Data collection labeling features for machine learning model positioning

Abstract

Disclosed are techniques for data collection for a machine learning model for positioning. In an aspect, a first device may receive, from a second device, a request for labels for training or monitoring the machine learning model and labeling features corresponding to the labels. The first device may generate a set of labels and a set of labeling features, wherein the set of labels includes at least a set of ground truth labels for output by the machine learning model based on a set of channel measurements for input into the machine learning model, and wherein the set of labeling features includes at least a set of quality indicators associated with the set of ground truth labels.

Description

Qualcomm Ref. No. 2500148WO1DATA COLLECTION LABELING FEATURES FOR MACHINE LEARNING MODEL POSITIONINGTECHNICAL FIELD

[0001] Aspects of the disclosure relate generally to wireless technologies.BACKGROUND

[0002] Wireless communication systems have developed through various generations, including a first-generation analog wireless phone service (1G), a second-generation (2G) digital wireless phone service (including interim 2.5G and 2.75G networks), a third-generation (3G) high speed data, Internet-capable wireless service and a fourth-generation (4G) service (e.g., Long Term Evolution (LTE) or WiMax). There are presently many different types of wireless communication systems in use, including cellular and personal communications service (PCS) systems. Examples of known cellular systems include the cellular analog advanced mobile phone system (AMPS), and digital cellular systems based on code division multiple access (CDMA), frequency division multiple access (FDMA), time division multiple access (TDMA), the Global System for Mobile communications (GSM), etc.

[0003] A fifth generation (5G) wireless standard, referred to as New Radio (NR), enables higher data transfer speeds, greater numbers of connections, and better coverage, among other improvements. The 5G standard, according to the Next Generation Mobile Networks Alliance, is designed to provide higher data rates as compared to previous standards, more accurate positioning (e.g., based on reference signals for positioning (RS-P), such as downlink, uplink, or sidelink positioning reference signals (PRS)), RF sensing, and other technical enhancements. These enhancements, as well as the use of higher frequency bands, enable improved RF sensing and 5G-based positioning.SUMMARY

[0004] The following presents a simplified summary relating to one or more aspects disclosed herein. Thus, the following summary should not be considered an extensive overview relating to all contemplated aspects, nor should the following summary be considered to identify key or critical elements relating to all contemplated aspects or to delineate the1QC2500148WOQualcomm Ref. No. 2500148WO2 scope associated with any particular aspect. Accordingly, the following summary has the sole purpose to present certain concepts relating to one or more aspects relating to the mechanisms disclosed herein in a simplified form to precede the detailed description presented below.

[0005] In an aspect, a method of data collection for a machine learning model for positioning performed by a first device includes receiving, from a second device, a request for labels for training or monitoring the machine learning model and labeling features corresponding to the labels; and generating a set of labels and a set of labeling features, wherein the set of labels includes at least a set of ground truth labels for output by the machine learning model based on a set of channel measurements for input into the machine learning model, and wherein the set of labeling features includes at least a set of quality indicators associated with the set of ground truth labels.

[0006] In an aspect, a first device includes one or more memories; one or more transceivers; and one or more processors communicatively coupled to the one or more memories and the one or more transceivers, the one or more processors, either alone or in combination, configured to: receive, via the one or more transceivers, from a second device, a request for labels for training or monitoring the machine learning model and labeling features corresponding to the labels; and generate a set of labels and a set of labeling features, wherein the set of labels includes at least a set of ground truth labels for output by the machine learning model based on a set of channel measurements for input into the machine learning model, and wherein the set of labeling features includes at least a set of quality indicators associated with the set of ground truth labels.

[0007] In an aspect, a first device includes means for receiving, from a second device, a request for labels for training or monitoring the machine learning model and labeling features corresponding to the labels; and means for generating a set of labels and a set of labeling features, wherein the set of labels includes at least a set of ground truth labels for output by the machine learning model based on a set of channel measurements for input into the machine learning model, and wherein the set of labeling features includes at least a set of quality indicators associated with the set of ground truth labels.

[0008] In an aspect, a non-transitory computer-readable medium stores computer-executable instructions that, when executed by a first device, cause the first device to: receive, from a second device, a request for labels for training or monitoring the machine learning2QC2500148WOQualcomm Ref. No. 2500148WO3 model and labeling features corresponding to the labels; and generate a set of labels and a set of labeling features, wherein the set of labels includes at least a set of ground truth labels for output by the machine learning model based on a set of channel measurements for input into the machine learning model, and wherein the set of labeling features includes at least a set of quality indicators associated with the set of ground truth labels.

[0009] Other obj ects and advantages associated with the aspects disclosed herein will be apparent to those skilled in the art based on the accompanying drawings and detailed description.BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The accompanying drawings are presented to aid in the description of various aspects of the disclosure and are provided solely for illustration of the aspects and not limitation thereof.

[0011] FIG. 1 illustrates an example wireless communications system, according to aspects of the disclosure.

[0012] FIGS. 2 A, 2B, and 2C illustrate example wireless network structures, according to aspects of the disclosure.

[0013] FIGS. 3A, 3B, and 3C are simplified block diagrams of several sample aspects of components that may be employed in a user equipment (UE), a base station, and a network entity, respectively, and configured to support communications as taught herein.

[0014] FIG. 4 illustrates an example Long-Term Evolution (LTE) positioning protocol (LPP) capability transfer procedure, assistance data transfer procedure, and location information transfer procedure between a target device and a location server, according to aspects of the disclosure.

[0015] FIG. 5 illustrates an example neural network, according to aspects of the disclosure.

[0016] FIG. 6A is a diagram illustrating an example of classical positioning and / or sensing, according to aspects of the disclosure.

[0017] FIG. 6B is a diagram illustrating an example of direct artificial intelligence / machine learning (AIML) positioning and / or sensing, according to aspects of the disclosure.

[0018] FIG. 6C is a diagram illustrating an example of AIML assisted positioning and / or sensing, according to aspects of the disclosure.

[0019] FIG. 6D illustrates various AIML positioning and / or sensing scenarios, according to aspects of the disclosure.3QC2500148WOQualcomm Ref. No. 2500148WO4

[0020] FIG. 7 is a diagram illustrating an ellipsoid point with altitude and uncertainty ellipsoid, according to aspects of the disclosure.

[0021] FIGS. 8 A to 8D illustrate example information elements for various location information types and associated uncertainties, according to aspects of the disclosure.

[0022] FIG. 9 illustrates example information elements for various location information formats, according to aspects of the disclosure.

[0023] FIG. 10 illustrates an example method of data collection for a machine learning model for positioning performed, according to aspects of the disclosure.DETAILED DESCRIPTION

[0024] Aspects of the disclosure are provided in the following description and related drawings directed to various examples provided for illustration purposes. Alternate aspects may be devised without departing from the scope of the disclosure. Additionally, well-known elements of the disclosure will not be described in detail or will be omitted so as not to obscure the relevant details of the disclosure.

[0025] Various aspects relate generally to machine learning model positioning. Some aspects more specifically relate to signaling aspects for data collection labeling for machine learning model positioning. In some examples, a first device (e.g., a user equipment (UE) or location server) may receive a request from a second device (e.g., a location server or a UE) for labeling features for machine learning model positioning (including conditions, prioritization, resolution, accuracy, quality, source, etc.).

[0026] Particular aspects of the subject matter described in this disclosure can be implemented to realize one or more of the following potential advantages. In some examples, by obtaining the timestamping assistance information, the described techniques can be used to improve data collection for machine learning model positioning by enabling the correlation of the channel measurements for input into the machine learning model and the labels for output by the machine learning model based on the timestamping assistance information.

[0027] The words “exemplary” and / or “example” are used herein to mean “serving as an example, instance, or illustration.” Any aspect described herein as “exemplary” and / or “example” is not necessarily to be construed as preferred or advantageous over other4QC2500148WOQualcomm Ref. No. 2500148WO5 aspects. Likewise, the term “aspects of the disclosure” does not require that all aspects of the disclosure include the discussed feature, advantage or mode of operation.

[0028] Those of skill in the art will appreciate that the information and signals described below may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout the description below may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof, depending in part on the particular application, in part on the desired design, in part on the corresponding technology, etc.

[0029] Further, many aspects are described in terms of sequences of actions to be performed by, for example, elements of a computing device. It will be recognized that various actions described herein can be performed by specific circuits (e.g., application specific integrated circuits (ASICs)), by program instructions being executed by one or more processors, or by a combination of both. Additionally, the sequence(s) of actions described herein can be considered to be embodied entirely within any form of non- transitory computer-readable storage medium having stored therein a corresponding set of computer instructions that, upon execution, would cause or instruct an associated processor of a device to perform the functionality described herein. Thus, the various aspects of the disclosure may be embodied in a number of different forms, all of which have been contemplated to be within the scope of the claimed subject matter. In addition, for each of the aspects described herein, the corresponding form of any such aspects may be described herein as, for example, “logic configured to” perform the described action.

[0030] As used herein, the terms “user equipment” (UE) and “base station” are not intended to be specific or otherwise limited to any particular radio access technology (RAT), unless otherwise noted. In general, a UE may be any wireless communication device (e.g., a mobile phone, router, tablet computer, laptop computer, consumer asset locating device, wearable (e.g., smartwatch, glasses, augmented reality (AR) / virtual reality (VR) headset, etc.), vehicle (e.g., automobile, motorcycle, bicycle, etc.), Internet of Things (loT) device, etc.) used by a user to communicate over a wireless communications network. A UE may be mobile or may (e.g., at certain times) be stationary, and may communicate with a radio access network (RAN). As used herein, the term “UE” may be referred to interchangeably as an “access terminal” or “AT,” a “client device,” a “wireless device,” a “subscriber5QC2500148WOQualcomm Ref. No. 2500148WO6 device,” a “subscriber terminal,” a “subscriber station,” a “user terminal” or “UT,” a “mobile device,” a “mobile terminal,” a “mobile station,” or variations thereof. Generally, UEs can communicate with a core network via a RAN, and through the core network the UEs can be connected with external networks such as the Internet and with other UEs. Of course, other mechanisms of connecting to the core network and / or the Internet are also possible for the UEs, such as over wired access networks, wireless local area network (WLAN) networks (e.g., based on the Institute of Electrical and Electronics Engineers (IEEE) 802.11 specification, etc.) and so on.

[0031] A base station may operate according to one of several RATs in communication with UEs depending on the network in which it is deployed, and may be alternatively referred to as an access point (AP), a network node, a NodeB, an evolved NodeB (eNB), a next generation eNB (ng-eNB), a New Radio (NR) Node B (also referred to as a gNB or gNodeB), etc. A base station may be used primarily to support wireless access by UEs, including supporting data, voice, and / or signaling connections for the supported UEs. In some systems a base station may provide purely edge node signaling functions while in other systems it may provide additional control and / or network management functions. A communication link through which UEs can send signals to a base station is called an uplink (UL) channel (e.g., a reverse traffic channel, a reverse control channel, an access channel, etc.). A communication link through which the base station can send signals to UEs is called a downlink (DL) or forward link channel (e.g., a paging channel, a control channel, a broadcast channel, a forward traffic channel, etc.). As used herein the term traffic channel (TCH) can refer to either an uplink / reverse or downlink / forward traffic channel.

