussed in connection with FIGs. 5B, 8 A, and 9A, for UE-side assisted positioning or base station-side positioning, a UE / base station (e.g., the UE 702 or the base station 706) may be configured to perform reference signal (RS) measurement(s) using at least one AI / ML model (e.g., the at least one AI / ML model 708), and then provide the RS measurement(s) (which may be referred to as the “intermediate measurement(s)”) to a location server (e.g., the location server 704). Based on the intermediate measurement(s), the location server may derive the location of the UE.

[0121] For example, as shown at 1010, a set of measurements associated with one or more TRP(s) may be used as an inputfor an AI / ML model 1002. The set of measurements associated with one or more TRP(s) may refer to the measurement(s) performed by one or more TRPs based on SRS(s) transmitted from aUE, and / orthe measurements) performed by a UE based on PRS(s) transmitted from one or more TRPs, etc. In addition, the AI / ML model 1002 may be a logical AI / ML model, a physical AI / ML model, an AI / ML functionality, or a combination thereof.

[0122] As shown at 1012, based on the set of measurements, the AI / ML model 1002 may be configured to output a set of phase measurements of one TRP / PRS resource / SRS resource or multiple (e.g., N) TRPs / PRS resources / SRS resources, etc. In some implementations, as shown at 1014, the AI / ML model 1002 may also be configured to provide an indication of the quality of the set of phase measurements. For purposes of the present disclosure, AI / ML assisted positioning that provides phase measurements may be referred to as “phase-based AI / ML assisted positioning.”

[0123] FIG. 11 is a communication flow 1100 illustrating an example phase-based AI / ML assisted positioning between a UE and a location server in accordance with various aspects of the present disclosure. The numberings associated with the communication flow 1100 do not specify a particular temporal order and are merely used as references for the communication flow 1100.

[0124] At 1110, a UE 1102 (which may also be a positioning reference unit (PRU)) may receive, from a network entity 1106, a set of RSs, such as a set of downlink (DL) RSs129025-2434WO01Qualcomm Ref. No. 2405929WO 41(DL-RSs) (e.g., PRSs). For example, the UE 1102 may receive the set of RSs from a TRP of abase station, from multiple TRPs of the base station, and / or from atleast one TRP of each of multiple base stations, etc.

[0125] At 1112, based on the received set of RSs, the UE 1102 may measure the set of RSs and obtain measurement(s) of a reference signal carrier phase (RSCP) or a reference signal carrier phase difference (RSCPD)forthe set of RSs using AI / ML (e.g., using at least one physical AI / ML model, at least one logical AI / ML model, and / or at least one AI / ML functionality, etc.). For illustration and differentiation purposes, the measurement(s) may collectively be referred to as DL-RSCP / RSCPD measurement(s). In some examples, the UE 1102 may also receive the RS measurement(s) from another entity (e.g., from another UE), and derive the DL- RSCP / RSCPD measurement(s) from the received RS measurement(s) using the AI / ML.

[0126] For example, as shown at 1114, the UE 1102 may be configured to provide a set of AI / ML input 1116 to the AI / ML to obtain a set of AI / ML output 1118. Depending on implementations, the set of AI / ML input 1116 may include DL measurements) between the UE 1102 and the network entity 1106, such as between the UE 1102 and at least one TRP, between a neighboring PRU and at least one TRP, and / or phase measurement(s) from a neighboring PRU, etc.), and the DL measurement(s) (or RS measurement(s)) may include channel frequency response (CFR) measurement(s), channel impulse response (CIR) measurement(s), power delay profile (PDP) measurement(s), delay profile (DP) measurement(s), sample-based measurements) (e.g., corresponding sample measurement(s) may be timing, power, and / or phase of time-domain channel response) (it may also be truncated and / or sub sampled)), pathbased measurement(s) (e.g., corresponding path measurement(s) may be timing power, and / or phase of time-domain channel response), or a combination thereof.

[0127] In some implementations, the set of AI / ML input 1116 may also include other information in addition to the DL measurements, such as material information of surrounding environment (e.g., environment information such as in a forest, in an indoor area with walls, at a place with furniture, etc.), phase error / calib ration information at a transmitter / transmission (TX) side, and / or phase error / calibration information atareceiver / reception(RX) side. In addition, the set of AI / ML input 1116 (or the AI / ML model input construction) may include measurement(s) for / from a129025-2434WO01Qualcomm Ref. No. 2405929WO 42single TRP, measurement(s) for / from multiple TRPs, or measurement(s) for / from a single TRP with N AI / ML models for N TRPs, such as described in connection with FIG. 6.

[0128] The set of AI / ML output 1118 (e.g., the DL-RSCP / RSCPD measurement(s)) may be configured to include an RSCP of carrier, an RSCPD of carrier, an RSCP of a first path arrival, an RSCPD of a first path arrival, an RSCP of an Nthpath, an RSCPD of an Nthpath, or a combination thereof. Note the phase measurements / information described herein may be configuredto be integer multiple of wavelength cycles and / or fractional wavelength. As discussed in connection with 1014 of FIG. 10 and 1120 of FIG. 11, the set of AI / ML output 1118 may also include the quality of the phase measurement^. g., the quality of the DL-RSCP / RSCPD measurement(s)), which may be based on the request from a location server 1104. Similarly, the set of AI / ML output 1118 (or the AI / ML model output construction) may include phase measurement(s) of a single TRP, a single RS resource, or a single RS resource set, or phase measurement(s) multiple TRPs, multiple RS resources, or multiple RS resource sets, etc.

[0129] As DL-RSCP / RSCPD measurement(s) may include measurements of phase differences between two phases, there may be various options for phase referencing (for the set of AI / ML output 1118). For example, the DL-RSCP / RSCPD measurement(s) may be configured to include at least one of:(1) a phase difference / reference with respect to a phase corresponding to RS from a reference TRP,(2) a phase difference / reference with respect to a phase corresponding to RS (e.g., SSB / CSLRS) from a serving cell,(3) a phase difference / reference with respect to a phase corresponding to RS from another beam or PRS / SRS resource,(4) a phase difference / reference with respect to a phase corresponding to RS from another beam or PRS / SRS resource in another beam / resource set, (5) a phase difference / reference with respect to a phase corresponding to RS from another beam or PRS / SRS resource in another beam / resource set in another PFL (or frequency carrier / frequency band / frequency subband, etc.), (6) a phase difference / reference with respect to a phase corresponding to RS sent earlier (e.g., a UE Tx-Rx phase difference or a gNB Tx-Rx phase difference),129025-2434WO01Qualcomm Ref. No. 2405929WO 43(7) a phase difference / reference with respect to a phase corresponding to RS’s first path, or(8) a phase difference / reference with respect to a phase corresponding to RS’s strongest path.

[0130] At 1120, the UE 1102 may transmit, to a location server 1104, the DL-RSCP / RSCPD measurement(s) and an indication that the DL-RSCP / RSCPD measurement(s) are obtained using AI / ML. Depending on implementations, the UE 1102 may also be configured to provide the quality of the DL-RSCP / RSCPD measurement(s). For example, the report for the DL-RSCP / RSCPD measurement(s) may include a quality field or information element (IE) that describes the likelihood, probability, and / or confidence of the DL-RSCP / RSCPD measurement(s). In addition, the UE 1102 may obtain the quality of the DL-RSCP / RSCPD measurement(s) using an AI / ML model (output) or using a non-AI / ML technique. The location server 1104 may be a location management function (LMF), a sensing management function, or an AI / ML management function, etc.).

[0131] In some implementations, the UE 1102 may also be configured to obtain additional DL-RSCP / RSCPD measurement(s) without using the AI / ML, such as for AI / ML model training or comparison purposes. In such cases, at 1120, the UE 1102 may also transmitthe additional DL-RSCP / RSCPD measurement(s) to the location server 1104 with an indication thatthe additional DL-RSCP / RSCPD measurement(s) are obtained without using AI / ML.

[0132] In another example, the measurement(s) of DL-RSCP / RSCPD using AI / ML may be based on a request from the location server 1104 (e.g., the measurement(s) are configured to be “on-demand”). For example, as shown at 1122, the location server 1104 may transmit, to the UE 1102, a request to measure DL-RSCP / RSCPD of RSs using AI / ML. In response, at 1112, the UE 1102 may measure the DL-RSCP / RSCPD of the set of RSs using the AI / ML. In addition, the location server 1104 may also request the UE 1102 to provide the quality of the DL-RSCP / RSCPD measurement(s), and in response, the UE 1102 may include the quality of the DL-RSCP / RSCPD measurement(s) when providing the DL-RSCP / RSCPD measurement(s) at 1120.

[0133] In some implementations, as shown at 1124, the UE 1102 may be configured to provide its capabilities related to phase measurements to the location server 1104, such as capabilities related to the support of phase measurements using AI / ML,129025-2434WO01Qualcomm Ref. No. 2405929WO 44capabilities related to the support of phase measurements types (e.g., RSCP, RSCPD ofDL / SL / UL) using AI / ML, capabilities related to the support of phase AI / ML model output construction (e.g., the number of phase measurements, the maximum number of TRPs, the maximum number of PRS resources, etc.) using AI / ML, and / or capabilities related to the support of phase AI / ML model input construction (e.g., the number of phase measurements, the maximum number of TRPs, the maximum number of PRS resources, etc.) using AI / ML, etc. Then, based on the capabilities of the UE 1102 related to phase measurements, the location server 1104 may request the UE 1102 to provide phase measurements supported by the UE 1102 (e.g., via the request at 1122).

[0134] In some implementations, as shown at 1126, the location server 1104 may be configured to provide assistance data (AD) or assistance information related to phase measurements to the UE 1102, such as assistance on RS configurations (e.g., configurations for receiving the setofRSs), assistance on material information, (e.g, for the set of AI / ML input 1116 as discussed at 1114), assistance on phase error / calibration indicators corresponding to TX side (e.g., for the set of AI / ML input 1116 as discussed at 1114), and / or assistance on phase error / calibration indicators correspondingto RX side (e.g., forthe set of AI / ML input 1116 as discussed at 1114), etc.

[0135] Depending on implementations, the communication(s) between the UE 1102 and the location server 1104 / network entity 1106 may be based on LTE Positioning Protocol (LPP), NR Positioning Protocol A (NRPPa), and / or sidelink (SL) LPP (SL-LPP). For example, dedicated signaling / messages may be configured for the UE 1102, the location server 1104, and / or the network entity 1106 for transmitting the signal / information discussed in connection with 1110, 1120, 1122, 1124, and 1126.

[0136] At 1128, based on the DL-RSCP / RSCPD measurement(s) from the UE 1102 and the indication that the DL-RSCP / RSCPD measurement(s) are obtained with AI / ML, the location server 1104 may determine the location of the UE 1102, which may include prioritizing on using the DL-RSCP / RSCPD measurement(s) obtained with AI / ML as they are likely to provide better accuracy, or giving a higher weight to the location of the UE 1102 estimated from the DL-RSCP / RSCPD measurement(s) obtained with AI / ML, etc.129025-2434WO01Qualcomm Ref. No. 2405929WO 45

[0137] In some scenarios, the UE 1102, subject to its UE capability, may be requested (e.g, by the location server 1104) to perform DL-RSCPD and / or DL-RSCP measurements on indicated DL PRS resource sets occurring within one or two time window(s) indicated by a DL PRS measurement time window configuration parameter (e.g., NR- DL-PRS-MeasurementTimeWindowsConfig). Within each window indicated by this parameter, the UE 1102 may expect that the indicated DL PRS resource sets across all DL PRS IDs (e.g., dl-PRS-IDs) are from one DL PRS positioning frequency layer, and that the number of indicated DL PRS resource sets associated with each DL PRS ID are the same. Similarly, the UE 1102, subject to its UE capability, may be requested to perform DL RSTD, UE Rx - Tx time difference, DL PRS-RSRP, and DL PRS-RSRPP measurement on the indicated DL PRS resource sets just within the window(s) indicated by a DL PRS measurement time window configuration parameter (e.g., NR-DL-PRS-MeasurementTimeWindow sConfig). Otherwise, the UE 1102 may use the indicated DL PRS resource set(s) occurring outside the indicated time window for these measurements in addition to the indicated DL PRS resource set(s) occurring inside the indicated time window(s).

[0138] As such, in another aspect of the present disclosure, the UE 1102 may be configured to derive / obtain the DL-RSCP / RSCPD measurement(s) based on:(1) just using a conventional (non-AI / ML) method to derive / obtain the DL- RSCP / RSCPD measurement(s) if the set of RSs is within an indicated time window,(2) just using AI / ML to derive / obtain the DL-RSCP / RSCPD measurement(s) if the set of RSs is within an indicated time window,(3) usinga conventional (non-AI / ML) method and / or AI / ML to derive / obtain the DL- RSCP / RSCPD measurement(s) if the set of RSs is within an indicated time window,(4) just using a conventional (non-AI / ML) method to derive / obtain the DL- RSCP / RSCPD measurement(s) if the set of RSs is outside of an indicated time window,(5) just using AI / ML to derive / obtain the DL-RSCP / RSCPD measurement(s) if the set of RSs is outside of an indicated time window, and / or129025-2434WO01Qualcomm Ref. No. 2405929WO 46(6) using a conventional (non- AI / ML) method and / or AI / ML to derive / obtain the DL- RSCP / RSCPD measurement(s) if the set of RSs is outside of an indicated time window.

[0139] In some scenarios, the UE 1102, the UE 1102 may be provided with positioning reference unit (PRU) information (e.g., via an IE nr-PruInformation-Ue-based-DLr CPP) which may contain DL-RSCP / RSCPD measurements together with DL RSTD, DL PRS-RSRP, and / or DL PRS-RSRPP measurement(s) associated with the RSCP / RSCPD measurements performed by a PRU, the timestamps associated with the measurements, and / or the location information of the PRU, etc. As such, in another aspect of the present disclosure, when a PRU performs carrier phase (CP) measurements based on AI / ML, the PRU may inform the location server 1104 (e.g, an LMF) about it, and the location server 1104 may forward that information to the UE 1102. In other words, the assistance data that the UE 1102 receives (e.g., at 1126) may include the carrier phase positioning (CPP) measurement(s) from another UE (e.g., PRU), and may also include an indication / flag that the phase measurements are AI / ML-based or not (e.g., obtained based on AI / ML). Similarly, the UE 1102 may be configured with the capability to request such assistance data (e.g., CPP measurements from another UE that is AI / ML-based or non-AI / ML based).

[0140] FIG. 12 is a communication flow 1200 illustrating an example phase-based AI / ML assisted positioningbetween a network entity and a location server 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.

[0141] At 1210, a network entity 1206 (e.g., a base station, a TRP of the base station, multipole TRPs of the base station, etc.) may receive, from a UE 1202 (which may be a PRU), a set of RSs, such as a set of uplink (UL) RSs (UL-RSs) (e.g., SRSs).

[0142] At 1212, based on the received set of RSs, the network entity 1206 may measure the set of RSs and obtain measurement(s) of an RSCP or an RSCPD for the set of RSs using AI / ML (e.g., using at least one physical AI / ML model, at least one logical AI / ML model, and / or at least one AI / ML functionality, etc.). For illustration and differentiation purposes, the measurement(s) may collectively be referred to as UL- RSCP / RSCPD measurement(s). In some examples, the network entity 1206 may also receive the RS measurement(s) from another entity (e.g., from another base station or129025-2434WO01Qualcomm Ref. No. 2405929WO 47TRP), and derive the UL-RSCP / RSCPD measurement(s) from the received RS measurement(s) using the AI / ML.

[0143] For example, as shown at 1214, the network entity 1206 maybe configured to provide a set of AI / ML input 1216 to the AI / ML to obtain a set of AI / ML output 1218. Depending on implementations, the set of AI / ML input 1216 may include UL measurement(s) between the network entity 1206 and the UE 1202, such as between at least one TRP and the UE 1202, and / or between at least one TRP and a PRU, etc.), and the UL measurement(s) (or RS measurement(s)) may include CFR measurement(s), CIR measurement(s), PDP measurement(s), DP measurements), sample-based measurement(s) (e.g., corresponding sample measurement(s) may be timing, power, and / or phase of time-domain channel response) (it may also be truncated and / or subsampled)), path-based measurement(s) (e.g., corresponding path measurement(s) may be timing, power, and / or phase of time-domain channel response), or a combination thereof.

[0144] In some implementations, the set of AI / ML input 1216 may also include other information in addition to the UL measurements, such as material information of surrounding environment (e.g., environment information such as in a forest, in an indoor area with walls, at a place with furniture, etc.), phase error / calib ration information at a TX side, and / or phase error / calibration information at an RX side. In addition, the set of AI / ML input 1216 (or the AI / ML model input construction) may include measurement(s) for / from a single TRP, measurement(s) for / from multiple TRPs, or measurement(s) for / from a single TRP with N AI / ML models for N TRPs, such as described in connection with FIG. 6.

[0145] The set of AI / ML output 1218 (e.g., the UL-RSCP / RSCPD measurement(s)) maybe configured to include an RSCP of carrier, an RSCPD of carrier, an RSCP of a first path arrival, an RSCPD of a first path arrival, an RSCP of an Nthpath, an RSCPD of an Nthpath, or a combination thereof. Note the phase measurements / information described herein may be configuredto be integer multiple of wavelength cycles and / or fractional wavelength. As discussed in connection with 1014 of FIG. 10 and 1220 of FIG. 12, the set of AI / ML output 1218 may also include the quality of the phase measurement^. g., the quality of the UL-RSCP / RSCPD measurement(s)), which may be based on the request from a location server 1204.129025-2434WO01Qualcomm Ref. No. 2405929WO 48

[0146] As UL-RSCP / RSCPD measurement(s) may include measurements of phase differences between two phases, there may be various options for phase referencing (for the set of AI / ML output 1218). For example, the UL-RSCP / RSCPD measurement(s) may be configured to include at least one of:(1) a phase difference / reference with respect to a phase corresponding to RS from a reference TRP,(2) a phase difference / reference with respect to a phase corresponding to RS (e.g., SSB / CSLRS) from a serving cell,(3) a phase difference / reference with respect to a phase corresponding to RS from another beam or PRS / SRS resource,(4) a phase difference / reference with respect to a phase corresponding to RS from another beam or PRS / SRS resource in another beam / resource set, (5) a phase difference / reference with respect to a phase corresponding to RS from another beam or PRS / SRS resource in another beam / resource set in another PFL (or frequency carrier / frequency band / frequency subband, etc.), (6) a phase difference / reference with respect to a phase corresponding to RS sent earlier (e.g., a UE Tx-Rx phase difference or a gNB Tx-Rx phase difference), (7) a phase difference / reference with respect to a phase corresponding to RS’s first path, or(8) a phase difference / reference with respect to a phase corresponding to RS’s strongest path.

[0147] At 1220, the network entity 1206 may transmit, to a location server 1204, the UL- RSCP / RSCPD measurement(s) and an indication that the UL-RSCP / RSCPD measurement(s) are obtained using AI / ML. Depending on implementations, the network entity 1206 may also be configured to provide the quality of the UL- RSCP / RSCPD measurement(s). For example, the report for the UL-RSCP / RSCPD measurement(s) may include a quality field or IE that describes the likelihood, probability, and / or confidence of the UL-RSCP / RSCPD measurement(s). In addition, the network entity 1206 may obtain the quality of the UL-RSCP / RSCPD measurement(s) using an AI / ML model (output) or using a non-AI / ML technique. The location server 1204 may be an LMF, a sensing management function, or an AI / ML management function, etc.129025-2434WO01Qualcomm Ref. No. 2405929WO 49

[0148] In some implementations, the network entity 1206 may also be configured to obtain additional UL-RSCP / RSCPD measurement(s) without using the AI / ML, such as for AI / ML model training or comparison purposes. In such cases, at 1220, the network entity 1206 may also transmit the additional UL-RSCP / RSCPD measurement(s) to the location server 1204 with an indication that the additional UL-RSCP / RSCPD measurement(s) are obtained without using AI / ML.

[0149] In another example, the measurement(s) of UL-RSCP / RSCPD using AI / ML may be based on a request from the location server 1204 (e.g., the measurement(s) are configured to be “on-demand”). For example, as shown at 1222, the location server 1204 may transmit, to the network entity 1206, a request to measure UL- RSCP / RSCPD of RSs using AI / ML. In response, at 1212, the network entity 1206 may measure the UL-RSCP / RSCPD of the set of RSs using the AI / ML. In addition, the location server 1204 may also request the network entity 1206 to provide the quality of the UL-RSCP / RSCPD measurement(s), and in response, the network entity 1206 may include the quality of the UL-RSCP / RSCPD measurement(s) when providing the UL-RSCP / RSCPD measurement(s) at 1220.

[0150] In some implementations, as shown at 1224, the network entity 1206 may be configured to provide its capabilities related to phase measurements to the location server 1204, such as capabilities related to the support of phase measurements using AI / ML, capabilities related to the support of phase measurements types (e.g., RSCP, RSCPD of DL / SL / UL) using AI / ML, capabilities related to the support of phase AI / ML model output construction (e.g., the number of phase measurements, the maximum number of SRS resources, etc.) using AI / ML, and / or capabilities related to the support of phase AI / ML model input construction (e.g., the number of phase measurements, the maximum number of SRS resources, etc.) using AI / ML, etc. Then, based on the capabilities of the network entity 1206 related to phase measurements, the location server 1204 may request the network entity 1206 to provide phase measurements supported by the network entity 1206 (e.g., via the request at 1222).

[0151] In some implementations, as shown at 1226, the location server 1204 may be configured to provide assistance data or assistance information related to phase measurements to the network entity 1206, such as assistance on RS configurations (e.g., configurations for receiving the set of RSs), assistance on material information, (e.g., for the set of AI / ML input 1216 as discussed at 1214), assistance on phase129025-2434WO01Qualcomm Ref. No. 2405929WO 50error / calibration indicators corresponding to TX side (e.g., for the set of AI / ML input 1216 as discussed at 1214), and / or assistance on phase error / calibration indicators correspondingto RX side (e.g., for the set of AI / ML input 1216 as discussed at 1214), etc.

[0152] Depending on implementations, the communication(s) between the network entity 1206 and the location server 1204 / the UE 1202 may be based on LPP, NRPPa, and / or SL-LPP. For example, dedicated signaling / messages may be configured for the network entity 1206, the location server 1204, and / orthe UE 1202 for transmitting the signaling / information discussed in connection with 1210, 1220, 1222, 1224, and 1226.