[0032] The term “base station” may refer to a single physical transmission-reception point (TRP) or to multiple physical TRPs that may or may not be co-located. For example, where the term “base station” refers to a single physical TRP, the physical TRP may be an antenna of the base station corresponding to a cell (or several cell sectors) of the base station. Where the term “base station” refers to multiple co-located physical TRPs, the physical TRPs may be an array of antennas (e.g., as in a multiple-input multiple-output (MIMO) system or where the base station employs beamforming) of the base station. Where the term “base station” refers to multiple non-co-located physical TRPs, the physical TRPs may be a distributed antenna system (DAS) (a network of spatially separated antennas6QC2500148WOQualcomm Ref. No. 2500148WO7 connected to a common source via a transport medium) or a remote radio head (RRH) (a remote base station connected to a serving base station). Alternatively, the non-co-located physical TRPs may be the serving base station receiving the measurement report from the UE and a neighbor base station whose reference radio frequency (RF) signals the UE is measuring. Because a TRP is the point from which a base station transmits and receives wireless signals, as used herein, references to transmission from or reception at a base station are to be understood as referring to a particular TRP of the base station.

[0033] In some implementations that support positioning of UEs, a base station may not support wireless access by UEs (e.g., may not support data, voice, and / or signaling connections for UEs), but may instead transmit reference signals to UEs to be measured by the UEs, and / or may receive and measure signals transmitted by the UEs. Such a base station may be referred to as a positioning beacon (e.g., when transmitting signals to UEs) and / or as a location measurement unit (e.g., when receiving and measuring signals from UEs).

[0034] An “RF signal” comprises an electromagnetic wave of a given frequency that transports information through the space between a transmitter and a receiver. As used herein, a transmitter may transmit a single “RF signal” or multiple “RF signals” to a receiver. However, the receiver may receive multiple “RF signals” corresponding to each transmitted RF signal due to the propagation characteristics of RF signals through multipath channels. The same transmitted RF signal on different paths between the transmitter and receiver may be referred to as a “multipath” RF signal. As used herein, an RF signal may also be referred to as a “wireless signal” or simply a “signal” where it is clear from the context that the term “signal” refers to a wireless signal or an RF signal.

[0035] FIG. 1 illustrates an example wireless communications system 100, according to aspects of the disclosure. The wireless communications system 100 (which may also be referred to as a wireless wide area network (WWAN)) may include various base stations 102 (labeled “BS”) and various UEs 104. The base stations 102 may include macro cell base stations (high power cellular base stations) and / or small cell base stations (low power cellular base stations). In an aspect, the macro cell base stations may include eNBs and / or ng-eNBs where the wireless communications system 100 corresponds to an LTE network, or gNBs where the wireless communications system 100 corresponds to a NR network, or a combination of both, and the small cell base stations may include femtocells, picocells, microcells, etc.7QC2500148WOQualcomm Ref. No. 2500148WO8

[0036] The base stations 102 may collectively form a RAN and interface with a core network 170 (e.g., an evolved packet core (EPC) or a 5G core (5GC)) through backhaul links 122, and through the core network 170 to one or more location servers 172 (e.g., a location management function (LMF) or a secure user plane location (SUPL) location platform (SLP)). The location server(s) 172 may be part of core network 170 or may be external to core network 170. A location server 172 may be integrated with a base station 102. A UE 104 may communicate with a location server 172 directly or indirectly. For example, a UE 104 may communicate with a location server 172 via the base station 102 that is currently serving that UE 104. A UE 104 may also communicate with a location server 172 through another path, such as via an application server (not shown), via another network, such as via a wireless local area network (WLAN) access point (AP) (e.g., AP 150 described below), and so on. For signaling purposes, communication between a UE 104 and a location server 172 may be represented as an indirect connection (e.g., through the core network 170, etc.) or a direct connection (e.g., as shown via direct connection 128), with the intervening nodes (if any) omitted from a signaling diagram for clarity.

[0037] In addition to other functions, the base stations 102 may perform functions that relate to one or more of transferring user data, radio channel ciphering and deciphering, integrity protection, header compression, mobility control functions (e.g., handover, dual connectivity), inter-cell interference coordination, connection setup and release, load balancing, distribution for non-access stratum (NAS) messages, NAS node selection, synchronization, RAN sharing, multimedia broadcast multicast service (MBMS), subscriber and equipment trace, RAN information management (RIM), paging, positioning, and delivery of warning messages. The base stations 102 may communicate with each other directly or indirectly (e.g., through the EPC / 5GC) over backhaul links 134, which may be wired or wireless.

[0038] The base stations 102 may wirelessly communicate with the UEs 104. Each of the base stations 102 may provide communication coverage for a respective geographic coverage area 110. In an aspect, one or more cells may be supported by a base station 102 in each geographic coverage area 110. A “cell” is a logical communication entity used for communication with a base station (e.g., over some frequency resource, referred to as a carrier frequency, component carrier, carrier, band, or the like), and may be associated with an identifier (e.g., a physical cell identifier (PCI), an enhanced cell identifier (ECI),8QC2500148WOQualcomm Ref. No. 2500148WO9 a virtual cell identifier (VCI), a cell global identifier (CGI), etc.) for distinguishing cells operating via the same or a different carrier frequency. In some cases, different cells may be configured according to different protocol types (e.g., machine-type communication (MTC), narrowband loT (NB-IoT), enhanced mobile broadband (eMBB), or others) that may provide access for different types of UEs. Because a cell is supported by a specific base station, the term “cell” may refer to either or both of the logical communication entity and the base station that supports it, depending on the context. In addition, because a TRP is typically the physical transmission point of a cell, the terms “cell” and “TRP” may be used interchangeably. In some cases, the term “cell” may also refer to a geographic coverage area of a base station (e.g., a sector), insofar as a carrier frequency can be detected and used for communication within some portion of geographic coverage areas 110.

[0039] While neighboring macro cell base station 102 geographic coverage areas 110 may partially overlap (e.g., in a handover region), some of the geographic coverage areas 110 may be substantially overlapped by a larger geographic coverage area 110. For example, a small cell base station 102' (labeled “SC” for “small cell”) may have a geographic coverage area 110' that substantially overlaps with the geographic coverage area 110 of one or more macro cell base stations 102. A network that includes both small cell and macro cell base stations may be known as a heterogeneous network. A heterogeneous network may also include home eNBs (HeNBs), which may provide service to a restricted group known as a closed subscriber group (CSG).

[0040] The communication links 120 between the base stations 102 and the UEs 104 may include uplink (also referred to as reverse link) transmissions from a UE 104 to a base station 102 and / or downlink (DL) (also referred to as forward link) transmissions from a base station 102 to a UE 104. The communication links 120 may use MIMO antenna technology, including spatial multiplexing, beamforming, and / or transmit diversity. The communication links 120 may be through one or more carrier frequencies. Allocation of carriers may be asymmetric with respect to downlink and uplink (e.g., more or less carriers may be allocated for downlink than for uplink).

[0041] The wireless communications system 100 may further include a wireless local area network (WLAN) access point (AP) 150 in communication with WLAN stations (STAs) 152 via communication links 154 in an unlicensed frequency spectrum (e.g., 5 GHz).9QC2500148WOQualcomm Ref. No. 2500148WO10When communicating in an unlicensed frequency spectrum, the WLAN STAs 152 and / or the WLAN AP 150 may perform a clear channel assessment (CCA) or listen before talk (LBT) procedure prior to communicating in order to determine whether the channel is available.

[0042] The small cell base station 102' may operate in a licensed and / or an unlicensed frequency spectrum. When operating in an unlicensed frequency spectrum, the small cell base station 102' may employ LTE or NR technology and use the same 5 GHz unlicensed frequency spectrum as used by the WLAN AP 150. The small cell base station 102', employing LTE / 5G in an unlicensed frequency spectrum, may boost coverage to and / or increase capacity of the access network. NR in unlicensed spectrum may be referred to as NR-U. LTE in an unlicensed spectrum may be referred to as LTE-U, licensed assisted access (LAA), or MULTEFIRE®.

[0043] The wireless communications system 100 may further include a millimeter wave (mmW) base station 180 that may operate in mmW frequencies and / or near mmW frequencies in communication with a UE 182. Extremely high frequency (EHF) is part of the RF in the electromagnetic spectrum. EHF has a range of 30 GHz to 300 GHz and a wavelength between 1 millimeter and 10 millimeters. Radio waves in this band may be referred to as a millimeter wave. Near mmW may extend down to a frequency of 3 GHz with a wavelength of 100 millimeters. The super high frequency (SHF) band extends between 3 GHz and 30 GHz, also referred to as centimeter wave. Communications using the mmW / near mmW radio frequency band have high path loss and a relatively short range. The mmW base station 180 and the UE 182 may utilize beamforming (transmit and / or receive) over a mmW communication link 184 to compensate for the extremely high path loss and short range. Further, it will be appreciated that in alternative configurations, one or more base stations 102 may also transmit using mmW or near mmW and beamforming. Accordingly, it will be appreciated that the foregoing illustrations are merely examples and should not be construed to limit the various aspects disclosed herein.

[0044] Transmit beamforming is a technique for focusing an RF signal in a specific direction. Traditionally, when a network node (e.g., a base station) broadcasts an RF signal, it broadcasts the signal in all directions (omni-directionally). With transmit beamforming, the network node determines where a given target device (e.g., a UE) is located (relative to the transmitting network node) and projects a stronger downlink RF signal in that10QC2500148WOQualcomm Ref. No. 2500148WO11 specific direction, thereby providing a faster (in terms of data rate) and stronger RF signal for the receiving device(s). To change the directionality of the RF signal when transmitting, a network node can control the phase and relative amplitude of the RF signal at each of the one or more transmitters that are broadcasting the RF signal. For example, a network node may use an array of antennas (referred to as a “phased array” or an “antenna array”) that creates a beam of RF waves that can be “steered” to point in different directions, without actually moving the antennas. Specifically, the RF current from the transmitter is fed to the individual antennas with the correct phase relationship so that the radio waves from the separate antennas add together to increase the radiation in a desired direction, while cancelling to suppress radiation in undesired directions.

[0045] Transmit beams may be quasi-co-located, meaning that they appear to the receiver (e.g., a UE) as having the same parameters, regardless of whether or not the transmitting antennas of the network node themselves are physically co-located. In NR, there are four types of quasi -co-1 ocati on (QCL) relations. Specifically, a QCL relation of a given type means that certain parameters about a second reference RF signal on a second beam can be derived from information about a source reference RF signal on a source beam. Thus, if the source reference RF signal is QCL Type A, the receiver can use the source reference RF signal to estimate the Doppler shift, Doppler spread, average delay, and delay spread of a second reference RF signal transmitted on the same channel. If the source reference RF signal is QCL Type B, the receiver can use the source reference RF signal to estimate the Doppler shift and Doppler spread of a second reference RF signal transmitted on the same channel. If the source reference RF signal is QCL Type C, the receiver can use the source reference RF signal to estimate the Doppler shift and average delay of a second reference RF signal transmitted on the same channel. If the source reference RF signal is QCL Type D, the receiver can use the source reference RF signal to estimate the spatial receive parameter of a second reference RF signal transmitted on the same channel.

[0046] In receive beamforming, the receiver uses a receive beam to amplify RF signals detected on a given channel. For example, the receiver can increase the gain setting and / or adjust the phase setting of an array of antennas in a particular direction to amplify (e.g., to increase the gain level of) the RF signals received from that direction. Thus, when a receiver is said to beamform in a certain direction, it means the beam gain in that direction is high relative to the beam gain along other directions, or the beam gain in that direction11QC2500148WOQualcomm Ref. No. 2500148WO12 is the highest compared to the beam gain in that direction of all other receive beams available to the receiver. This results in a stronger received signal strength (e.g., reference signal received power (RSRP), reference signal received quality (RSRQ), signal -to- interference-plus-noise ratio (SINR), etc.) of the RF signals received from that direction.

[0047] Transmit and receive beams may be spatially related. A spatial relation means that parameters for a second beam (e.g., a transmit or receive beam) for a second reference signal can be derived from information about a first beam (e.g., a receive beam or a transmit beam) for a first reference signal. For example, a UE may use a particular receive beam to receive a reference downlink reference signal (e.g., synchronization signal block (SSB)) from a base station. The UE can then form a transmit beam for sending an uplink reference signal (e.g., sounding reference signal (SRS)) to that base station based on the parameters of the receive beam.

[0048] Note that a “downlink” beam may be either a transmit beam or a receive beam, depending on the entity forming it. For example, if a base station is forming the downlink beam to transmit a reference signal to a UE, the downlink beam is a transmit beam. If the UE is forming the downlink beam, however, it is a receive beam to receive the downlink reference signal. Similarly, an “uplink” beam may be either a transmit beam or a receive beam, depending on the entity forming it. For example, if a base station is forming the uplink beam, it is an uplink receive beam, and if a UE is forming the uplink beam, it is an uplink transmit beam.

[0049] The electromagnetic spectrum is often subdivided, based on frequency / wavelength, into various classes, bands, channels, etc. In 5G NR 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). It should be understood that although a portion of FR1 is greater than 6 GHz, FR1 is often referred to (interchangeably) as a “Sub-6 GHz” band in various documents and articles. A similar nomenclature issue sometimes occurs with regard to FR2, which is often referred to (interchangeably) as a “millimeter wave” band in documents and articles, despite being different from the extremely high frequency (EHF) band (30 GHz - 300 GHz) which is identified by the INTERNATIONAL TELECOMMUNICATION UNION® as a “millimeter wave” band.

[0050] The frequencies between FR1 and FR2 are often referred to as mid-band frequencies.Recent 5G NR studies have identified an operating band for these mid-band frequencies12QC2500148WOQualcomm Ref. No. 2500148WO13 as frequency range designation FR3 (7.125 GHz - 24.25 GHz). Frequency bands falling within FR3 may inherit FR1 characteristics and / or FR2 characteristics, and thus may effectively extend features of FR1 and / or FR2 into mid-band frequencies. In addition, higher frequency bands are currently being explored to extend 5G NR operation beyond 52.6 GHz. For example, three higher operating bands have been identified as frequency range designations FR4a or FR4-1 (52.6 GHz - 71 GHz), FR4 (52.6 GHz - 114.25 GHz), and FR5 (114.25 GHz - 300 GHz). Each of these higher frequency bands falls within the EHF band.

[0051] With the above aspects in mind, unless specifically stated otherwise, it should be understood that the term “sub-6 GHz” or the like if used herein may broadly represent frequencies that may be less than 6 GHz, may be within FR1, or may include mid-band frequencies. Further, unless specifically stated otherwise, it should be understood that 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, FR4-a or FR4-1, and / or FR5, or may be within the EHF band.

[0052] In a multi-carrier system, such as 5G, one of the carrier frequencies is referred to as the “primary carrier” or “anchor carrier” or “primary serving cell” or “PCell,” and the remaining carrier frequencies are referred to as “secondary carriers” or “secondary serving cells” or “SCells.” In carrier aggregation, the anchor carrier is the carrier operating on the primary frequency (e.g., FR1) utilized by a UE 104 / 182 and the cell in which the UE 104 / 182 either performs the initial radio resource control (RRC) connection establishment procedure or initiates the RRC connection re-establishment procedure. The primary carrier carries all common and UE-specific control channels, and may be a carrier in a licensed frequency (however, this is not always the case). A secondary carrier is a carrier operating on a second frequency (e.g., FR2) that may be configured once the RRC connection is established between the UE 104 and the anchor carrier and that may be used to provide additional radio resources. In some cases, the secondary carrier may be a carrier in an unlicensed frequency. The secondary carrier may contain only necessary signaling information and signals, for example, those that are UE-specific may not be present in the secondary carrier, since both primary uplink and downlink carriers are typically UE-specific. This means that different UEs 104 / 182 in a cell may have different downlink primary carriers. The same is true for the uplink primary carriers. The network13QC2500148WOQualcomm Ref. No. 2500148WO14 is able to change the primary carrier of any UE 104 / 182 at any time. This is done, for example, to balance the load on different carriers. Because a “serving cell” (whether a PCell or an SCell) corresponds to a carrier frequency / component carrier over which some base station is communicating, the term “cell,” “serving cell,” “component carrier,” “carrier frequency,” and the like can be used interchangeably.

[0053] For example, still referring to FIG. 1, one of the frequencies utilized by the macro cell base stations 102 may be an anchor carrier (or “PCell”) and other frequencies utilized by the macro cell base stations 102 and / or the mmW base station 180 may be secondary carriers (“SCells”). The simultaneous transmission and / or reception of multiple carriers enables the UE 104 / 182 to significantly increase its data transmission and / or reception rates. For example, two 20 MHz aggregated carriers in a multi-carrier system would theoretically lead to a two-fold increase in data rate (i.e., 40 MHz), compared to that attained by a single 20 MHz carrier.

[0054] The wireless communications system 100 may further include a UE 164 that may communicate with a macro cell base station 102 over a communication link 120 and / or the mmW base station 180 over a mmW communication link 184. For example, the macro cell base station 102 may support a PCell and one or more SCells for the UE 164 and the mmW base station 180 may support one or more SCells for the UE 164.

[0055] In some cases, the UE 164 and the UE 182 may be capable of sidelink communication. Sidelink-capable UEs (SL-UEs) may communicate with base stations 102 over communication links 120 using the Uu interface (i.e., the air interface between a UE and abase station). SL-UEs (e.g., UE 164, UE 182) may also communicate directly with each other over a wireless sidelink 160 using the PC5 interface (i.e., the air interface between sidelink-capable UEs). A wireless sidelink (or just “sidelink”) is an adaptation of the core cellular (e.g., LTE, NR) standard that allows direct communication between two or more UEs without the communication needing to go through a base station. Sidelink communication may be unicast or multicast, and may be used for device-to-device (D2D) media-sharing, vehicle-to-vehicle (V2V) communication, vehicle-to-everything (V2X) communication (e.g., cellular V2X (cV2X) communication, enhanced V2X (eV2X) communication, etc.), emergency rescue applications, etc. One or more of a group of SL- UEs utilizing sidelink communications may be within the geographic coverage area 110 of a base station 102. Other SL-UEs in such a group may be outside the geographic14QC2500148WOQualcomm Ref. No. 2500148WO15 coverage area 110 of a base station 102 or be otherwise unable to receive transmissions from a base station 102. In some cases, groups of SL-UEs communicating via sidelink communications may utilize a one-to-many (1 :M) system in which each SL-UE transmits to every other SL-UE in the group. In some cases, a base station 102 facilitates the scheduling of resources for sidelink communications. In other cases, sidelink communications are carried out between SL-UEs without the involvement of a base station 102.

[0056] In an aspect, the sidelink 160 may operate over a wireless communication medium of interest, which may be shared with other wireless communications between other vehicles and / or infrastructure access points, as well as other RATs. A “medium” may be composed of one or more time, frequency, and / or space communication resources (e.g., encompassing one or more channels across one or more carriers) associated with wireless communication between one or more transmitter / receiver pairs. In an aspect, the medium of interest may correspond to at least a portion of an unlicensed frequency band shared among various RATs. Although different licensed frequency bands have been reserved for certain communication systems (e.g., by a government entity such as the Federal Communications Commission (FCC) in the United States), these systems, in particular those employing small cell access points, have recently extended operation into unlicensed frequency bands such as the Unlicensed National Information Infrastructure (U-NII) band used by wireless local area network (WLAN) technologies, most notably IEEE 802.1 lx WLAN technologies generally referred to as “Wi-Fi.” Example systems of this type include different variants of CDMA systems, TDMA systems, FDMA systems, orthogonal FDMA (OFDMA) systems, single-carrier FDMA (SC-FDMA) systems, and so on.

[0057] Note that although FIG. 1 only illustrates two of the UEs as SL-UEs (i.e., UEs 164 and 182), any of the illustrated UEs may be SL-UEs. Further, although only UE 182 was described as being capable of beamforming, any of the illustrated UEs, including UE 164, may be capable of beamforming. Where SL-UEs are capable of beamforming, they may beamform towards each other (i.e., towards other SL-UEs), towards other UEs (e.g., UEs 104), towards base stations (e.g., base stations 102, 180, small cell 102’, access point 150), etc. Thus, in some cases, UEs 164 and 182 may utilize beamforming over sidelink 160.15QC2500148WOQualcomm Ref. No. 2500148WO16

[0058] In the example of FIG. 1, any of the illustrated UEs (shown in FIG. 1 as a single UE 104 for simplicity) may receive signals 124 from one or more Earth orbiting space vehicles (SVs) 112 (e.g., satellites). In an aspect, the S Vs 112 may be part of a satellite positioning system that aUE 104 can use as an independent source of location information. A satellite positioning system typically includes a system of transmitters (e.g., SVs 112) positioned to enable receivers (e.g., UEs 104) to determine their location on or above the Earth based, at least in part, on positioning signals (e.g., signals 124) received from the transmitters. Such a transmitter typically transmits a signal marked with a repeating pseudo-random noise (PN) code of a set number of chips. While typically located in SVs 112, transmitters may sometimes be located on ground-based control stations, base stations 102, and / or other UEs 104. A UE 104 may include one or more dedicated receivers specifically designed to receive signals 124 for deriving geo location information from the SVs 112.

[0059] In a satellite positioning system, the use of signals 124 can be augmented by various satellite-based augmentation systems (SBAS) that may be associated with or otherwise enabled for use with one or more global and / or regional navigation satellite systems. For example an SBAS may include an augmentation system(s) that provides integrity information, differential corrections, etc., such as the Wide Area Augmentation System (WAAS), the European Geostationary Navigation Overlay Service (EGNOS), the Multifunctional Satellite Augmentation System (MSAS), the Global Positioning System (GPS) Aided Geo Augmented Navigation or GPS and Geo Augmented Navigation system (GAGAN), and / or the like. Thus, as used herein, a satellite positioning system may include any combination of one or more global and / or regional navigation satellites associated with such one or more satellite positioning systems.

[0060] In an aspect, SVs 112 may additionally or alternatively be part of one or more nonterrestrial networks (NTNs). In an NTN, an SV 112 is connected to an earth station (also referred to as a ground station, NTN gateway, or gateway), which in turn is connected to an element in a 5G network, such as a modified base station 102 (without a terrestrial antenna) or a network node in a 5GC. This element would in turn provide access to other elements in the 5G network and ultimately to entities external to the 5G network, such as Internet web servers and other user devices. In that way, a UE 104 may receive communication signals (e.g., signals 124) from an SV 112 instead of, or in addition to, communication signals from a terrestrial base station 102.16QC2500148WOQualcomm Ref. No. 2500148WO17

[0061] The wireless communications system 100 may further include one or more UEs, such as UE 190, that connects indirectly to one or more communication networks via one or more device-to-device (D2D) peer-to-peer (P2P) links (referred to as “sidelinks”). In the example of FIG. 1, UE 190 has a D2D P2P link 192 with one of the UEs 104 connected to one of the base stations 102 (e.g., through which UE 190 may indirectly obtain cellular connectivity) and a D2D P2P link 194 with WLAN STA 152 connected to the WLAN AP 150 (through which UE 190 may indirectly obtain WLAN-based Internet connectivity). In an example, the D2D P2P links 192 and 194 may be supported with any well-known D2D RAT, such as LTE Direct (LTE-D), WI-FI DIRECT®, BLUETOOTH®, and so on.