[0153] At 1228, based on the UL-RSCP / RSCPD measurement(s) from the network entity 1206 and the indication that the UL-RSCP / RSCPD measurement(s) are obtained with AI / ML, the location server 1204 may determine the location of the UE 1202, which may include prioritizing on using the UL-RSCP / RSCPD measurement(s) obtained with AI / ML as they are likely to provide better accuracy, or giving a higher weight to the location of the UE 1202 estimated from the UL-RSCP / RSCPD measurements) obtained with AI / ML, etc.

[0154] Similarly, in some implementations, the network entity 1206 may be configured to derive / obtain the UL-RSCP / RSCPD measurement(s) based on:(1) just using a conventional (non-AI / ML) method to derive / obtain the UL- RSCP / RSCPD measurement(s) if the set of RSs is within an indicated time window,(2) just using AI / ML to derive / obtain the UL-RSCP / RSCPD measurement(s) if the set of RSs is within an indicated time window,(3)usinga conventional (non-AI / ML) method and / or AI / ML to derive / obtain the UL- RSCP / RSCPD measurement(s) if the set of RSs is within an indicated time window,(4) just using a conventional (non-AI / ML) method to derive / obtain the UL- RSCP / RSCPD measurement(s) if the set of RSs is outside of an indicated time window,(5) just using AI / ML to derive / obtain the UL-RSCP / RSCPD measurement(s) if the set of RSs is outside of an indicated time window, and / or129025-2434WO01Qualcomm Ref. No. 2405929WO 51(6) using a conventional (non- AI / ML) method and / or AI / ML to derive / obtain the UL- RSCP / RSCPD measurement(s) if the set of RSs is outside of an indicated time window.

[0155] FIG. 13 is a communication flow 1300 illustrating an example phase-based AI / ML assisted positioning between a sidelink UE and a location server in accordance with various aspects of the present disclosure. The numberings associated with the communication flow 1300 do not specify a particular temporal order and are merely used as references for the communication flow 1300.

[0156] At 1310, a first UE 1302 (e.g., a first sidelink device, a firstPRU, etc.) may receive, from a second UE 1306 (e.g., a second sidelink device, a second PRU, etc.), a set of RSs, such as a set of sidelink (SL) RSs (SL-RSs).

[0157] At 1312, based on the received set of RSs, the first UE 1302 may measure the set of RSs and obtain measurement(s) of an RSCP or an RSCPD for the set of RSs using AI / ML (e.g., using at least one physical AI / ML model, at least one logical AI / ML model, and / or at least one AI / ML functionality, etc.). For illustration and differentiation purposes, the measurement(s) may collectively be referred to as SL- RSCP / RSCPD measurement(s). In some examples, the first UE 1302 may also receive the RS measurement(s) from another entity (e.g., from another base station or TRP), and derive the SL-RSCP / RSCPD measurement(s) from the received RS measurement(s) using the AI / ML.

[0158] For example, as shown at 1314, the first UE 1302 maybe configured to provide a set of AI / ML input 1316 to the AI / ML to obtain a set of AI / ML output 1318. Depending on implementations, the set of AI / ML input 1316 may include SL measurements) between the first UE 1302 and the second UE 1306 or between the first UE 1302 and a neighboring PRU, or SL measurement(s) from a neighboring PRU, etc., and the SL measurement(s) (or RS measurement(s)) may include CFR measurement(s), CIR measurement(s), PDP measurement(s), DP measurement(s), sample-based measurement(s) (e.g., corresponding sample measurement(s) may be timing, power, and / or phase of time-domain channel response) (it may also be truncated and / or subsampled)), path-based measurement(s) (e.g., corresponding path measurements) may be timing, power, and / or phase of time-domain channel response), or a combination thereof.129025-2434WO01Qualcomm Ref. No. 2405929WO 52

[0159] In some implementations, the set of AI / ML input 1316 may also include other information in addition to the SL measurements, such as material information of surrounding environment (e.g., environment information such as in a forest, in an indoor area with walls, at a place with furniture, etc.), phase error / calibration information at a TX side, and / or phase error / calibration information at an RX side. In addition, the set of AI / ML input 1316 (or the AI / ML model input construction) may include measuremen t(s) for / from a single UE, measurement(s) for / from multiple UEs, or measurement(s) for / from a single UE with N AI / ML models for N UEs.

[0160] The set of AI / ML output 1318 (e.g., the SL-RSCP / RSCPD measurement(s)) may be configured to include an RSCP of carrier, an RSCPD of carrier, an RSCP of a first path arrival, an RSCPD of a first path arrival, an RSCP of an Nthpath, an RSCPD of an Nthpath, or a combination thereof. Note the phase measurements / information described herein may be configuredto be integer multiple of wavelength cycles and / or fractional wavelength. As discussed in connection with 1014 of FIG. 10 and 1320 of FIG. 13, the set of AI / ML output 1318 may also include the quality of the phase measurement (e.g., the quality of the SL-RSCP / RSCPD measurement(s)), which may be based on the request from a location server 1304.

[0161] As SL-RSCP / RSCPD measurement(s) may include measurements of phase differences between two phases, there may be various options for phase referencing (for the set of AI / ML output 1318). For example, the SL-RSCP / RSCPD measurement(s) may be configured to include at least one of:(1) a phase difference / reference with respect to a phase corresponding to RS from a reference TRP,(2) a phase difference / reference with respect to a phase corresponding to RS (e.g., SSB / CSLRS) from a serving cell,(3) a phase difference / reference with respect to a phase corresponding to RS from another beam or PRS / SRS resource,(4) a phase difference / reference with respect to a phase corresponding to RS from another beam or PRS / SRS resource in another beam / resource set, (5) a phase difference / reference with respect to a phase corresponding to RS from another beam or PRS / SRS resource in another beam / resource set in another PFL (or frequency carrier / frequency band / frequency subband, etc.),129025-2434WO01Qualcomm Ref. No. 2405929WO 53(6) a phase difference / reference with respect to a phase corresponding to RS sent earlier (e.g., a UE Tx-Rx phase difference or a gNB Tx-Rx phase difference), (7) a phase difference / reference with respect to a phase corresponding to RS’s first path, or(8) a phase difference / reference with respect to a phase corresponding to RS’s strongest path.

[0162] At 1320, the first UE 1302 may transmit, to a location server 1304, the SL- RSCP / RSCPD measurement(s) and an indication that the SL-RSCP / RSCPD measurement(s) are obtained using AI / ML. Depending on implementations, the first UE 1302 may also be configured to provide the quality of the SL-RSCP / RSCPD measurement(s). For example, the report for the SL-RSCP / RSCPD measurements) may include a quality field or IE that describes the likelihood, probability, and / or confidence of the SL-RSCP / RSCPD measurement(s). In addition, the first UE 1302 may obtain the quality of the SL-RSCP / RSCPD measurement(s) using an AI / ML model (output) or using a non-AI / ML technique. The location server 1304 may be an LMF, a sensing management function, or an AI / ML management function, etc.

[0163] In some implementations, the first UE 1302 may also be configured to obtain additional SL-RSCP / RSCPD measurement(s) without using the AI / ML, such as for AI / ML model training or comparison purposes. In such cases, at 1320, the first UE 1302 may also transmit the additional SL-RSCP / RSCPD measurement(s) to the location server 1304 with an indication that the additional SL-RSCP / RSCPD measurement(s) are obtained without using AI / ML.

[0164] In another example, the measurement(s) of SL-RSCP / RSCPD using AI / ML may be based on a request from the location server 1304 (e.g., the measurement(s) are configured to be “on-demand”). For example, as shown at 1322, the location server 1304 may transmit, to the first UE 1302, a request to measure SL-RSCP / RSCPD of RSs using AI / ML. In response, at 1312, the first UE 1302 may measure the SL- RSCP / RSCPD of the set of RSs using the AI / ML. In addition, the location server 1304 may also request the first UE 1302 to provide the quality of the SL-RSCP / RSCPD measurement(s), and in response, the first UE 1302 may include the quality of the SL- RSCP / RSCPD measurement(s) when providing the SL-RSCP / RSCPD measurement(s) at 1320.129025-2434WO01Qualcomm Ref. No. 2405929WO 54

[0165] In some implementations, as shown at 1324, the first UE 1302 may be configured to provide its capabilities related to phase measurements to the location server 1304, such as capabilities related to the support of phase measurements using AI / ML, capabilities related to the support of phase measurements types (e.g., RSCP, RSCPD of DL / SL / UL) using AI / ML, capabilities related to the support of phase AI / ML model output construction (e.g., the number of phase measurements, the maximum number of SL-RS resources, etc.) using AI / ML, and / or capabilities related to the support of phase AI / ML model input construction (e.g., the number of phase measurements, the maximum number of SL-RS resources, etc.) using AI / ML, etc. Then, based on the capabilities of the first UE 1302 related to phase measurements, the location server 1304 may request the first UE 1302 to provide phase measurements supported by the first UE 1302 (e.g., via the request at 1322).

[0166] In some implementations, as shown at 1326, the location server 1304 may be configured to provide assistance data or assistance information related to phase measurements to the first UE 1302, such as assistance on RS configurations (e.g, configurations for receiving the setofRSs), assistance on material information, (e.g, for the set of AI / ML input 1316 as discussed at 1314), assistance on phase error / calibration indicators corresponding to TX side (e.g., for the set of AI / ML input 1316 as discussed at 1314), and / or assistance on phase error / calibration indicators correspondingtoRX side (e.g., forthesetof AI / ML input 1316 as discussed at 1314), etc.

[0167] Depending on implementations, the communication(s) between the first UE 1302 and the location server 1304 / the second UE 1306 may be based on LPP, NRPPa, and / or SL-LPP. For example, dedicated signaling / messages may be configured for the first UE 1302, the location server 1304, and / or the second UE 1306 for transmitting the signaling / information discussed in connection with 1310, 1320, 1322, 1324, and 1326.

[0168] At 1328, based on the SL-RSCP / RSCPD measurement(s) from the first UE 1302 and the indication that the SL-RSCP / RSCPD measurement(s) are obtained with AI / ML, the location server 1304 may determine the location of the first UE 1302 and / or the second UE 1306, which may include prioritizing on using the SL-RSCP / RSCPD measurement(s) obtained with AI / ML as they are likely to provide better accuracy, or129025-2434WO01Qualcomm Ref. No. 2405929WO 55giving a higher weight to the location of the first UE 1302 and / or the second UE 1306 estimated from the SL-RSCP / RSCPD measurement(s) obtained with AI / ML, etc.

[0169] Similarly, in some implementations, the first UE 1302 may be configured to derive / obtain the SL-RSCP / RSCPD measurement(s) based on:(1) just using a conventional (non-AI / ML) method to derive / obtain the SL- RSCP / RSCPD measurement(s) if the set of RSs is within an indicated time window,(2) just using AI / ML to derive / obtain the SL-RSCP / RSCPD measurement(s) if the set of RSs is within an indicated time window,(3) using a conventional (non-AI / ML) method and / or AI / ML to derive / obtain the SU RSCP / RSCPD measurement(s) if the set of RSs is within an indicated time window,(4) just using a conventional (non-AI / ML) method to derive / obtain the SL- RSCP / RSCPD measurement(s) if the set of RSs is outside of an indicated time window,(5) just using AI / ML to derive / obtain the SL-RSCP / RSCPD measurement(s) if the set of RSs is outside of an indicated time window, and / or(6) using a conventional (non-AI / ML) method and / or AI / ML to derive / obtain the SU RSCP / RSCPD measurement(s) if the set of RSs is outside of an indicated time window.

[0170] FIG. 14 is a flowchart 1400 of wireless communication. The method may be performed by a wireless device (e.g., theUE 104, 404, 602, 1102, 1202, 1302, 1306; the base station 102, 706; the network entity 1106, 1206, 1702; the apparatus 1604). The method may enable the wireless device (which may be a UE, a PRU, a base station, a TRP, a sidelink device, etc.) to perform phase measurements using AI / ML, and also indicate that the phase measurements are performed using the AI / ML, thereby improving the overall performance of phase-based AI / ML assisted positioning.

[0171] At 1408, the wireless device may obtain a first indication of a measurement of at least one of an RSCP or an RSCPD for a set of RSs using AI / ML, such as described in connection with FIGs. 11 to 13. For example, as discussed in connection with 1112 of FIG. 11 , based on the received set of RSs, the UE 1102 may measure the set of RSs and obtain measurement(s) of an RSCP or an RSCPD for the set of RSs using AI / ML129025-2434WO01Qualcomm Ref. No. 2405929WO 56(e.g., using at least one physical AI / ML model, at least one logical AI / ML model, and / or at least one AI / ML functionality, etc.). In some examples, the UE 1102 may also receive the RS measurement(s) from another entity (e.g., from another UE), and derive the DL-RSCP / RSCPD measurement(s) from the received RS measurements) using the AI / ML. Similarly, as discussed in connection with 1212 of FIG. 12, based on the received set of RSs, the network entity 1206 may measure the set of RSs and obtain measurement(s) of an RSCP or an RSCPD for the set of RSs using AI / ML. The obtainment of the first indication of the measurement may be performed by, e.g., the AI / ML phase measurement component 198, the transceiver(s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 ofthe apparatus 1604 in FIG. 16. The reception of the request may also be performedby, e.g., the AI / ML phase measurement component 199, the transceiver(s) 1746, the RU processor(s) 1742, the DU processor(s) 1732, and / or the CU processor(s) 1712, ofthe network entity 1702 in FIG. 17.

[0172] In one example, to obtain the first indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs, the wireless device may be configured to measure at least one of the RSCP or the RSCPD for the set of RSs.

[0173] In another example, the wireless device is a UE or a PRU, where the set of RSs corresponds to a set of DL-RSs or a set of PRSs, the wireless is further configured to receive, from at least one network entity prior to obtainment of the first indication, the set of DL-RSs or the set PRSs.

[0174] In another example, the wireless device is a network entity, where the set of RSs corresponds to a set of UL-RSs or a set of SRSs, the wireless is further configured to receive, from a UE or a PRU prior to obtainment of the first indication, the set of UL- RSs or the set SRSs.

[0175] In another example, the wireless device is a first UE or a first PRU, where the set of RSs corresponds to a set of SL-RSs, the wireless is further configuredto receive, from a second UE or a second PRU prior to obtainment of the first indication, the set of SL-RSs.

[0176] In another example, the measurement of the RSCP or the RSCPD for the set of RSs is based on at least one of: a CFR measurement, a CIR measurement, a PDP measurement, a set of sample-based measurements, or a set of path-based measurements.129025-2434WO01Qualcomm Ref. No. 2405929WO 57

[0177] In another example, at least one of information related to a surrounding environment of the wireless device, a first phase error or calibration at a transmitter side, or a second phase error or calibration at a receiver side is used as an input to the AI / ML for measuring the RSCP or the RSCPD for the set of RSs using the AI / ML.

[0178] In another example, an output of the AI / ML includes at least one of : the RSCP of a carrier, the RSCPD of the carrier, the RSCP of a first path arrival, the RSCPD of the first path arrival, the RSCP of an Nthpath, or the RSCPD of the Nthpath.

[0179] In another example, the AI / ML is associated with at least one of : a physical AI / ML model, a logical AI / ML model, or an AI / ML functionality.

[0180] At 1410, the wireless device may transmit a second indication of the measurement of at least one of the RSCP orthe RSCPD forthe setofRSs, where the second indication indicates that at least one of the RSCP or the RSCPD forthe set of RSs is obtained using the AI / ML, such as described in connection with FIGs. 11 to 13. For example, as discussed in connection with 1120 of FIG. 11, the UE 1102 may transmit, to a location server 1104, the DL-RSCP / RSCPD measurement(s) and an indication that the DL-RSCP / RSCPD measurement(s) are obtained using AI / ML. Similarly, as discussed in connection with 1220 of FIG. 12, the network entity 1206 may transmit, to a location server 1204, the UL-RSCP / RSCPD measurement(s) and an indication that the UL-RSCP / RSCPD measurement(s) are obtained using AI / ML. The transmission of the second indication of the measurement may be performed by, e.g, the AI / ML phase measurement component 198, the transceiver(s) 1622, the cellular baseband processor(s) 1624, and / orthe application processor(s) 1606 of the apparatus 1604 in FIG. 16. The reception of the request may also be performed by, e.g., the AI / ML phase measurement component 199, the transceiver(s) 1746, the RU processor(s) 1742, the DU processor(s) 1732, and / orthe CU processor(s) 1712, of the network entity 1702 in FIG. 17.

[0181] In one example, the wireless device may transmit a third indication that is indicative of a quality of the measurement of at least one of the RSCP or the RSCPD forthe set of RSs.

[0182] In another example, the wireless device may receive a request to measure the RSCP or the RSCPD using the AI / ML, where to obtain the first indication of the measurement of at least one of the RSCP or the RSCPD forthe setofRSs using the AI / ML, the wireless device may be configured to obtain, based on the request, the129025-2434WO01Qualcomm Ref. No. 2405929WO 58first indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs using the AI / ML. In some implementations, the request further includes a third indication to provide a quality indication for the measurement.

[0183] In another example, the wireless device may transmit a capability indication that is indicative at least one of : a support of phase measurements using the AI / ML, a list of phase measurement types supported using the AI / ML, a list of phase measurements referencing options supported using the AI / ML, a list of supported AI / ML model outputs, or a list of supported AI / ML model inputs.

[0184] In another example, the wireless device may receive, based on the capability indication, assistance data or information that includes at least one of: first assistance data associated with RS configurations, second assistance data associated with material information, third assistance data associated with a first set of phase error or calibration indicators corresponding to a TX side, or fourth assistance data associated with a second set of phase error or calibration indicators corresponding to an RX side.

[0185] FIG. 15 is a flowchart 1500 of wireless communication. The method may be performed by a wireless device (e.g., theUE 104, 404, 602, 1102, 1202, 1302, 1306; the base station 102, 706; the network entity 1106, 1206, 1702; the apparatus 1604). The method may enable the wireless device (which may be a UE, a PRU, a base station, a TRP, a sidelink device, etc.) to perform phase measurements using AI / ML, and also indicate that the phase measurements are performed using the AI / ML, thereby improving the overall performance of phase-based AI / ML assisted positioning.

[0186] At 1508, the wireless device may obtain a first indication of a measurement of at least one of an RSCP or an RSCPD for a set of RSs using AI / ML, such as described in connection with FIGs. 11 to 13. For example, as discussed in connection with 1112 of FIG. 11 , based on the received set of RSs, the UE 1102 may measure the set of RSs and obtain measurement(s) of an RSCP or an RSCPD for the set of RSs using AI / ML (e.g., using at least one physical AI / ML model, at least one logical AI / ML model, and / or at least one AI / ML functionality, etc.). In some examples, the UE 1102 may also receive the RS measurement(s) from another entity (e.g., from another UE), and derive the DL-RSCP / RSCPD measurement(s) from the received RS measurements) using the AI / ML. Similarly, as discussed in connection with 1212 of FIG. 12, based on the received set of RSs, the network entity 1206 may measure the set of RSs and129025-2434WO01Qualcomm Ref. No. 2405929WO 59obtain measurement(s) of an RSCP or an RSCPD for the set of RSs using AI / ML. The obtainment of the first indication of the measurement may be performed by, e.g., the AI / ML phase measurement component 198, the transceiver(s) 1622, the cellular baseband processor(s) 1624, and / orthe application processor(s) 1606 of the apparatus 1604 in FIG. 16. The reception of the request may also be performedby, e.g., the AI / ML phase measurement component 199, the transceiver(s) 1746, the RU processor(s) 1742, the DU processor(s) 1732, and / orthe CU processor(s) 1712, of the network entity 1702 in FIG. 17.

[0187] In one example, to obtain the first indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs, the wireless device may be configured to measure at least one of the RSCP or the RSCPD for the set of RSs.

[0188] In another example, the wireless device is a UE or a PRU, where the set of RSs corresponds to a set of DL-RSs or a set of PRSs, the wireless is further configured to receive, from at least one network entity prior to obtainment of the first indication, the set of DL-RSs or the set PRSs.

[0189] In another example, the wireless device is a network entity, where the set of RSs corresponds to a set of UL-RSs or a set of SRSs, the wireless is further configured to receive, from a UE or a PRU prior to obtainment of the first indication, the set of UL- RSs or the set SRSs.

[0190] In another example, the wireless device is a first UE or a first PRU, where the set of RSs corresponds to a set of SL-RSs, the wireless is further configuredto receive, from a second UE or a second PRU prior to obtainment of the first indication, the set of SL-RSs.

[0191] In another example, the measurement of the RSCP or the RSCPD forthe setofRSs is based on at least one of: a CFR measurement, a CIR measurement, a PDP measurement, a set of sample-based measurements, or a set of path-based measurements.

[0192] In another example, at least one of information related to a surrounding environment of the wireless device, a first phase error or calibration at a transmitter side, or a second phase error or calibration at a receiver side is used as an input to the AI / ML for measuring the RSCP or the RSCPD for the set of RSs using the AI / ML.129025-2434WO01Qualcomm Ref. No. 2405929WO 60

[0193] In another example, an output of the AI / ML includes at least one of : the RSCP of a carrier, the RSCPD of the carrier, the RSCP of a first path arrival, the RSCPD of the first path arrival, the RSCP of an Nthpath, or the RSCPD of the Nthpath.

[0194] In another example, the AI / ML is associated with at least one of : a physical AI / ML model, a logical AI / ML model, or an AI / ML functionality.

[0195] At 1510, the wireless device may transmit a second indication of the measurement of at least one of the RSCP orthe RSCPD forthe setofRSs, where the second indication indicates that at least one of the RSCP or the RSCPD forthe set of RSs is obtained using the AI / ML, such as described in connection with FIGs. 11 to 13. For example, as discussed in connection with 1120 of FIG. 11, the UE 1102 may transmit, to a location server 1104, the DL-RSCP / RSCPD measurement(s) and an indication that the DL-RSCP / RSCPD measurement(s) are obtained using AI / ML. Similarly, as discussed in connection with 1220 of FIG. 12, the network entity 1206 may transmit, to a location server 1204, the UL-RSCP / RSCPD measurement(s) and an indication that the UL-RSCP / RSCPD measurement(s) are obtained using AI / ML. The transmission of the second indication of the measurement may be performed by, e.g, the AI / ML phase measurement 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. The reception of the request may also be performed by, e.g., the AI / ML phase measurement component 199, the transceiver(s) 1746, the RU processor(s) 1742, the DU processor(s) 1732, and / or the CU processor(s) 1712, of the network entity 1702 in FIG. 17.