[0062] FIG. 2A illustrates an example wireless network structure 200. For example, a 5GC 210 (also referred to as a Next Generation Core (NGC)) can be viewed functionally as control plane (C-plane) functions 214 (e.g., UE registration, authentication, network access, gateway selection, etc.) and user plane (U-plane) functions 212, (e.g., UE gateway function, access to data networks, IP routing, etc.) which operate cooperatively to form the core network. User plane interface (NG-U) 213 and control plane interface (NG-C) 215 connect the gNB 222 to the 5GC 210 and specifically to the user plane functions 212 and control plane functions 214, respectively. In an additional configuration, an ng-eNB 224 may also be connected to the 5GC 210 via NG-C 215 to the control plane functions 214 and NG-U 213 to user plane functions 212. Further, ng-eNB 224 may directly communicate with gNB 222 via a backhaul connection 223. In some configurations, a Next Generation RAN (NG-RAN) 220 may have one or more gNBs 222, while other configurations include one or more of both ng-eNBs 224 and gNBs 222. Either (or both) gNB 222 or ng-eNB 224 may communicate with one or more UEs 204 (e.g., any of the UEs described herein).

[0063] Another optional aspect may include a location server 230, which may be in communication with the 5GC 210 to provide location assistance for UE(s) 204. The location server 230 can be implemented as a plurality of separate servers (e.g., physically separate servers, different software modules on a single server, different software modules spread across multiple physical servers, etc.), or alternately may each correspond to a single server. The location server 230 can be configured to support one or more location services for UEs 204 that can connect to the location server 230 via the core17QC2500148WOQualcomm Ref. No. 2500148WO18 network, 5GC 210, and / or via the Internet (not illustrated). Further, the location server 230 may be integrated into a component of the core network, or alternatively may be external to the core network (e.g., a third party server, such as an original equipment manufacturer (OEM) server or service server).

[0064] FIG. 2B illustrates another example wireless network structure 240. A 5GC 260 (which may correspond to 5GC 210 in FIG. 2A) can be viewed functionally as control plane functions, provided by an access and mobility management function (AMF) 264, and user plane functions, provided by a user plane function (UPF) 262, which operate cooperatively to form the core network (i.e., 5GC 260). The functions of the AMF 264 include registration management, connection management, reachability management, mobility management, lawful interception, transport for session management (SM) messages between one or more UEs 204 (e.g., any of the UEs described herein) and a session management function (SMF) 266, transparent proxy services for routing SM messages, access authentication and access authorization, transport for short message service (SMS) messages between the UE 204 and the short message service function (SMSF) (not shown), and security anchor functionality (SEAF). The AMF 264 also interacts with an authentication server function (AUSF) (not shown) and the UE 204, and receives the intermediate key that was established as a result of the UE 204 authentication process. In the case of authentication based on a UMTS (universal mobile telecommunications system) subscriber identity module (USIM), the AMF 264 retrieves the security material from the AUSF. The functions of the AMF 264 also include security context management (SCM). The SCM receives a key from the SEAF that it uses to derive access-network specific keys. The functionality of the AMF 264 also includes location services management for regulatory services, transport for location services messages between the UE 204 and a location management function (LMF) 270 (which acts as a location server 230), transport for location services messages between the NG-RAN 220 and the LMF 270, evolved packet system (EPS) bearer identifier allocation for interworking with the EPS, and UE 204 mobility event notification. In addition, the AMF 264 also supports functionalities for non-3GPP® (Third Generation Partnership Project) access networks.

[0065] Functions of the UPF 262 include acting as an anchor point for intra / inter-RAT mobility (when applicable), acting as an external protocol data unit (PDU) session point of18QC2500148WOQualcomm Ref. No. 2500148WO19 interconnect to a data network (not shown), providing packet routing and forwarding, packet inspection, user plane policy rule enforcement (e.g., gating, redirection, traffic steering), lawful interception (user plane collection), traffic usage reporting, quality of service (QoS) handling for the user plane (e.g., uplink / downlink rate enforcement, reflective QoS marking in the downlink), uplink traffic verification (service data flow (SDF) to QoS flow mapping), transport level packet marking in the uplink and downlink, downlink packet buffering and downlink data notification triggering, and sending and forwarding of one or more “end markers” to the source RAN node. The UPF 262 may also support transfer of location services messages over a user plane between the UE 204 and a location server, such as an SLP 272.

[0066] The functions of the SMF 266 include session management, UE Internet protocol (IP) address allocation and management, selection and control of user plane functions, configuration of traffic steering at the UPF 262 to route traffic to the proper destination, control of part of policy enforcement and QoS, and downlink data notification. The interface over which the SMF 266 communicates with the AMF 264 is referred to as the Ni l interface.

[0067] Another optional aspect may include an LMF 270, which may be in communication with the 5GC 260 to provide location assistance for UEs 204. The LMF 270 can be implemented as a plurality of separate servers (e.g., physically separate servers, different software modules on a single server, different software modules spread across multiple physical servers, etc.), or alternately may each correspond to a single server. The LMF 270 can be configured to support one or more location services for UEs 204 that can connect to the LMF 270 via the core network, 5GC 260, and / or via the Internet (not illustrated). The SLP 272 may support similar functions to the LMF 270, but whereas the LMF 270 may communicate with the AMF 264, NG-RAN 220, and UEs 204 over a control plane (e.g., using interfaces and protocols intended to convey signaling messages and not voice or data), the SLP 272 may communicate with UEs 204 and external clients (e.g., third-party server 274) over a user plane (e.g., using protocols intended to carry voice and / or data like the transmission control protocol (TCP) and / or IP).

[0068] Yet another optional aspect may include a third-party server 274, which may be in communication with the LMF 270, the SLP 272, the 5GC 260 (e.g., via the AMF 264 and / or the UPF 262), the NG-RAN 220, and / or the UE 204 to obtain location information19QC2500148WOQualcomm Ref. No. 2500148WO20(e.g., a location estimate) for the UE 204. As such, in some cases, the third-party server 274 may be referred to as a location services (LCS) client or an external client. The third- party server 274 can be implemented as a plurality of separate servers (e.g., physically separate servers, different software modules on a single server, different software modules spread across multiple physical servers, etc.), or alternately may each correspond to a single server.

[0069] User plane interface 263 and control plane interface 265 connect the 5GC 260, and specifically the UPF 262 and AMF 264, respectively, to one or more gNBs 222 and / or ng-eNBs 224 in the NG-RAN 220. The interface between gNB(s) 222 and / or ng-eNB(s) 224 and the AMF 264 is referred to as the “N2” interface, and the interface between gNB(s) 222 and / or ng-eNB(s) 224 and the UPF 262 is referred to as the “N3” interface. The gNB(s) 222 and / or ng-eNB(s) 224 of the NG-RAN 220 may communicate directly with each other via backhaul connections 223, referred to as the “Xn-C” interface. One or more of gNBs 222 and / or ng-eNBs 224 may communicate with one or more UEs 204 over a wireless interface, referred to as the “Uu” interface.

[0070] The functionality of a gNB 222 may be divided between a gNB central unit (gNB-CU) 226, one or more gNB distributed units (gNB-DUs) 228, and one or more gNB radio units (gNB-RUs) 229. A gNB-CU 226 is a logical node that includes the base station functions of transferring user data, mobility control, radio access network sharing, positioning, session management, and the like, except for those functions allocated exclusively to the gNB-DU(s) 228. More specifically, the gNB-CU 226 generally host the radio resource control (RRC), service data adaptation protocol (SDAP), and packet data convergence protocol (PDCP) protocols of the gNB 222. A gNB-DU 228 is a logical node that generally hosts the radio link control (RLC) and medium access control (MAC) layer of the gNB 222. Its operation is controlled by the gNB-CU 226. One gNB-DU 228 can support one or more cells, and one cell is supported by only one gNB-DU 228. The interface 232 between the gNB-CU 226 and the one or more gNB-DUs 228 is referred to as the “Fl” interface. The physical (PHY) layer functionality of a gNB 222 is generally hosted by one or more standalone gNB-RUs 229 that perform functions such as power amplification and signal transmission / reception. The interface between a gNB-DU 228 and a gNB-RU 229 is referred to as the “Fx” interface. Thus, a UE 204 communicates20QC2500148WOQualcomm Ref. No. 2500148WO21 with the gNB-CU 226 via the RRC, SDAP, and PDCP layers, with a gNB-DU 228 via the RLC and MAC layers, and with a gNB-RU 229 via the PHY layer.

[0071] Deployment of communication systems, such as 5G NR 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 RAN node, a core network node, a network element, or a network equipment, such as a base station, 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 base station (such as a Node B (NB), evolved NB (eNB), NR base station, 5G NB, AP, TRP, cell, etc.) may be implemented as an aggregated base station (also known as a standalone base station or a monolithic base station) or a disaggregated base station.

[0072] An aggregated base station may be configured to utilize a radio protocol stack that is physically or logically integrated within a single RAN node. A disaggregated base station may be configured to utilize a protocol stack that is physically or logically distributed among two or more units (such as one or more central or centralized units (CUs), one or more distributed units (DUs), or one or more radio units (RUs)). In some aspects, a CU may be implemented within a RAN node, and one or more DUs may be co-located with the CU, or alternatively, may be geographically or virtually distributed throughout one or multiple other RAN nodes. The DUs may be implemented to communicate with one or more RUs. Each of the CU, DU and RU also can be implemented as virtual units, i.e., a virtual central unit (VCU), a virtual distributed unit (VDU), or a virtual radio unit (VRU).

[0073] Base station-type 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 (0-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.21QC2500148WOQualcomm Ref. No. 2500148WO22

[0074] FIG. 2C illustrates an example disaggregated base station architecture 250, according to aspects of the disclosure. The disaggregated base station architecture 250 may include one or more central units (CUs) 280 (e.g., gNB-CU 226) that can communicate directly with a core network 267 (e.g., 5GC 210, 5GC 260) via a backhaul link, or indirectly with the core network 267 through one or more disaggregated base station units (such as a Near-Real Time (Near-RT) RAN Intelligent Controller (RIC) 259 via an E2 link, or a Non-Real Time (Non-RT) RIC 257 associated with a Service Management and Orchestration (SMO) Framework 255, or both). A CU 280 may communicate with one or more DUs 285 (e.g., gNB-DUs 228) via respective midhaul links, such as an Fl interface. The DUs 285 may communicate with one or more radio units (RUs) 287 (e.g., gNB-RUs 229) via respective fronthaul links. The RUs 287 may communicate with respective UEs 204 via one or more radio frequency (RF) access links. In some implementations, the UE 204 may be simultaneously served by multiple RUs 287.

[0075] Each of the units, i.e., the CUs 280, the DUs 285, the RUs 287, as well as the Near-RT RICs 259, the Non-RT RICs 257 and the SMO Framework 255, may include one or more interfaces or be coupled to one or more interfaces configured to receive or 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 transmit signals over a wired transmission medium to one or more of the other units. Additionally, the units can include a wireless interface, which may include a receiver, a transmitter or transceiver (such as a RF transceiver), configured to receive or transmit signals, or both, over a wireless transmission medium to one or more of the other units.

[0076] In some aspects, the CU 280 may host one or more higher layer control functions. Such control functions can include RRC, 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 280. The CU 280 may be configured to handle user plane functionality (i.e., Central Unit - User Plane (CU- UP)), control plane functionality (i.e., Central Unit - Control Plane (CU-CP)), or a combination thereof. In some implementations, the CU 280 can be logically split into22QC2500148WOQualcomm Ref. No. 2500148WO23 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 the El interface when implemented in an O-RAN configuration. The CU 280 can be implemented to communicate with the DU 285, as necessary, for network control and signaling.

[0077] The DU 285 may correspond to a logical unit that includes one or more base station functions to control the operation of one or more RUs 287. In some aspects, the DU 285 may host one or more of a RLC layer, a MAC layer, and one or more high PHY layers (such as modules for forward error correction (FEC) encoding and decoding, scrambling, modulation and demodulation, or the like) depending, at least in part, on a functional split, such as those defined by the 3rd Generation Partnership Project (3GPP®). In some aspects, the DU 285 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 285, or with the control functions hosted by the CU 280.