[0196] In one example, as shown at 1512, the wireless device may transmit a third indication that is indicative of a quality of the measurement of at least one of the RSCP or the RSCPD forthe set of RSs, such as described in connection with FIGs. 11 to 13. For example, as discussed in connection with 1120 of FIG. 11, the UE 1102 may also be configured to provide the quality of the DL-RSCP / RSCPD measurement(s). Similarly, as discussed in connection with 1220 of FIG. 12, the network entity 1206 may also be configured to provide the quality of the UL-RSCP / RSCPD measurement(s). The transmission of the third indication may be performed by, e.g, the AI / ML phase measurement 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. The reception of the request may also be performedby, e.g., the129025-2434WO01Qualcomm Ref. No. 2405929WO 61AI / ML phase measurement component 199, the transceiver(s) 1746, the RU processor(s) 1742, the DU processor(s) 1732, and / or the CU processor(s) 1712, of the network entity 1702 in FIG. 17.

[0197] In another example, as shown at 1506, the wireless device may receive a request to measure the RSCP ortheRSCPD usingthe AI / ML, where to obtain the first indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs using the AI / ML, the wireless device may be configured to obtain, based on the request, the first indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs usingthe AI / ML, such as described in connection with FIGs. 11 to 13. For example, as discussed in connection with 1122 of FIG. 11, the UE 1102 may receive, from the location server 1104, a request to measure DL-RSCP / RSCPD of RSs using AI / ML. In response, at 1112, the UE 1102 may measure the DL-RSCP / RSCPD of the set of RSs using the AI / ML. Similarly, as discussed in connection with 1222 of FIG.12, the network entity 1206 may receive, from the location server 1204, a request to measure UL-RSCP / RSCPD of RSs using AI / ML. In response, at 1212, the network entity 1206 may measure the UL-RSCP / RSCPD of the set of RSs using the AI / ML. The reception of the request may be performed by, e.g., the AI / ML phase measurement 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. The reception of the request may also be performed by , e.g. , the AI / ML phase measurement component 199, the transceiver(s) 1746, theRU processor(s) 1742, the DU processor(s) 1732, and / or the CU processor(s) 1712, of the network entity 1702 in FIG. 17. In some implementations, the request further includes a third indication to provide a quality indication for the measurement.

[0198] In another example, as shown at 1502, the wireless device may transmit a capability indication that is indicative at least one of a support of phase measurements using the AI / ML, a list of phase measurement types supported usingthe AI / ML, a list of phase measurements referencing options supported usingthe AI / ML, a list of supported AI / ML model outputs, or a list of supported AI / ML model inputs, such as described in connection with FIGs. 11 to 13. For example, as discussed in connection with 1124 of FIG. 11 , the UE 1102 may be configured to provide its capabilities related to phase measurements to the location server 1104, such as capabilities related to the support of phase measurements using AI / ML, capabilities related to the support of phase129025-2434WO01Qualcomm Ref. No. 2405929WO 62measurements types (e.g., RSCP, RSCPD ofDL / SL / UL) using AI / ML, capabilities related to the support of phase AI / ML model output construction (e.g., the number of phase measurements, the maximum number of TRPs, the maximum number of PRS resources, etc.) using AI / ML, and / or capabilities related to the support of phase AI / ML model input construction (e.g., the number of phase measurements, the maximum number of TRPs, the maximum number of PRS resources, etc.) using AI / ML, etc. Then, based on the capabilities of the UE 1102 related to phase measurements, the location server 1104 may request the UE 1102 to provide phase measurements supported by the UE 1102 (e.g., via the request at 1122). Similarly, as discussed in connection with 1224 of FIG. 12, the network entity 1206 may be configured to provide its capabilities related to phase measurements to the location server 1204. The transmission of the capability indication maybe performed by, e.g, the AI / ML phase measurement component 198, the transceiver(s) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 ofthe apparatus 1604 in FIG. 16. The reception of the request may also be performedby, e.g., the AI / ML phase measurement component 199, the transceiver(s) 1746, the RU processor(s) 1742, the DU processor(s) 1732, and / or the CU processor(s) 1712, ofthe network entity 1702 in FIG. 17.

[0199] In another example, as shown at 1504, the wireless device may receive, based on the capability indication, assistance data or information that includes at least one of first assistance data associated with RS configurations, second assistance data associated with material information, third assistance data associated with a first set of phase error or calibration indicators corresponding to a TX side, or fourth assistance data associated with a second set of phase error or calibration indicators corresponding to an RX side, such as described in connection with FIGs. 11 to 13. For example, as discussed in connection with 1126 of FIG. 11, the UE 1102 may receive, from the location server 1104, assistance data or assistance information related to phase measurements to, such as assistance on RS configurations (e.g., configurations for receiving the set of RSs), assistance on material information, (e.g., for the set of AI / ML input 1116 as discussed at 1114), assistance on phase error / calib ration indicators correspondingto TX side (e.g., forthe setof AI / ML input 1116 as discussed at 1114), and / or assistance on phase error / calibration indicators correspondingto RX side (e.g., for the set of AI / ML input 1116 as discussed at 1114), etc. Similarly, as129025-2434WO01Qualcomm Ref. No. 2405929WO 63discussed in connection with 1226 of FIG. 12, the network entity 1206 may receive, from the location server 1204, assistance data or assistance information related to phase measurements. The reception of the assistance data or information may be performed by, e.g., the AI / ML phase measurement component 198, the transceivers) 1622, the cellular baseband processor(s) 1624, and / or the application processor(s) 1606 of the apparatus 1604 in FIG. 16. The reception of the request may also be performed by, e.g., the AI / ML phase measurement component 199, the transceiver(s) 1746, the RU processor(s) 1742, the DU processor(s) 1732, and / or the CU processor(s) 1712, of the network entity 1702 in FIG. 17.

[0200] 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 atleast 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, aWLAN module 1614, an ultrawide band (UWB) module 1638 (e.g., a UWB transceiver), an SPS module 1616 (e.g., GNSS module), one ormore 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 / oracamera 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 entity129025-2434WO01Qualcomm Ref. No. 2405929WO 641602. 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, includingthe 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 to perform the various functions described supra. The cellular baseband processors) 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 configuredto perform a first sub set of the various functions described supra without information storedin the memory and may be configured to perform a second subset of the various functions described supra based on the information stored in the memory. The computer-readable medium / memory may also be used for storing data that is manipulated by the cellular baseband processors) 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.

[0201] As discussed supra, the AI / ML phase measurement component 198 may be configured to obtain a first indication of a measurement of at least one of an RSCP or an RSCPD for a set of RSs using AI / ML. The AI / ML phase measurement component 198 may also be configured to transmit a second indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs, where the second indication indicates that at least one of the RSCP or the RSCPD for the set of RSs is obtained129025-2434WO01Qualcomm Ref. No. 2405929WO 65using the AI / ML. The AI / ML phase measurement 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 AI / ML phase measurement component 198 may be one or more hardware components specifically configured to carry out the stated processes / algorithm, implemented by one or more processors configured to perform the stated processes / algorithm, stored within a computer-readable medium for implementation by one or more processors, or some combination thereof. When multiple processors are implemented, the multiple processors may perform the stated processes / algorithm individually or in combination. As shown, the apparatus 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 obtaining a first indication of a measurement of at least one of anRSCP or an RSCPD for a set of RSs using AI / ML. The apparatus 1604 may further include means for transmitting a second indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs, where the second indication indicates that at least one of the RSCP or the RSCPD for the set of RSs is obtained using the AI / ML.

[0202] In one configuration, the means for obtaining the first indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs may include configuring the apparatus 1604 to measure at least one of the RSCP or the RSCPD for the set of RSs.

[0203] In another configuration, the apparatus 1604 may further include means for receiving from at least one network entity prior to obtainment of the first indication, the set of DL-RSs or the set PRSs.

[0204] In another configuration, the apparatus 1604 may further include means for receiving from a second UE or a second PRU prior to obtainment of the first indication, the set of SL-RSs.

[0205] In another configuration, the measurement of the RSCP or the RSCPD for the set of RSs is based on at least one of: a CFR measurement, a CIR measurement, a PDP measurement, a set of sample-based measurements, or a set of path-based measurements.129025-2434WO01Qualcomm Ref. No. 2405929WO 66

[0206] In another configuration, at least one of information related to a surrounding environment of the wireless device, a first phase error or calibration at a transmitter side, or a second phase error or calibration at a receiver side is used as an input to the AI / ML for measuring the RSCP or the RSCPD for the set of RSs using the AI / ML.

[0207] In another configuration, an output of the AI / ML includes at least one of : the RSCP of a carrier, the RSCPD of the carrier, the RSCP of a first path arrival, the RSCPD of the first path arrival, the RSCP of an Nthpath, or the RSCPD of the Nthpath.

[0208] In another configuration, the AI / ML is associated with at least one of: a physical AI / ML model, a logical AI / ML model, or an AI / ML functionality.

[0209] In another configuration, the apparatus 1604 may further include means for transmitting a third indication that is indicative of a quality of the measurement of at least one of the RSCP or the RSCPD for the set of RSs.

[0210] In another configuration, the apparatus 1604 may further include means for receiving a request to measure the RSCP or the RSCPD using the AI / ML, where the means for obtaining the first indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs using the AI / ML may include configuring the apparatus 1604 to obtain, based on the request, the first indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs using the AI / ML. In some implementations, the request further includes a third indication to provide a quality indication for the measurement.

[0211] In another configuration, the apparatus 1604 may further include means for transmitting a capability indication that is indicative at least one of : a support of phase measurements using the AI / ML, a list of phase measurement types supported using the AI / ML, a list of phase measurements referencing options supported using the AI / ML, a list of supported AI / ML model outputs, or a list of supported AI / ML model inputs.

[0212] In another configuration, the apparatus 1604 may further include means for receiving based on the capability indication, assistance data or information that includes at least one of: first assistance data associated with RS configurations, second assistance data associated with material information, third assistance data associated with a first set of phase error or calibration indicators correspondingto a TX side, or fourth assistance data associated with a second set of phase error or calibration indicators corresponding to an RX side.129025-2434WO01Qualcomm Ref. No. 2405929WO 67

[0213] The means may be the AI / ML phase measurement 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.

[0214] FIG. 17 is a diagram 1700 illustrating an example of a hardware implementation for a network entity 1702. The network entity 1702 may be aBS, a component of aBS, or may implement B S functionality . The network entity 1702 may include at least one of a CU 1710, a DU 1730, or an RU 1740. For example, depending on the layer functionality handled by the AI / ML phase measurement component 199, the network entity 1702 may include the CU 1710; both the CU 1710 and the DU 1730; each of the CU 1710, the DU 1730, and the RU 1740; the DU 1730; both the DU 1730 and the RU 1740; ortheRU 1740. The CU 1710 may include at least one CU processor 1712. The CU processor(s) 1712 may include on-chip memory 1712' . In some aspects, the CU 1710 may further include additional memory modules 1714 and a communications interface 1718. The CU 1710 communicates with the DU 1730 through a midhaul link, such as an Fl interface. The DU 1730 may include at least one DU processor 1732. The DU processor(s) 1732 may include on-chip memory 1732'. In someaspects, theDU 1730 may further include additional memory modules 1734 and acommunications interface 1738. TheDU 1730 communicates with the RU 1740 through a fronthaul link. The RU 1740 may include at least one RU processor 1742. The RUprocessor(s) 1742 may include on-chip memory 1742'. In someaspects, the RU 1740 may further include additional memory modules 1744, one or more transceivers 1746, antennas 1780, and a communications interface 1748. The RU 1740 communicates with the UE 104. The on-chip memory 1712', 1732', 1742' and the additional memory modules 1714, 1734, 1744 may each be considered a computer-readable medium / memory. Each computer-readable medium / memory may be non-transitory. Each of the processors 1712, 1732, 1742 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.129025-2434WO01Qualcomm Ref. No. 2405929WO 68The computer-readable medium / memory may also be used for storing data that is manipulated by the processor(s) when executing software.