[0078] Lower-layer functionality can be implemented by one or more RUs 287. In some deployments, an RU 287, controlled by a DU 285, may correspond to a logical node that hosts RF processing functions, or low-PHY layer functions (such as performing fast Fourier transform (FFT), inverse FFT (iFFT), digital beamforming, physical random access channel (PRACH) extraction and filtering, or the like), or both, based at least in part on the functional split, such as a lower layer functional split. In such an architecture, the RU(s) 287 can be implemented to handle over the air (OTA) communication with one or more UEs 204. In some implementations, real-time and non-real-time aspects of control and user plane communication with the RU(s) 287 can be controlled by the corresponding DU 285. In some scenarios, this configuration can enable the DU(s) 285 and the CU 280 to be implemented in a cloud-based RAN architecture, such as a vRAN architecture.

[0079] The SMO Framework 255 may be configured to support RAN deployment and provisioning of non-virtualized and virtualized network elements. For non-virtualized network elements, the SMO Framework 255 may be configured to support the deployment of dedicated physical resources for RAN coverage requirements which may be managed via an operations and maintenance interface (such as an 01 interface). For23QC2500148WOQualcomm Ref. No. 2500148WO24 virtualized network elements, the SMO Framework 255 may be configured to interact with a cloud computing platform (such as an open cloud (O-Cloud) 269) 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 280, DUs 285, RUs 287 and Near-RT RICs 259. In some implementations, the SMO Framework 255 can communicate with a hardware aspect of a 4G RAN, such as an open eNB (O-eNB) 261, via an 01 interface. Additionally, in some implementations, the SMO Framework 255 can communicate directly with one or more RUs 287 via an 01 interface. The SMO Framework 255 also may include a Non-RT RIC 257 configured to support functionality of the SMO Framework 255.

[0080] The Non-RT RIC 257 may be configured to include a logical function that enables non- real-time control and optimization of RAN elements and resources, artificial intelligence / machine learning (AIML) workflows including model training and updates, or policy-based guidance of applications / features in the Near-RT RIC 259. The Non-RT RIC 257 may be coupled to or communicate with (such as via an Al interface) the Near- RT RIC 259. The Near-RT RIC 259 may be configured to include a logical function that enables near-real-time control and optimization of RAN elements and resources via data collection and actions over an interface (such as via an E2 interface) connecting one or more CUs 280, one or more DUs 285, or both, as well as an O-eNB, with the Near-RT RIC 259.

[0081] In some implementations, to generate AIML models to be deployed in the Near-RT RIC 259, the Non-RT RIC 257 may receive parameters or external enrichment information from external servers. Such information may be utilized by the Near-RT RIC 259 and may be received at the SMO Framework 255 or the Non-RT RIC 257 from non-network data sources or from network functions. In some examples, the Non-RT RIC 257 or the Near-RT RIC 259 may be configured to tune RAN behavior or performance. For example, the Non-RT RIC 257 may monitor long-term trends and patterns for performance and employ AIML models to perform corrective actions through the SMO Framework 255 (such as reconfiguration via 01) or via creation of RAN management policies (such as Al policies).24QC2500148WOQualcomm Ref. No. 2500148WO25

[0082] FIGS. 3A, 3B, and 3C illustrate several example components (represented by corresponding blocks) that may be incorporated into a UE 302 (which may correspond to any of the UEs described herein), a base station 304 (which may correspond to any of the base stations described herein), and a network entity 306 (which may correspond to or embody any of the network functions described herein, including the location server 230 and the LMF 270, or alternatively may be independent from the NG-RAN 220 and / or 5GC 210 / 260 infrastructure depicted in FIGS. 2 A and 2B, such as a private network) to support the operations described herein. It will be appreciated that these components may be implemented in different types of apparatuses in different implementations (e.g., in an ASIC, in a system-on-chip (SoC), etc.). The illustrated components may also be incorporated into other apparatuses in a communication system. For example, other apparatuses in a system may include components similar to those described to provide similar functionality. Also, a given apparatus may contain one or more of the components. For example, an apparatus may include multiple transceiver components that enable the apparatus to operate on multiple carriers and / or communicate via different technologies.

[0083] The UE 302 and the base station 304 each include one or more wireless wide area network (WWAN) transceivers 310 and 350, respectively, providing means for communicating (e.g., means for transmitting, means for receiving, means for measuring, means fortuning, means for refraining from transmitting, etc.) via one or more wireless communication networks (not shown), such as an NR network, an LTE network, a GSM network, and / or the like. The WWAN transceivers 310 and 350 may each be connected to one or more antennas 316 and 356, respectively, for communicating with other network nodes, such as other UEs, access points, base stations (e.g., eNBs, gNBs), etc., via at least one designated RAT (e.g., NR, LTE, GSM, etc.) over a wireless communication medium of interest (e.g., some set of time / frequency resources in a particular frequency spectrum). The WWAN transceivers 310 and 350 may be variously configured for transmitting and encoding signals 318 and 358 (e.g., messages, indications, information, and so on), respectively, and, conversely, for receiving and decoding signals 318 and 358 (e.g., messages, indications, information, pilots, and so on), respectively, in accordance with the designated RAT. Specifically, the WWAN transceivers 310 and 350 include one or more transmitters 314 and 354, respectively, for transmitting and encoding signals 31825QC2500148WOQualcomm Ref. No. 2500148WO26 and 358, respectively, and one or more receivers 312 and 352, respectively, for receiving and decoding signals 318 and 358, respectively.

[0084] The UE 302 and the base station 304 each also include, at least in some cases, one or more short-range wireless transceivers 320 and 360, respectively. The short-range wireless transceivers 320 and 360 may be connected to one or more antennas 326 and 366, respectively, and provide means for communicating (e.g., means for transmitting, means for receiving, means for measuring, means for tuning, means for refraining from transmitting, etc.) with other network nodes, such as other UEs, access points, base stations, etc., via at least one designated RAT (e.g., Wi-Fi, LTE Direct, BLUETOOTH®, ZIGBEE®, Z-WAVE®, PC5, dedicated short-range communications (DSRC), wireless access for vehicular environments (WAVE), near-field communication (NFC), ultra- wideband (UWB), etc.) over a wireless communication medium of interest. The short- range wireless transceivers 320 and 360 may be variously configured for transmitting and encoding signals 328 and 368 (e.g., messages, indications, information, and so on), respectively, and, conversely, for receiving and decoding signals 328 and 368 (e.g., messages, indications, information, pilots, and so on), respectively, in accordance with the designated RAT. Specifically, the short-range wireless transceivers 320 and 360 include one or more transmitters 324 and 364, respectively, for transmitting and encoding signals 328 and 368, respectively, and one or more receivers 322 and 362, respectively, for receiving and decoding signals 328 and 368, respectively. As specific examples, the short-range wireless transceivers 320 and 360 may be Wi-Fi transceivers, BLUETOOTH® transceivers, ZIGBEE® and / or Z-WAVE® transceivers, NFC transceivers, UWB transceivers, or vehicle-to-vehicle (V2V) and / or vehicle-to- everything (V2X) transceivers.

[0085] The UE 302 and the base station 304 also include, at least in some cases, satellite signal interfaces 330 and 370, which each include one or more satellite signal receivers 332 and 372, respectively, and may optionally include one or more satellite signal transmitters 334 and 374, respectively. In some cases, the base station 304 may be a terrestrial base station that may communicate with space vehicles (e.g., space vehicles 112) via the satellite signal interface 370. In other cases, the base station 304 may be a space vehicle (or other non-terrestrial entity) that uses the satellite signal interface 370 to communicate with terrestrial networks and / or other space vehicles.26QC2500148WOQualcomm Ref. No. 2500148WO27

[0086] The satellite signal receivers 332 and 372 may be connected to one or more antennas 336 and 376, respectively, and may provide means for receiving and / or measuring satellite positioning / communication signals 338 and 378, respectively. Where the satellite signal receiver(s) 332 and 372 are satellite positioning system receivers, the satellite positioning / communication signals 338 and 378 may be global positioning system (GPS) signals, global navigation satellite system (GLONASS) signals, Galileo signals, Beidou signals, Indian Regional Navigation Satellite System (NAVIC), Quasi-Zenith Satellite System (QZSS) signals, etc. Where the satellite signal receiver(s) 332 and 372 are nonterrestrial network (NTN) receivers, the satellite positioning / communication signals 338 and 378 may be communication signals (e.g., carrying control and / or user data) originating from a 5G network. The satellite signal receiver(s) 332 and 372 may comprise any suitable hardware and / or software for receiving and processing satellite positioning / communication signals 338 and 378, respectively. The satellite signal receiver(s) 332 and 372 may request information and operations as appropriate from the other systems, and, at least in some cases, perform calculations to determine locations of the UE 302 and the base station 304, respectively, using measurements obtained by any suitable satellite positioning system algorithm.

[0087] The optional satellite signal transmitter(s) 334 and 374, when present, may be connected to the one or more antennas 336 and 376, respectively, and may provide means for transmitting satellite positioning / communication signals 338 and 378, respectively. Where the satellite signal transmitter(s) 374 are satellite positioning system transmitters, the satellite positioning / communication signals 378 may be GPS signals, GLONASS® signals, Galileo signals, Beidou signals, NAVIC, QZSS signals, etc. Where the satellite signal transmitter(s) 334 and 374 are NTN transmitters, the satellite positioning / communication signals 338 and 378 may be communication signals (e.g., carrying control and / or user data) originating from a 5G network. The satellite signal transmitter(s) 334 and 374 may comprise any suitable hardware and / or software for transmitting satellite positioning / communication signals 338 and 378, respectively. The satellite signal transmitter(s) 334 and 374 may request information and operations as appropriate from the other systems.

[0088] The base station 304 and the network entity 306 each include one or more network transceivers 380 and 390, respectively, providing means for communicating (e.g., means27QC2500148WOQualcomm Ref. No. 2500148WO28 for transmitting, means for receiving, etc.) with other network entities (e.g., other base stations 304, other network entities 306). For example, the base station 304 may employ the one or more network transceivers 380 to communicate with other base stations 304 or network entities 306 over one or more wired or wireless backhaul links. As another example, the network entity 306 may employ the one or more network transceivers 390 to communicate with one or more base station 304 over one or more wired or wireless backhaul links, or with other network entities 306 over one or more wired or wireless core network interfaces.

[0089] A transceiver may be configured to communicate over a wired or wireless link. A transceiver (whether a wired transceiver or a wireless transceiver) includes transmitter circuitry (e.g., transmitters 314, 324, 354, 364) and receiver circuitry (e.g., receivers 312, 322, 352, 362). A transceiver may be an integrated device (e.g., embodying transmitter circuitry and receiver circuitry in a single device) in some implementations, may comprise separate transmitter circuitry and separate receiver circuitry in some implementations, or may be embodied in other ways in other implementations. The transmitter circuitry and receiver circuitry of a wired transceiver (e.g., network transceivers 380 and 390 in some implementations) may be coupled to one or more wired network interface ports. Wireless transmitter circuitry (e.g., transmitters 314, 324, 354, 364) may include or be coupled to a plurality of antennas (e.g., antennas 316, 326, 356, 366), such as an antenna array, that permits the respective apparatus (e.g., UE 302, base station 304) to perform transmit “beamforming,” as described herein. Similarly, wireless receiver circuitry (e.g., receivers 312, 322, 352, 362) may include or be coupled to a plurality of antennas (e.g., antennas 316, 326, 356, 366), such as an antenna array, that permits the respective apparatus (e.g., UE 302, base station 304) to perform receive beamforming, as described herein. In an aspect, the transmitter circuitry and receiver circuitry may share the same plurality of antennas (e.g., antennas 316, 326, 356, 366), such that the respective apparatus can only receive or transmit at a given time, not both at the same time. A wireless transceiver (e.g., WWAN transceivers 310 and 350, short-range wireless transceivers 320 and 360) may also include a network listen module (NLM) or the like for performing various measurements.

[0090] As used herein, the various wireless transceivers (e.g., transceivers 310, 320, 350, and 360, and network transceivers 380 and 390 in some implementations) and wired28QC2500148WOQualcomm Ref. No. 2500148WO29 transceivers (e.g., network transceivers 380 and 390 in some implementations) may generally be characterized as “a transceiver,” “at least one transceiver,” or “one or more transceivers.” As such, whether a particular transceiver is a wired or wireless transceiver may be inferred from the type of communication performed. For example, backhaul communication between network devices or servers will generally relate to signaling via a wired transceiver, whereas wireless communication between a UE (e.g., UE 302) and a base station (e.g., base station 304) will generally relate to signaling via a wireless transceiver.

[0091] The UE 302, the base station 304, and the network entity 306 also include other components that may be used in conjunction with the operations as disclosed herein. The UE 302, the base station 304, and the network entity 306 include one or more processors 342, 384, and 394, respectively, for providing functionality relating to, for example, wireless communication, and for providing other processing functionality. The processors 342, 384, and 394 may therefore provide means for processing, such as means for determining, means for calculating, means for receiving, means for transmitting, means for indicating, etc. In an aspect, the processors 342, 384, and 394 may include, for example, one or more general purpose processors, multi-core processors, central processing units (CPUs), ASICs, digital signal processors (DSPs), field programmable gate arrays (FPGAs), other programmable logic devices or processing circuitry, or various combinations thereof.

[0092] The UE 302, the base station 304, and the network entity 306 include memory circuitry implementing memories 340, 386, and 396 (e.g., each including a memory device), respectively, for maintaining information (e.g., information indicative of reserved resources, thresholds, parameters, and so on). The memories 340, 386, and 396 may therefore provide means for storing, means for retrieving, means for maintaining, etc. In some cases, the UE 302, the base station 304, and the network entity 306 may include positioning component 348, 388, and 398, respectively. The positioning component 348, 388, and 398 may be hardware circuits that are part of or coupled to the processors 342, 384, and 394, respectively, that, when executed, cause the UE 302, the base station 304, and the network entity 306 to perform the functionality described herein. In other aspects, the positioning component 348, 388, and 398 may be external to the processors 342, 384, and 394 (e.g., part of a modem processing system, integrated with another processing29QC2500148WOQualcomm Ref. No. 2500148WO30 system, etc.). Alternatively, the positioning component 348, 388, and 398 may be memory modules stored in the memories 340, 386, and 396, respectively, that, when executed by the processors 342, 384, and 394 (or a modem processing system, another processing system, etc.), cause the UE 302, the base station 304, and the network entity 306 to perform the functionality described herein. FIG. 3A illustrates possible locations of the positioning component 348, which may be, for example, part of the one or more WWAN transceivers 310, the memory 340, the one or more processors 342, or any combination thereof, or may be a standalone component. FIG. 3B illustrates possible locations of the positioning component 388, which may be, for example, part of the one or more WWAN transceivers 350, the memory 386, the one or more processors 384, or any combination thereof, or may be a standalone component. FIG. 3C illustrates possible locations of the positioning component 398, which may be, for example, part of the one or more network transceivers 390, the memory 396, the one or more processors 394, or any combination thereof, or may be a standalone component.

[0093] The UE 302 may include one or more sensors 344 coupled to the one or more processors 342 to provide means for sensing or detecting movement and / or orientation information that is independent of motion data derived from signals received by the one or more WWAN transceivers 310, the one or more short-range wireless transceivers 320, and / or the satellite signal interface 330. By way of example, the sensor(s) 344 may include an accelerometer (e.g., a micro-electrical mechanical systems (MEMS) device), a gyroscope, a geomagnetic sensor (e.g., a compass), an altimeter (e.g., a barometric pressure altimeter), and / or any other type of movement detection sensor. Moreover, the sensor(s) 344 may include a plurality of different types of devices and combine their outputs in order to provide motion information. For example, the sensor(s) 344 may use a combination of a multi-axis accelerometer and orientation sensors to provide the ability to compute positions in two-dimensional (2D) and / or three-dimensional (3D) coordinate systems.

[0094] In addition, the UE 302 includes a user interface 346 providing means for providing indications (e.g., audible and / or visual indications) to a user and / or for receiving user input (e.g., upon user actuation of a sensing device such a keypad, a touch screen, a microphone, and so on). Although not shown, the base station 304 and the network entity 306 may also include user interfaces.30QC2500148WOQualcomm Ref. No. 2500148WO31

[0095] Referring to the one or more processors 384 in more detail, in the downlink, IP packets from the network entity 306 may be provided to the processor 384. The one or more processors 384 may implement functionality for an RRC layer, a packet data convergence protocol (PDCP) layer, a radio link control (RLC) layer, and a medium access control (MAC) layer. The one or more processors 384 may provide RRC layer functionality associated with broadcasting of system information (e.g., master information block (MIB), system information blocks (SIBs)), RRC connection control (e.g., RRC connection paging, RRC connection establishment, RRC connection modification, and RRC connection release), inter-RAT mobility, and measurement configuration for UE measurement reporting; PDCP layer functionality associated with header compression / decompression, security (ciphering, deciphering, integrity protection, integrity verification), and handover support functions; RLC layer functionality associated with the transfer of upper layer PDUs, error correction through automatic repeat request (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, scheduling information reporting, error correction, priority handling, and logical channel prioritization.

[0096] The transmitter 354 and the receiver 352 may implement Layer- 1 (LI) functionality associated with various signal processing functions. Layer- 1, which includes a physical (PHY) layer, may include error detection on the transport channels, forward error correction (FEC) coding / decoding of the transport channels, interleaving, rate matching, mapping onto physical channels, modulation / demodulation of physical channels, and MIMO antenna processing. The transmitter 354 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 orthogonal frequency division multiplexing (OFDM) subcarrier, multiplexed with a reference signal (e.g., pilot) in the time and / or frequency domain, and then combined together using an inverse fast Fourier transform (IFFT) to produce a physical channel carrying a time domain OFDM symbol stream. The OFDM symbol stream is spatially precoded to produce multiple spatial31QC2500148WOQualcomm Ref. No. 2500148WO32 streams. Channel estimates from a channel estimator 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 302. Each spatial stream may then be provided to one or more different antennas 356. The transmitter 354 may modulate an RF carrier with a respective spatial stream for transmission.

[0097] At the UE 302, the receiver 312 receives a signal through its respective antenna(s) 316. The receiver 312 recovers information modulated onto an RF carrier and provides the information to the one or more processors 342. The transmitter 314 and the receiver 312 implement Lay er- 1 functionality associated with various signal processing functions. The receiver 312 may perform spatial processing on the information to recover any spatial streams destined for the UE 302. If multiple spatial streams are destined for the UE 302, they may be combined by the receiver 312 into a single OFDM symbol stream. The receiver 312 then converts the OFDM symbol stream from the time-domain to the frequency domain using a fast Fourier transform (FFT). The frequency domain signal comprises 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 304. These soft decisions may be based on channel estimates computed by a channel estimator. The soft decisions are then decoded and de-interleaved to recover the data and control signals that were originally transmitted by the base station 304 on the physical channel. The data and control signals are then provided to the one or more processors 342, which implements Layer-3 (L3) and Layer-2 (L2) functionality.

[0098] In the downlink, the one or more processors 342 provides demultiplexing between transport and logical channels, packet reassembly, deciphering, header decompression, and control signal processing to recover IP packets from the core network. The one or more processors 342 are also responsible for error detection.

[0099] Similar to the functionality described in connection with the downlink transmission by the base station 304, the one or more processors 342 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,32QC2500148WOQualcomm Ref. No. 2500148WO33 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 transport blocks (TBs), demultiplexing of MAC SDUs from TBs, scheduling information reporting, error correction through hybrid automatic repeat request (HARQ), priority handling, and logical channel prioritization.

[0100] Channel estimates derived by the channel estimator from a reference signal or feedback transmitted by the base station 304 may be used by the transmitter 314 to select the appropriate coding and modulation schemes, and to facilitate spatial processing. The spatial streams generated by the transmitter 314 may be provided to different antenna(s) 316. The transmitter 314 may modulate an RF carrier with a respective spatial stream for transmission.

[0101] The uplink transmission is processed at the base station 304 in a manner similar to that described in connection with the receiver function at the UE 302. The receiver 352 receives a signal through its respective antenna(s) 356. The receiver 352 recovers information modulated onto an RF carrier and provides the information to the one or more processors 384.

[0102] In the uplink, the one or more processors 384 provides demultiplexing between transport and logical channels, packet reassembly, deciphering, header decompression, control signal processing to recover IP packets from the UE 302. IP packets from the one or more processors 384 may be provided to the core network. The one or more processors 384 are also responsible for error detection.

[0103] For convenience, the UE 302, the base station 304, and / or the network entity 306 are shown in FIGS. 3 A, 3B, and 3C as including various components that may be configured according to the various examples described herein. It will be appreciated, however, that the illustrated components may have different functionality in different designs. In particular, various components in FIGS. 3A to 3C are optional in alternative configurations and the various aspects include configurations that may vary due to design choice, costs, use of the device, or other considerations. For example, in case of FIG. 3A, a particular implementation of UE 302 may omit the WWAN transceiver(s) 310 (e.g., a wearable device or tablet computer or personal computer (PC) or laptop may have Wi-Fi33QC2500148WOQualcomm Ref. No. 2500148WO34 and / or BLUETOOTH® capability without cellular capability), or may omit the short- range wireless transceiver(s) 320 (e.g., cellular-only, etc.), or may omit the satellite signal interface 330, or may omit the sensor(s) 344, and so on. In another example, in case of FIG. 3B, a particular implementation of the base station 304 may omit the WWAN transceiver(s) 350 (e.g., a Wi-Fi “hotspot” access point without cellular capability), or may omit the short-range wireless transceiver(s) 360 (e.g., cellular-only, etc.), or may omit the satellite signal interface 370, and so on. For brevity, illustration of the various alternative configurations is not provided herein, but would be readily understandable to one skilled in the art.

[0104] The various components of the UE 302, the base station 304, and the network entity 306 may be communicatively coupled to each other over data buses 308, 382, and 392, respectively. In an aspect, the data buses 308, 382, and 392 may form, or be part of, a communication interface of the UE 302, the base station 304, and the network entity 306, respectively. For example, where different logical entities are embodied in the same device (e.g., gNB and location server functionality incorporated into the same base station 304), the data buses 308, 382, and 392 may provide communication between them.

[0105] The components of FIGS. 3A, 3B, and 3C may be implemented in various ways. In some implementations, the components of FIGS. 3 A, 3B, and 3C may be implemented in one or more circuits such as, for example, one or more processors and / or one or more ASICs (which may include one or more processors). Here, each circuit may use and / or incorporate at least one memory component for storing information or executable code used by the circuit to provide this functionality. For example, some or all of the functionality represented by blocks 310 to 346 may be implemented by processor and memory component(s) of the UE 302 (e.g., by execution of appropriate code and / or by appropriate configuration of processor components). Similarly, some or all of the functionality represented by blocks 350 to 388 may be implemented by processor and memory component(s) of the base station 304 (e.g., by execution of appropriate code and / or by appropriate configuration of processor components). Also, some or all of the functionality represented by blocks 390 to 398 may be implemented by processor and memory component(s) of the network entity 306 (e.g., by execution of appropriate code and / or by appropriate configuration of processor components). For simplicity, various operations, acts, and / or functions are described herein as being performed “by a UE,” “by34QC2500148WOQualcomm Ref. No. 2500148WO35 a base station,” “by a network entity,” etc. However, as will be appreciated, such operations, acts, and / or functions may actually be performed by specific components or combinations of components of the UE 302, base station 304, network entity 306, etc., such as the processors 342, 384, 394, the transceivers 310, 320, 350, and 360, the memories 340, 386, and 396, the positioning component 348, 388, and 398, etc.