[0215] As discussed supra, the AI / ML phase measurement component 199 may be configured to obtain a first indication of a measurement of at least one of an RSCP or an RSCPD for a set of RSs using AI / ML. The AI / ML phase measurement component 199 may also be configured to transmit a second indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs, where the second indication indicates that at least one of the RSCP or the RSCPD for the set of RSs is obtained using the AI / ML. The AI / ML phase measurement component 199 may be within one or more processors of one or more of the CU 1710, DU 1730, and the RU 1740. The AI / ML phase measurement component 199 may be one or more hardware components specifically configured to carry out the stated processes / algorithm, implemented by one or more processors configured to perform the stated processes / algorithm, stored within a computer-readable medium for 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 1702 may include a variety of components configured forvarious functions. In one configuration, the networkentity 1702 may include means for obtaining a first indication of a measurement of at least one of an RSCP or an RSCPD for a set of RSs using AI / ML. The network entity 1702 may further include means for transmitting a second indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs, where the second indication indicates that at least one of the RSCP or the RSCPD for the set of RSs is obtained using the AI / ML.

[0216] In one configuration, the means for obtaining the first indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs may include configuring the network entity 1702 to measure at least one of the RSCP or the RSCPD for the set of RSs.

[0217] In another configuration, the network entity 1702 may further include means for receiving, from a UE or a PRU prior to obtainment of the first indication, the set of UL-RSs or the set SRSs.

[0218] In another configuration, the measurement of the RSCP or the RSCPD for the set of RSs is based on at least one of: a CFR measurement, a CIR measurement, a PDP129025-2434WO01Qualcomm Ref. No. 2405929WO 69measurement, a set of sample-based measurements, or a set of path-based measurements.

[0219] In another configuration, at least one of information related to a surrounding environment of the wireless device, a first phase error or calibration at a transmitter side, or a second phase error or calibration at a receiver side is used as an input to the AI / ML for measuring the RSCP or the RSCPD for the set of RSs using the AI / ML.

[0220] In another configuration, an output of the AI / ML includes at least one of : the RSCP of a carrier, the RSCPD of the carrier, the RSCP of a first path arrival, the RSCPD of the first path arrival, the RSCP of an Nthpath, or the RSCPD of the Nthpath.

[0221] In another configuration, the AI / ML is associated with at least one of: a physical AI / ML model, a logical AI / ML model, or an AI / ML functionality.

[0222] In another configuration, the network entity 1702 may further include means for transmitting a third indication that is indicative of a quality of the measurement of at least one of the RSCP or the RSCPD for the set of RSs.

[0223] In another configuration, the network entity 1702 may further include means for receiving a request to measure the RSCP or the RSCPD using the AI / ML, where the means for obtainingthe first indication ofthe measurement of atleast one of the RSCP or the RSCPD for the set of RSs using the AI / ML may include configuring the network entity 1702 to obtain, based on the request, the first indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs using the AI / ML. In some implementations, the request further includes a third indication to provide a quality indication for the measurement.

[0224] In another configuration, the network entity 1702 may further include means for transmitting a capability indication that is indicative atleast one of : a support of phase measurements using the AI / ML, a list of phase measurement types supported using the AI / ML, a list of phase measurements referencing options supported using the AI / ML, a list of supported AI / ML model outputs, or a list of supported AI / ML model inputs.

[0225] In another configuration, the network entity 1702 may further include means for receiving, based on the capability indication, assistance data or information that includes at least one of : first assistance data associated with RS configurations, second assistance data associated with material information, third assistance data associated with a first set of phase error or calibration indicators corresponding to a TX side, or129025-2434WO01Qualcomm Ref. No. 2405929WO 70fourth assistance data associated with a second set of phase error or calibration indicators corresponding to an RX side.

[0226] The means may be the AI / ML phase measurement component 199 of the network entity 1702 configured to perform the functions recited by the means. As described supra, the network entity 1702 may include the TX processor 316, the RX processor 370, and the controller / processor 375. As such, in one configuration, the means may be the TX processor 316, the RX processor 370, and / or the controller / processor 375 configured to perform the functions recited by the means.

[0227] FIG. 18 is a flowchart 1800 of wireless communication. The method may be perf ormed by a network entity (e .g. , the one or more location servers 168 ; the location server 704, 1104, 1204, 1304; the network entity 1960). The method may enable the network entity to configure a wireless device (which may be a UE, a PRU, a base station, a TRP, a sidelink device, etc.) to perform phase measurements using AI / ML, thereby improving the overall performance of phase-based AI / ML assisted positioning.

[0228] At 1802, the network entity may receive, from a wireless device, a measurement of at least one of an RSCP or an RSCPD for a set of RSs, such as described in connection withFIGs. 11 to 13. For example, as discussed in connection with 1120 of FIG. 11, a location server 1104 may receive, from the UE 1102, the DL-RSCP / RSCPD measurement(s) and an indication that the DL-RSCP / RSCPD measurement(s) are obtained using AI / ML. Similarly, as discussed in connection with 1220 of FIG. 11, a location server 1204 may receive, from the network entity 1206, the UL- RSCP / RSCPD measurement(s) and an indication that the UL-RSCP / RSCPD measurement(s) are obtainedusing AI / ML. The reception of the measurement may be performed by, e.g., the AI / ML phase measurement configuration component 197, the network processor(s) 1912, and / orthe network interface 1980 of the network entity 1960 in FIG. 19.

[0229] At 1804, the network entity may receive, from the wireless device, an indication indicating that the measurement of at least one of the RSCP or the RSCPD for the set of RSs is obtained using AI / ML, such as describedin connection with FIGs. 11 to 13. For example, as discussed in connection with 1120 of FIG. 11, a location server 1104 may receive, from the UE 1102, the DL-RSCP / RSCPD measurement(s) and an indication that the DL-RSCP / RSCPD measurement(s) are obtained using AI / ML.129025-2434WO01Qualcomm Ref. No. 2405929WO 71Similarly, as discussed in connection with 1220 of FIG. 11, a location server 1204 may receive, from the network entity 1206, the UL-RSCP / RSCPD measurements) and an indication that the UL-RSCP / RSCPD measurement(s) are obtained using AI / ML. The reception of the indication may be performed by, e.g., the AI / ML phase measurement configuration component 197, the network processor(s) 1912, and / or the network interface 1980 of the network entity 1960 in FIG. 19.

[0230] In one example, the network entity may further estimate a location of the wireless device or a target based on the measurement and the indication.

[0231] In another example, the network entity may further receive a second indication that is indicative of a quality of the measurement of at least one of the RSCP or the RSCPD for the set of RSs.

[0232] In another example, the wireless device is a UE, a PRU, a base station, or a TRP.

[0233] In another example, the network entity may further transmit, to the wireless device, a request to measure the RSCP or the RSCPD using the AI / ML, where to receive the measurement of atleast one of the RSCP orthe RSCPD forthe set of RSs, the network entity may be configured to receive, based on the request, the measurement of at least one of the RSCP or the RSCPD forthe set of RSs. In some implementations, the request further includes a second indication to provide a quality indication for the measurement.

[0234] In another example, the measurement of the RSCP or the RSCPD forthe set of RSs is based on at least one of: a CFR measurement, a CIR measurement, a PDP measurement, a set of sample-based measurements, or a set of path-based measurements.

[0235] In another example, at least one of information related to a surrounding environment of the wireless device, a first phase error or calibration at a transmitter side, or a second phase error or calibration at a receiver side is used as input to the AI / ML for measuring the RSCP or the RSCPD for the set of RSs using the AI / ML.

[0236] In another example, an output of the AI / ML includes at least one of : the RSCP of a carrier, the RSCPD of the carrier, the RSCP of a first path arrival, the RSCPD of the first path arrival, the RSCP of an Nthpath, or the RSCPD of the Nthpath.

[0237] In another example, the network entity may further receive, from the wireless device, a capability indication that is indicative at least one of: a support of phase measurements using the AI / ML, a list of phase measurement types supported using129025-2434WO01Qualcomm Ref. No. 2405929WO 72the AI / ML, a list of phase measurements referencing options supported using the AI / ML, a list of AI / ML supported model outputs, or a list of AI / ML supported model inputs.

[0238] In another example, the network entity may further transmit, to the wireless device based on the capability indication, assistance data or information that includes at least one of: first assistance data associated with RS configurations, second assistance data associated with material information, third assistance data associated with a first set of phase error or calibration indicators correspondingto a TX side, or fourth assistance data associated with a second set of phase error or calibration indicators corresponding to an RX side.

[0239] In another example, the AI / ML is associated with at least one of: a physical AI / ML model, a logical AI / ML model, or an AI / ML functionality.

[0240] FIG. 19 is a diagram 1900 illustrating an example of a hardware implementation for a network entity 1960. In one example, the network entity 1960 may be within the core network 120. The network entity 1960 may include at least one network processor 1912. The network processor(s) 1912 may include on-chip memory 1912'. In some aspects, the network entity 1960 may further include additional memory modules 1914. The network entity 1960communicatesviathenetworkinterfacel980 directly (e.g., backhaul link) or indirectly (e.g., through a RIC) with the CU 1902. The on-chip memory 1912' and the additional memory modules 1914 may each be considered a computer-readable medium / memory. Each computer-readable medium / memory may be non-transitory. The network processor(s) 1912 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.

[0241] As discussed supra, the AI / ML phase measurement configuration component 197 may be configured to receive, from a wireless device, a measurement of at least one of an RSCP or an RSCPD for a set of RSs. The AI / ML phase measurement configuration component 197 may also be configured to receive, from the wireless device, an indication indicating that the measurement of at least one of the RSCP or the RSCPD for the set of RSs is obtained using AI / ML. The AI / ML phase129025-2434WO01Qualcomm Ref. No. 2405929WO 73measurement configuration component 197 may be within the network processors) 1912. The AI / ML phase measurement 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 1960 may include a variety of components configured for various functions. In one configuration, the network entity 1960 may include means for receiving, from a wireless device, a measurement of at least one of an RSCP or an RSCPD for a set of RSs. The network entity 1960 may further include means for receiving, from the wireless device, an indication indicating that the measurement of at least one of the RSCP or the RSCPD for the set of RSs is obtained using AI / ML.

[0242] In one configuration, the network entity 1960 may further include means for estimating a location of the wireless device or a target based on the measurement and the indication.

[0243] In another configuration, the network entity 1960 may further include means for receiving a second indication that is indicative of a quality of the measurement of at least one of the RSCP or the RSCPD for the set of RSs.