[0106] In some designs, the network entity 306 may be implemented as a core network component. In other designs, the network entity 306 may be distinct from a network operator or operation of the cellular network infrastructure (e.g., NG RAN 220 and / or 5GC 210 / 260). For example, the network entity 306 may be a component of a private network that may be configured to communicate with the UE 302 via the base station 304 or independently from the base station 304 (e.g., over a non-cellular communication link, such as Wi-Fi).

[0107] Long-Term Evolution (LTE) positioning protocol (LPP) is used point-to-point between a location server (e.g., LMF 270) and a target device (e.g., a UE) in order to position the target device using position-related measurements obtained by one or more reference sources (physical entities or parts of physical entities that provide signals that can be measured by a target device in order to obtain the location of the target device). An LPP session is used between a location server and a target device in order to obtain location- related measurements or a location estimate or to transfer assistance data. Currently, a single LPP session is used to support a single location request and multiple LPP sessions can be used between the same endpoints to support multiple different location requests. Each LPP session comprises one or more LPP transactions (or procedures), with each LPP transaction performing a single operation (capability exchange, assistance data transfer, or location information transfer). Each LPP transaction involves the exchange of one or more LPP messages between the location server and the target device. The general format of an LPP message consists of a set of common fields followed by a body. The body (which may be empty) contains information specific to a particular message type. Each message type contains information specific to one or more positioning methods and / or information common to all positioning methods.

[0108] An LPP session generally includes at least a capability transfer or indication procedure, an assistance data transfer or delivery procedure, and a location information transfer or delivery procedure. FIG. 4 illustrates an example LPP capability transfer procedure 410,35QC2500148WOQualcomm Ref. No. 2500148WO36LPP assistance data transfer procedure 430, and LPP location information transfer procedure 450 between a target device (labeled “Target”) and a location server (labeled “Server”), according to aspects of the disclosure.

[0109] The purpose of an LPP capability transfer procedure 410 is to enable the transfer of capabilities from the target device (e.g., a UE 204) to the location server (e.g., an LMF 270). Capabilities in this context refer to positioning and protocol capabilities related to LPP and the positioning methods supported by LPP. In the LPP capability transfer procedure 410, the location server (e.g., an LMF 270) indicates the types of capabilities needed from the target device (e.g., UE 204) in an LPP Request Capabilities message. The target device responds with an LPP Provide Capabilities message. The capabilities included in the LPP Provide Capabilities message should correspond to any capability types specified in the LPP Request Capabilities message. Specifically, for each positioning method for which a request for capabilities is included in the LPP Request Capabilities message, if the target device supports this positioning method, the target device includes the capabilities of the target device for that supported positioning method in the LPP Provide Capabilities message. For an LPP capability indication procedure, the target device provides unsolicited (i.e., without receiving an LPP Request Capabilities message) capabilities to the location server in an LPP Provide Capabilities message.

[0110] The purpose of an LPP assistance data transfer procedure 430 is to enable the target device to request assistance data from the location server to assist in positioning, and to enable the location server to transfer assistance data to the target device in the absence of a request. In the LPP assistance data transfer procedure 430, the target device sends an LPP Request Assistance Data message to the location server. The location server responds to the target device with an LPP Provide Assistance Data message containing assistance data. The transferred assistance data should match or be a subset of the assistance data requested in the LPP Request Assistance Data. The location server may also provide any not requested information that it considers useful to the target device. The location server may also transmit one or more additional LPP Provide Assistance Data messages to the target device containing further assistance data. For an LPP assistance data delivery procedure, the location server provides unsolicited assistance data necessary for positioning. The assistance data may be provided periodically or non-periodically.36QC2500148WOQualcomm Ref. No. 2500148WO37

[0111] The purpose of an LPP location information transfer procedure 450 is to enable the location server to request location measurement data and / or a location estimate from the target device, and to enable the target device to transfer location measurement data and / or a location estimate to a location server in the absence of a request. In an LPP location information transfer procedure 450, the location server sends an LPP Request Location Information message to the target device to request location information, indicating the type of location information needed and potentially the associated QoS. The target device responds with an LPP Provide Location Information message to the location server to transfer location information. The location information transferred should match or be a subset of the location information requested by the LPP Request Location Information unless the location server explicitly allows additional location information. More specifically, if the requested information is compatible with the target device’s capabilities and configuration, the target device includes the requested information in an LPP Provide Location Information message. Otherwise, if the target device does not support one or more of the requested positioning methods, the target device continues to process the message as if it contained only information for the supported positioning methods and handles the signaling content of the unsupported positioning methods by LPP error detection. If requested by the LPP Request Lactation Information message, the target device sends additional LPP Provide Location Information messages to the location server to transfer additional location information. An LPP location information delivery procedure supports the delivery of positioning estimations based on unsolicited service.

[0112] LPP also defines procedures related to error indication for when a receiving endpoint (target device or location server) receives erroneous or unexpected data or detects that certain data are missing. Specifically, when a receiving endpoint determines that a received LPP message contains an error, it can return an Error message to the transmitting endpoint indicating the error or errors and discard the received / erroneous message. If the receiving endpoint is able to determine that the erroneous LPP message is an LPP Error or Abort Message, then the receiving endpoint discards the received message without returning an Error message to the transmitting endpoint.

[0113] LPP also defines procedures related to abort indication to allow a target device or location server to abort an ongoing procedure due to some unexpected event (e.g., cancellation of a location request by an LCS client). An Abort procedure can also be used to stop an37QC2500148WOQualcomm Ref. No. 2500148WO38 ongoing procedure (e.g., periodic location reporting from the target device). In an Abort procedure, a first endpoint determines that procedure P must be aborted and sends an Abort message to a second endpoint carrying the transaction ID for procedure P. The second endpoint then aborts procedure P.

[0114] Machine learning may be used to generate models that may be used to facilitate various aspects associated with processing of data. One specific application of machine learning relates to generation of measurement models for processing of reference signals for positioning (e.g., positioning reference signal (PRS)), such as feature extraction, reporting of reference signal measurements (e.g., selecting which extracted features to report), and so on.

[0115] Machine learning models are generally categorized as either supervised or unsupervised. A supervised model may further be sub-categorized as either a regression or classification model. Supervised learning involves learning a function that maps an input to an output based on example input-output pairs. For example, given a training dataset with two variables of age (input) and height (output), a supervised learning model could be generated to predict the height of a person based on their age. In regression models, the output is continuous. One example of a regression model is a linear regression, which simply attempts to find a line that best fits the data. Extensions of linear regression include multiple linear regression (e.g., finding a plane of best fit) and polynomial regression (e.g., finding a curve of best fit).

[0116] Another example of a machine learning model is a decision tree model. In a decision tree model, a tree structure is defined with a plurality of nodes. Decisions are used to move from a root node at the top of the decision tree to a leaf node at the bottom of the decision tree (i.e., a node with no further child nodes). Generally, a higher number of nodes in the decision tree model is correlated with higher decision accuracy.

[0117] Another example of a machine learning model is a decision forest. Random forests are an ensemble learning technique that builds off of decision trees. Random forests involve creating multiple decision trees using bootstrapped datasets of the original data and randomly selecting a subset of variables at each step of the decision tree. The model then selects the mode of all of the predictions of each decision tree. By relying on a “majority wins” model, the risk of error from an individual tree is reduced.38QC2500148WOQualcomm Ref. No. 2500148WO39

[0118] Another example of a machine learning model is a neural network (NN). A neural network is essentially a network of mathematical equations. Neural networks accept one or more input variables, and by going through a network of equations, result in one or more output variables. Put another way, a neural network takes in a vector of inputs and returns a vector of outputs.

[0119] FIG. 5 illustrates an example neural network 500, according to aspects of the disclosure. The neural network 500 includes an input layer ‘i’ that receives ‘n’ (one or more) inputs (illustrated as “Input 1,” “Input 2,” and “Input n”), one or more hidden layers (illustrated as hidden layers ‘hl,’ ‘h2,’ and ‘h3’) for processing the inputs from the input layer, and an output layer ‘o’ that provides ‘m’ (one or more) outputs (labeled “Output 1” and “Output m”). The number of inputs ‘n,’ hidden layers ‘h,’ and outputs ‘m’ may be the same or different. In some designs, the hidden layers ‘h’ may include linear function(s) and / or activation function(s) that the nodes (illustrated as circles) of each successive hidden layer process from the nodes of the previous hidden layer.

[0120] In classification models, the output is discrete. One example of a classification model is logistic regression. Logistic regression is similar to linear regression but is used to model the probability of a finite number of outcomes, typically two. In essence, a logistic equation is created in such a way that the output values can only be between ‘0’ and ‘ 1.’ Another example of a classification model is a support vector machine. For example, for two classes of data, a support vector machine will find a hyperplane or a boundary between the two classes of data that maximizes the margin between the two classes. There are many planes that can separate the two classes, but only one plane can maximize the margin or distance between the classes. Another example of a classification model is Naive Bayes, which is based on Bayes Theorem. Other examples of classification models include decision tree, random forest, and neural network, similar to the examples described above except that the output is discrete rather than continuous.

[0121] Unlike supervised learning, unsupervised learning is used to draw inferences and find patterns from input data without references to labeled outcomes. Two examples of unsupervised learning models include clustering and dimensionality reduction.

[0122] Clustering is an unsupervised technique that involves the grouping, or clustering, of data points. Clustering is frequently used for customer segmentation, fraud detection, and document classification. Common clustering techniques include k-means clustering,39QC2500148WOQualcomm Ref. No. 2500148WO40 hierarchical clustering, mean shift clustering, and density-based clustering. Dimensionality reduction is the process of reducing the number of random variables under consideration by obtaining a set of principal variables. In simpler terms, dimensionality reduction is the process of reducing the dimension of a feature set (in even simpler terms, reducing the number of features). Most dimensionality reduction techniques can be categorized as either feature elimination or feature extraction. One example of dimensionality reduction is called principal component analysis (PCA). In the simplest sense, PCA involves project higher dimensional data (e.g., three dimensions) to a smaller space (e.g., two dimensions). This results in a lower dimension of data (e.g., two dimensions instead of three dimensions) while keeping all original variables in the model.

[0123] Regardless of which machine learning model is used, at a high-level, a machine learning module (e.g., implemented by a processing system) may be configured to iteratively analyze training input data (e.g., measurements of reference signals to / from various target UEs) and to associate this training input data with an output data set (e.g., a set of possible or likely candidate locations of the various target UEs), thereby enabling later determination of the same output data set when presented with similar input data (e.g., from other target UEs at the same or similar location).