[0244] In another configuration, the wireless device is a UE, a PRU, a base station, or a TRP.

[0245] In another configuration, the network entity 1960 may further include means for transmitting, to the wireless device, a request to measure the RSCP or the RSCPD using the AI / ML, where the means for receiving the measurement of at least one of the RSCP or the RSCPD for the set of RSs may include configuringthe network entity 1960 to receive, based on the request, the measurement of at least one of the RSCP or the RSCPD for the set of RSs. In some implementations, the request further includes a second indication to provide a quality indication for the measurement.

[0246] In another configuration, the measurement of the RSCP or the RSCPD for the set of RSs is based on at least one of: a CFR measurement, a CIR measurement, a PDP measurement, a set of sample-based measurements, or a set of path-based measurements.129025-2434WO01Qualcomm Ref. No. 2405929WO 74

[0247] In another configuration, at least one of information related to a surrounding environment of the wireless device, a first phase error or calibration at a transmitter side, or a second phase error or calibration at a receiver side is used as input to the AI / ML for measuring the RSCP or the RSCPD for the set of RSs using the AI / ML.

[0248] In another configuration, an output of the AI / ML includes at least one of : the RSCP of a carrier, the RSCPD of the carrier, the RSCP of a first path arrival, the RSCPD of the first path arrival, the RSCP of an Nthpath, or the RSCPD of the Nthpath.

[0249] In another configuration, the network entity 1960 may further include means for receiving, from the wireless device, a capability indication that is indicative at least one of: a support of phase measurements using the AI / ML, a list of phase measurement types supported using the AI / ML, a list of phase measurements referencing options supported using the AI / ML, a list of AI / ML supported model outputs, or a list of AI / ML supported model inputs.

[0250] In another configuration, the network entity 1960 may further include means for transmitting, to the wireless device based on the capability indication, assistance data or information that includes at least one of: first assistance data associated with RS configurations, second assistance data associated with material information, third assistance data associated with a first set of phase error or calibration indicators corresponding to a TX side, or fourth assistance data associated with a second set of phase error or calibration indicators corresponding to an RX side.

[0251] In another configuration, the AI / ML is associated with at least one of: a physical AI / ML model, a logical AI / ML model, or an AI / ML functionality.

[0252] The means may be the AI / ML phase measurement configuration component 197 of the network entity 1960 configured to perform the functions recited by the means.

[0253] It is understood that the specific order or hierarchy of blocks in the processes / flowcharts disclosed is an illustration of example approaches. Based upon design preferences, it is understood that the specific order or hierarchy of blocks in the processes / flowcharts maybe rearranged. Further, some blocks may be combined or omitted. The accompanying method claims present elements of the various blocks in a sample order, and are not limited to the specific order or hierarchy presented.

[0254] 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 herein129025-2434WO01Qualcomm Ref. No. 2405929WO 75may 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 notimply an immediate action in response to or during the occurrence of an action, but simply imply that if a condition is met then an action will occur, butwithoutrequiringa specific or immediate time constraint for the action to occur. The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any aspect described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects. Unless specifically stated otherwise, the term “some” refers to one or more. Combinations such as “at least one of A, B, or C,” “one or more of A, B, or C,” “at least one of A, B, and C,” “one or more of A, B, and C,” and “A, B, C, or any combination thereof’ include any combination of A, B, and / or C, and may include multiples of A, multiples of B, or multiples of C. Specifically, combinations such as “at least one of A, B, or C,” “one or more of A, B, or C,” “at least one of A, B, and C,” “one or more of A, B, and C,” and “A, B, C, or any combination thereof’ may be A only, B only, C only, A and B, A and C, B and C, or A and B and C, where any such combinations may contain one or more memb er or members of A, B, or C. Sets should b e 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 is configured to perform a set of functions, the at least one processor, individually or in any combination, is configured to perform the set of functions. Accordingly, each processor of the at least one processor may be configured to perform a particular subset of the set of functions, where the subset is the full set, a proper subset of the set, or an empty subset of the set. A processor may be referred to as processor circuitry. A memory / memory module may be referred to as memory circuitry. If a first apparatus receives 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 the129025-2434WO01Qualcomm Ref. No. 2405929WO 76data 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 notbe a substitute forthe 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.”

[0255] As used herein, the phrase “based on” shall notbe 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.

[0256] The following aspects are illustrative only and may be combined with other aspects or teachings described herein, without limitation.

[0257] Aspect 1 is a method of wireless communication at a wireless device, comprising:obtaining a first indication of a measurement of at least one of a reference signal carrier phase (RSCP) or a reference signal carrier phase difference (RSCPD) for a set of reference signals (RSs) using artificial intelligence (Al) or machine learning (ML) (AI / ML); and transmitting a second indication of the measurement of at least one of the RSCP or the RSCPD forthe set of RSs, wherein the second indication indicates that at least one of the RSCP or the RSCPD forthe set of RSs is obtained using the AI / ML.

[0258] Aspect 2 is the method of aspect 1 , wherein obtaining the first indication of the measurement of at least one of the RSCP or the RSCPD forthe set of RSs comprises: measuring at least one of the RSCP or the RSCPD for the set of RSs.

[0259] Aspects isthemethodof aspectl oraspect2, further comprising: transmitting a third indication that is indicative of a quality of the measurement of at least one of the RSCP or the RSCPD for the set of RSs.129025-2434WO01Qualcomm Ref. No. 2405929WO 77

[0260] Aspect 4 is the method of any of aspects 1 to 3 , wherein the wireless device is a user equipment (UE) or a positioning reference unit (PRU), wherein the set of RSs corresponds to a set of downlink (DL) RSs (DL-RSs) or a set of positioning reference signal (PRSs), the method further comprising: receiving, from at least one network entity prior to obtainment of the first indication, the set of DL-RSs or the set PRSs.

[0261] Aspect 5 is the method of any of aspects 1 to 4, wherein the wireless device is a network entity, wherein the set of RSs corresponds to a set of uplink (UL) RSs (UL- RSs) or a set of sounding reference signal (SRSs), the method further comprising: receiving, from a user equipment (UE) or a positioning reference unit (PRU) prior to obtainment of the first indication, the set of UL-RSs or the set SRSs.

[0262] Aspect 6 is the method of any of aspects 1 to 5, wherein the wireless device is a first user equipment (UE) or a first positioning reference unit (PRU), wherein the set of RSs corresponds to a set of sidelink (SL) RSs (SL-RSs), the method further comprising: receiving, from a second UE or a second PRU prior to obtainment of the first indication, the set of SL-RSs.

[0263] Aspect 7 is the method of any of aspects 1 to 6, further comprising: receiving a request to measure the RSCP or the RSCPD using the AI / ML, wherein obtaining the first indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs using the AI / ML comprises: obtaining, based on the request, the first indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs using the AI / ML.

[0264] Aspect 8 is the method of any of aspects 1 to 7, wherein the request further includes a third indication to provide a quality indication for the measurement.

[0265] Aspect 9 is the method of any of aspects 1 to 8, wherein the measurement of the RSCP or the RSCPD for the set of RSs is based on at least one of: a channel frequency response (CFR) measurement, a channel impulse response (CIR) measurement, a power delay profile (PDP) measurement, a set of sample-based measurements, or a set of path-based measurements.

[0266] Aspect 10 is the method of any of aspects 1 to 9, wherein at least one of information related to a surrounding environment of the wireless device, a first phase error or calibration at a transmitter side, or a second phase error or calibration at a receiver side is used as an input to the AI / ML for measuring the RSCP or the RSCPD for the set of RSs using the AI / ML.129025-2434WO01Qualcomm Ref. No. 2405929WO 78

[0267] Aspect 11 is the method of any of aspects 1 to 10, wherein an output of the AI / ML includes at least one of: the RSCP of a carrier, the RSCPD of the carrier, the RSCP of a first path arrival, the RSCPD of the first path arrival, the RSCP of an Nthpath, or the RSCPD of the Nthpath.

[0268] Aspect 12 is the method of any of aspects 1 to 11 , further comprising: transmitting a capability indication that is indicative at least one of : a support of phase measurements using the AI / ML, a list of phase measurement types supported using the AI / ML, a list of phase measurements referencing options supported using the AI / ML, a list of supported AI / ML model outputs, or a list of supported AI / ML model inputs.

[0269] Aspect 13 is the method of any of aspects 1 to 12, further comprising: receiving, based on the capability indication, assistance data or information that includes at least one of: first assistance data associated with RS configurations, second assistance data associated with material information, third assistance data associated with a first set of phase error or calibration indicators corresponding to a transmission (TX) side, or fourth assistance data associated with a second set of phase error or calibration indicators corresponding to a reception (RX) side.

[0270] Aspect 14 is the method of any of aspects 1 to 13, wherein the AI / ML is associated with at least one of: a physical AI / ML model, a logical AI / ML model, or an AI / ML functionality.

[0271] Aspect 15 is an apparatus for wireless communication at a wireless device, including:at least one memory; and at least one processor coupled to the at least one memory and, based at least in part on stored information that is stored in the at least one memory, the at least one processor, individually or in any combination, is configured to implement any of aspects 1 to 14.

[0272] Aspect 16 is the apparatus of aspect 15, further including at least one transceiver coupled to the at least one processor.

[0273] Aspect 17 is an apparatus for wireless communication ata wireless device including means for implementing any of aspects 1 to 14.

[0274] Aspect 18 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 14.

[0275] Aspect 19 is a method of wireless communication at a network entity, comprising:receiving, from a wireless device, a measurement of at least one of a reference signal129025-2434WO01Qualcomm Ref. No. 2405929WO 79carrier phase (RSCP) or a reference signal carrier phase difference (RSCPD) for a set of reference signals (RSs); and receiving, from the wireless device, an indication indicating that the measurement of at least one of the RSCP or the RSCPD for the set of RSs is obtained using artificial intelligence (Al) or machine learning (ML) (AI / ML).

[0276] Aspect 20 is the method of aspect 19, further comprising: estimating a location of the wireless device or a target based on the measurement and the indication.

[0277] Aspect 21 is the method of aspect 19 or aspect 20, further comprising: receiving a second indication that is indicative of a quality of the measurement of at least one of the RSCP or the RSCPD for the set of RSs.

[0278] Aspect 22 is the method of any of aspects 19 to 21, wherein the wireless device is a user equipment (UE), a positioning reference unit (PRU), a base station, or a transmission reception point (TRP).

[0279] Aspect 23 is the method of any of aspects 19 to 22, further comprising: transmitting to the wireless device, a requestto measure the RSCP or the RSCPD using the AI / ML, wherein receiving the measurement of at least one of the RSCP or the RSCPD for the set of RSs comprises: receiving, based on the request, the measurement of at least one of the RSCP or the RSCPD for the set of RSs.

[0280] Aspect 24 is the method of any of aspects 19 to 23, wherein the request further includes a second indication to provide a quality indication for the measurement.

[0281] Aspect 25 is the method of any of aspects 19 to 24, wherein the measurement of the RSCP orthe RSCPD for the set of RSs is based on at least one of : a channel frequency response (CFR) measurement, a channel impulse response (CIR) measurement, a power delay profile (PDP) measurement, a set of sample-based measurements, or a set of path-based measurements.

[0282] Aspect26 is the method of any of aspects 19 to 25, wherein at least one of information related to a surrounding environment of the wireless device, a first phase error or calibration at a transmitter side, or a second phase error or calibration at a receiver side is used as input to the AI / ML for measuring the RSCP or the RSCPD for the set of RSs using the AI / ML.

[0283] Aspect 27 is the method of any of aspects 19 to 26, wherein an output of the AI / ML includes at least one of: the RSCP of a carrier, the RSCPD of the carrier, the RSCP of129025-2434WO01Qualcomm Ref. No. 2405929WO 80a first path arrival, the RSCPD of the first path arrival the RSCP of an Nthpath, or the RSCPD of the Nthpath.

[0284] Aspect 28 is the method of any of aspects 19 to 27, further comprising: receiving from the wireless device, a capability indication that is indicative at least one of: a support of phase measurements using the AI / ML, a list of phase measurement types supported using the AI / ML, a list of phase measurements referencing options supported using the AI / ML, a list of AI / ML supported model outputs, or a list of AI / ML supported model inputs.

[0285] Aspect 29 is the method of any of aspects 19 to 28, further comprising: transmitting to the wireless device based on the capability indication, assistance data or information that includes at least one of: first assistance data associated with RS configurations, second assistance data associated with material information, third assistance data associated with a first set of phase error or calibration indicators corresponding to a transmission (TX) side, or fourth assistance data associated with a second set of phase error or calibration indicators corresponding to a reception (RX) side.

[0286] Aspect 30 is the method of any of aspects 19 to 29, wherein the AI / ML is associated with at least one of: a physical AI / ML model, a logical AI / ML model, or an AI / ML functionality.

[0287] Aspect 31 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 19 to 30.

[0288] Aspect 32 is the apparatus of aspect 31, further including at least one network interface coupled to the at least one processor.

[0289] Aspect 33 is an apparatus for wireless communication ata network entity including means for implementing any of aspects 19 to 30.

[0290] Aspect 34 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 19 to 30.129025-2434WO01

Claims

Qualcomm Ref. No. 2405929WO 81CLAIMS WHAT IS CLAIMED IS:

1. An apparatus for wireless communication at a wireless device, comprising: at least one memory; andat least one processor coupled to the at least one memory, the at least one processor, individually or in any combination, is configured to:obtain a first indication of a measurement of at least one of a reference signal carrier phase (RSCP) or a reference signal carrier phase difference (RSCPD) for a set of reference signals (RSs) using artificial intelligence (Al) or machine learning (ML) (AI / ML); andtransmit a second indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs, wherein the second indication indicates that at least one of the RSCP or the RSCPD for the set of RSs is obtained using the AI / ML.

2. The apparatus of claim 1, wherein to obtain the first indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs, the at least one processor, individually or in any combination, is configured to:measure at least one of the RSCP or the RSCPD for the set of RSs.

3. The apparatus of claim 1, wherein the at least one processor, individually or in any combination, is further configured to:transmit a third indication that is indicative of a quality of the measurement of at least one of the RSCP or the RSCPD for the set of RSs.

4. The apparatus of claim 1, wherein the wireless device is a user equipment (UE) or a positioning reference unit (PRU), wherein the set of RSs corresponds to a set of downlink (DL)RSs (DL-RSs) or a set of positioningreference signal (PRSs), wherein the at least one processor, individually or in any combination, is further configured to:receive, from atleastone network entity priorto obtainment of the first indication, the set of DL-RSs or the set PRSs.129025-2434WO01Qualcomm Ref. No. 2405929WO 825. The apparatus of claim 1 , wherein the wireless device is a network entity, wherein the set of RSs corresponds to a set of uplink (UL) RSs (UL-RSs) or a set of sounding reference signal (SRSs), wherein the at least one processor, individually or in any combination, is further configured to:receive, from a user equipment (UE) or a positioning reference unit (PRU) prior to obtainment of the first indication, the set of UL-RSs or the set SRSs.

6. The apparatus of claim 1, wherein the wireless device is a first user equipment (UE) or a first positioning reference unit (PRU), wherein the set of RSs corresponds to a set of sidelink (SL) RSs (SL-RSs), wherein the at least one processor, individually or in any combination, is further configured to:receive, from a second UE or a second PRU prior to obtainment of the first indication, the set of SL-RSs.

7. The apparatus of claim 1, wherein the at least one processor, individually or in any combination, is further configured to:receive a request to measure the RSCP or the RSCPD using the AI / ML, wherein to obtain the first indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs using the AI / ML, the at least one processor, individually or in any combination, is configured to obtain, based on the request, the first indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs using the AI / ML.

8. The apparatus of claim 7, wherein the request further includes a third indication to provide a quality indication for the measurement.

9. The apparatus of claim 1, wherein the measurement of the RSCP or the RSCPD for the set of RSs is based on at least one of:a channel frequency response (CFR) measurement,a channel impulse response (CIR) measurement,a power delay profile (PDP) measurement,129025-2434WO01Qualcomm Ref. No. 2405929WO 83a set of sample-based measurements, ora set of path-based measurements.

10. The apparatus of claim 1, wherein at least one of information related to a surrounding environment of the wireless device, a first phase error or calibration at a transmitter side, or a second phase error or calibration at a receiver side is used as an input to the AI / ML for measuring the RSCP or the RSCPD for the set of RSs using the AI / ML.

11. The apparatus of claim 1, wherein an output of the AI / ML includes at least one of:the RSCP of a carrier,the RSCPD of the carrier,the RSCP of a first path arrival,the RSCPD of the first path arrival,the RSCP of an Nthpath, orthe RSCPD of the Nthpath.

12. The apparatus of claim 1, wherein the at least one processor, individually or in any combination, is further configured to:transmit a capability indication that is indicative at least one of :a support of phase measurements using the AI / ML,a list of phase measurement types supported using the AI / ML, a list of phase measurements referencing options supported using the AI / ML,a list of supported AI / ML model outputs, ora list of supported AI / ML model inputs.

13. The apparatus of claim 12, wherein the at least one processor, individually or in any combination, is further configured to:129025-2434WO01Qualcomm Ref. No. 2405929WO 84receive, based on the capability indication, assistance data or information that includes at least one of:first assistance data associated with RS configurations,second assistance data associated with material information,third assistance data associated with a first set of phase error or calibration indicators corresponding to a transmission (TX) side, orfourth assistance data associated with a second set of phase error or calibration indicators corresponding to a reception (RX) side.

14. The apparatus of claim 1, wherein the AI / ML is associated with at least one of:a physical AI / ML model,a logical AI / ML model, oran AI / ML functionality.

15. A method of wireless communication at a wireless device, comprising:obtaining a first indication of a measurement of at least one of a reference signal carrier phase (RSCP) or a reference signal carrier phase difference (RSCPD) for a set of reference signals (RSs) using artificial intelligence (Al) or machine learning (ML) (AI / ML); andtransmitting a second indication of the measurement of at least one of the RSCP or the RSCPD for the set of RSs, wherein the second indication indicates that at least one of the RSCP or the RSCPD for the set of RSs is obtained using the AI / ML.

16. The method of claim 15, further comprising:transmitting a third indication that is indicative of a quality of the measurement of at least one of the RSCP or the RSCPD for the set of RSs.

17. An apparatus for wireless communication at a network entity, comprising: at least one memory; andat least one processor coupled to the at least one memory, the at least one processor, individually or in any combination, is configured to:129025-2434WO01Qualcomm Ref. No. 2405929WO 85receive, from a wireless device, a measurement of at least one of a reference signal carrier phase (RSCP) or a reference signal carrier phase difference (RSCPD) for a set of reference signals (RSs); andreceive, from the wireless device, an indication indicating that the measurement of at least one of the RSCP or the RSCPD for the set of RSs is obtained using artificial intelligence (Al) or machine learning (ML) (AI / ML).

18. The apparatus of claim 17, wherein the at least one processor, individually or in any combination, is further configured to:estimate a location of the wireless device or a target based on the measurement and the indication.

19. The apparatus of claim 17, wherein the at least one processor, individually or in any combination, is further configured to:receive a second indication that is indicative of a quality of the measurement of at least one of the RSCP or the RSCPD for the set of RSs.

20. The apparatus of claim 17, wherein the wireless device is a user equipment (UE), a positioning reference unit (PRU), a base station, or a transmission reception point (TRP).

21. The apparatus of claim 17, wherein the at least one processor, individually or in any combination, is further configured to:transmit, to the wireless device, a request to measure the RSCP or the RSCPD using the AI / ML, wherein to receive the measurement of at least one of the RSCP or the RSCPD for the set of RSs, the at least one processor, individually or in any combination, is configured to receive, based on the request, the measurement of at least one of the RSCP or the RSCPD for the set of RSs.

22. The apparatus of claim 21, wherein the request further includes a second indication to provide a quality indication for the measurement.129025-2434WO01Qualcomm Ref. No. 2405929WO 8623. The apparatus of claim 17, wherein the measurement of the RSCP or the RSCPD for the set of RSs is based on at least one of:a channel frequency response (CFR) measurement,a channel impulse response (CIR) measurement,a power delay profile (PDP) measurement,a set of sample-based measurements, ora set of path-based measurements.

24. The apparatus of claim 17, wherein at least one of information related to a surrounding environment of the wireless device, a first phase error or calibration at a transmitter side, or a second phase error or calibration at a receiver side is used as input to the AI / ML for measuring the RSCP or the RSCPD for the set of RSs using the AI / ML.

25. The apparatus of claim 17, wherein an output of the AI / ML includes at least one of:the RSCP of a carrier,the RSCPD of the carrier,the RSCP of a first path arrival,the RSCPD of the first path arrival,the RSCP of an Nthpath, orthe RSCPD of the Nthpath.

26. The apparatus of claim 17, wherein the at least one processor, individually or in any combination, is further configured to:receive, from the wireless device, a capability indication that is indicative at least one of:a support of phase measurements using the AI / ML,a list of phase measurement types supported using the AI / ML,129025-2434WO01Qualcomm Ref. No. 2405929WO 87a list of phase measurements referencing options supported using the AI / ML,a list of AI / ML supported model outputs, ora list of AI / ML supported model inputs.

27. The apparatus of claim 26, wherein the at least one processor, individually or in any combination, is further configured to:transmit, to the wireless device based on the capability indication, assistance data or information that includes at least one of:first assistance data associated with RS configurations,second assistance data associated with material information,third assistance data associated with a first set of phase error or calibration indicators corresponding to a transmission (TX) side, orfourth assistance data associated with a second set of phase error or calibration indicators corresponding to a reception (RX) side.

28. The apparatus of claim 17, wherein the AI / ML is associated with at least one of:a physical AI / ML model,a logical AI / ML model, oran AI / ML functionality.

29. A method of wireless communication at a network entity, comprising:receiving, from a wireless device, a measurement of at least one of a reference signal carrier phase (RSCP) or a reference signal carrier phase difference (RSCPD) for a set of reference signals (RSs); andreceiving, from the wireless device, an indication indicating that the measurement of at least one of the RSCP or the RSCPD for the set of RSs is obtained using artificial intelligence (Al) or machine learning (ML) (AI / ML).129025-2434WO01Qualcomm Ref. No. 2405929WO 8830. The method of claim 29, further comprising:receiving a second indication that is indicative of a quality of the measurement of at least one of the RSCP or the RSCPD for the set of RSs.129025-2434WO01

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