[0124] FIG. 6A is a diagram 610 illustrating an example of classical (i.e., non-machine learning) positioning and / or sensing, according to aspects of the disclosure. As shown in FIG. 6A, a path finding algorithm receives measurements of one or more reference signals and outputs one or more intermediate measurements. The path finding algorithm may be a line-of-sight (LOS) quadrature (LOSQuad) algorithm, a multiple signal classification (MUSIC) algorithm, a matrix pencil (MP) algorithm, etc. The one or more reference signals may be downlink positioning reference signals (DL-PRS), sounding reference signals (SRS), sidelink positioning reference signals (SL-PRS), sensing signals, synchronization signal blocks (SSBs), channel state information reference signals (CSI- RS), etc. The measurements of the one or more reference signals may be channel energy response (CER) measurements, channel impulse response (CIR) measurements, power delay profile (PDP) measurements, delay profile (DP) measurements, channel frequency response (CFR) measurements, etc. The intermediate measurements may be LOS indicator(s), received signal strength indicator (RS SI) measurements(s), reference signal40QC2500148WOQualcomm Ref. No. 2500148WO41 received power (RSRP) measurement(s), path RSRP (RSRPP) measurement(s), reference signal received quality (RSRQ) measurement(s), time of arrival (To A) measurement(s), relative ToA (RTOA) measurement(s), reference signal time difference (RSTD) measurement(s), reception-to-transmission (Rx-Tx) time difference measurement(s), angle of departure (AoD) measurement(s), angle of arrival (AoA) measurement(s), etc.

[0125] A positioning engine (at the UE for UE-based positioning or the network for UE-assisted positioning) receives the intermediate measurements, applies a positioning algorithm (e.g., multi -laterati on, Chan’s algorithm, Kalman filtering, etc.) to the measurements, and outputs a target location (e.g., a UE location for positioning or a target object location for sensing).

[0126] Current positioning methods tend to perform poorly, and even fail, in non-line-of-sight (NLOS) conditions. Artificial intelligence / machine learning (AIML) techniques can enhance positioning accuracy in NLOS conditions because such techniques can learn channel multipath profiles and their mapping to location information.

[0127] The AIML positioning and / or sensing provided by an AIML model may be “direct” AIML (denoted “D-AIML”) positioning and / or sensing or AIML “assisted” (denoted “A- AIML”) positioning and / or sensing. Note that, as used herein, an AIML model (whether an A-AIML model or a D-AIML model) may alternatively be referred to as an “ML model,” an “Al model,” an “ML-based model,” an “Al-based model,” and the like.

[0128] FIG. 6B is a diagram 630 illustrating an example of direct AIML positioning and / or sensing, according to aspects of the disclosure. As shown in FIG. 6B, direct AIML positioning and / or sensing is where the AIML model is trained to accept input features (e.g., downlink positioning reference signal (DL-PRS) measurements, sounding reference signal (SRS) measurements, sidelink positioning reference signal (SL-PRS) measurements, sensing signal measurements, beam measurements (e.g., synchronization signal block (SSB) measurements), channel state information reference signal (CSLRS) measurements, etc.) and output a final result (referred to as a “direct label”), such as a target location (e.g., a UE location for positioning or a target object location for sensing). The measurements of the reference signal (s) may include the channel energy response (CER), channel impulse response (CIR), power delay profile (PDP), delay profile (DP), channel frequency response (CFR), received signal strength indicator (RS SI), reference signal received power (RSRP), path RSRP (RSRPP), reference signal received quality41QC2500148WOQualcomm Ref. No. 2500148WO42(RSRQ), time of arrival (ToA), relative ToA (RTOA), reference signal time difference (RSTD), angle of departure (AoD), angle of arrival (AoA), and / or the like of the reference signal(s).

[0129] FIG. 6C is a diagram 650 illustrating an example of AIML assisted positioning and / or sensing, according to aspects of the disclosure. As shown in FIG. 6C, AIML assisted positioning and / or sensing is where an AIML model is trained to accept input features (e.g., DL-PRS measurements, SRS measurements, SL-PRS measurements, sensing signal measurements, beam measurements, CSLRS measurements, etc.) and output one or more intermediate results (also referred to as “intermediate label(s)”). In a positioning context, generating the intermediate result may be referred to as “positioning feature extraction,” which may include determining timing / angle information, line of sight (LOS) identification, etc. The intermediate results may include the ToA, RTOA, RSTD, AoD, AoA, LOS indication, and / or the like. The intermediate result(s) may in turn be provided as an input to another AIML model or non-AIML model positioning and / or sensing technique (e.g., Chan’s algorithm, Kalman filtering, etc.) to determine a target location (e.g., a UE location for positioning or a target object location for sensing).

[0130] Note that as shown in FIG. 6C, the A-AIML model and the other model / technique may be implemented at the same entity (e.g., UE, base station, location server, sensing server, etc.) or at different entities. For example, for network-assisted positioning, the UE may apply the A-AIML model to compress the measurement data and then report the compressed data to the location server, which may then apply the other position estimation model / technique. As another example, for UE-based positioning, a network component (e.g., a base station, location server, or another UE for sidelink positioning) may apply the A-AIML model to compress the measurement data and report the compressed data to the UE, which then applies the other position estimation model / technique.

[0131] FIG. 6D illustrates various AIML positioning and / or sensing scenarios, according to aspects of the disclosure. As shown in diagram 670, there are three AIML positioning and / or sensing deployment scenarios based on downlink reference signals (e.g., DL-PRS, CSI-RS, etc.). The first deployment scenario (labeled “Case 1”) is a UE-based positioning and / or sensing case with a UE-side D-AIML positioning and / or sensing model (labeled “D-AIML”). In this case, the UE applies the D-AIML positioning and / or42QC2500148WOQualcomm Ref. No. 2500148WO43 sensing model (or simply “D-AIML model”) to the downlink reference signal measurements to determine a location of the UE or a target object and reports the target location to the network (e.g., LMF 270).

[0132] The second deployment scenario (labeled “Case 2a”) is UE-assisted / network-based positioning and / or sensing with a UE-side A-AIML positioning and / or sensing model that provides AIML-assisted positioning and / or sensing. That is, the UE inputs measurements of downlink reference signals (e.g., DL-PRS, CSI-RS) received from one or more TRPs into the A-AIML positioning and / or sensing model to obtain intermediate measurements (or quantities) of the downlink reference signals. The UE then reports the intermediate measurements to the network (e.g., LMF 270). The network entity may then apply an AIML model or a non-AIML model technique to the intermediate measurements to determine a target location (e.g., of the UE for positioning scenarios or a target object for sensing scenarios).

[0133] The third deployment scenario (labeled “Case 2b”) is UE-assisted / network-based positioning and / or sensing scenario with a network-side D-AIML positioning and / or sensing model. That is, the UE reports the measurements of the downlink reference signals received from one or more TRPs to the network (e.g., LMF 270). The network then applies the D-AIML positioning and / or sensing model to the measurements to determine the location of the UE or a target object.

[0134] As shown in diagram 690, there are two AIML positioning and / or sensing deployment scenarios based on uplink reference signals (e.g., SRS). The first deployment scenario (labeled “Case 3a”) is RAN node-assisted positioning and / or sensing with a RAN-side AIML model that provides AIML assisted positioning and / or sensing. In this case, the RAN node (e.g., a base station, TRP, or other base station component) applies an A-AIML positioning and / or sensing model to TRP measurements of one or more uplink reference signals (e.g., SRS) transmitted by a UE to obtain intermediate measurements of the received uplink reference signal(s). The RAN node then reports the intermediate measurements to the core network (e.g., LMF 270), which can use them to locate the UE (for positioning) or a target object (for sensing).

[0135] The second deployment scenario (labeled “Case 3b”) is RAN node-assisted positioning and / or sensing with a network-side AIML positioning and / or sensing model that provides direct AIML positioning and / or sensing. In this case, the RAN node reports43QC2500148WOQualcomm Ref. No. 2500148WO44 measurements of one or more uplink reference signals received from a UE to the core network (e.g., LMF 270). The core network then applies a D-AIML positioning and / or sensing model to the measurements of the uplink reference signal(s) to obtain a target location of the UE (for positioning) or a target object (for sensing).

[0136] Note that there may be other deployment scenarios in which the UE, RAN, or the core network use an AIML positioning and / or sensing model to compute or report a positioning and / or sensing estimate (target location), but these cases are implementationspecific and do not necessarily involve signaling between the UE, RAN, and / or the core network.

[0137] Further note that an AIML model may execute in a training mode or an inferencing mode. In the training mode, the AIML model is provided with pre-validated input data along with pre-validated output data to derive or modify weights of the AIML to increase the reliability of the AIML model to provide new (unvalidated) output data that is similar to the pre-validated output data in response to new (unvalidated) input data that is similar to the pre-validated input data. In the inferencing mode, the AIML model utilizes the weights determined during the training mode to process new (unvalidated) input data so as to generate new (unvalidated) output data (typically, without further adjusting the weights until / unless the AIML model returns to the training mode). The (unvalidated) output data may be characterized as an “inference.” Thus, the “final” positioning or sensing results described above with respect to FIGS. 6B to 6D may correspond to AIML model weights or inferences depending on whether the respective AIML model is executing in the training mode or the inferencing mode.

[0138] Currently, positioning accuracy enhancements for direct AIML positioning and AIML assisted positioning are being explored. Regarding direct AIML positioning, it has been agreed that enhancements to Case 1 (UE-based positioning with UE-side model) and Case 3b (NG-RAN node assisted positioning with LMF-side model), as shown in FIG. 6D, should have first priority, and enhancements to Case 2b (UE-assisted / LMF -based positioning with LMF-side model), as shown in FIG. 6D, should have second priority. Regarding AIML assisted positioning, it has been agreed that enhancements to Case 3a (NG-RAN node assisted positioning with gNB-side model) should have first priority and enhancements to Case 2a (UE-assisted / LMF-based positioning with UE-side model) should have second priority.44QC2500148WOQualcomm Ref. No. 2500148WO45

[0139] It has also been agreed to specify the measurements and signaling / mechanism(s) needed to facilitate life cycle management (LCM) operations specific to the positioning accuracy enhancement use cases, if any. The signaling of any measurement enhancements is also being investigated for specification. Methods are also being explored to ensure consistency between training and inference regarding network-side additional conditions (if identified) for inference at the UE for relevant positioning sub-use cases.

[0140] The following are examples of currently supported AIML model output types. As a first example, for AIML assisted positioning Case 3a, at least an LOS / NLOS indicator and / or timing information are supported for reporting. If an LOS / NLOS indicator is reported, the indicator can be reported as a soft indicator (e.g., a probability) or a hard indicator (e.g., a binary value). If timing information is reported, the timing information at least can be reported via uplink RTOA or gNB Rx-Tx time difference.

[0141] As another example, for AIML assisted positioning Case 2a, at least an LOS / NLOS indicator and / or timing information are supported for reporting. If an LOS / NLOS indicator is reported, the indicator can be reported as a soft indicator or a hard indicator. If timing information is reported, the timing information at least can be reported via DL- RSTD or UE Rx-Tx time difference.

[0142] The following are examples of currently supported AIML model input types. As a first example, for AIML based positioning Case 3b, at least the following types of time domain channel measurements are supported for reporting: (1) timing information and (2) paired timing information and power information. As another example, for AIML based positioning Case 2b, at least the following types of time domain channel measurements are supported for UE reporting to the LMF: (1) timing information and (2) paired timing information and power information.

[0143] The following are various considerations for AIML positioning related data collection. First, for training data generation of AIML based positioning Case 2a and Case 2b, the channel measurement and its related data (e.g., timestamp) are generated by a positioning reference unit (PRU) (e.g., a UE with a known / fixed location) and / or a non-PRU UE.

[0144] Second, for training data generation for AIML based positioning Case 1, the label and its related data (e.g., timestamp) can be generated by: (1) a PRU, (2) a non-PRU UE with an estimated location, and / or (3) an LMF. For training data generation for AIML based positioning Case 2a, the label and its related data (e.g., timestamp) can be generated by:45QC2500148WOQualcomm Ref. No. 2500148WO46(1) a PRU, (2) a non-PRU UE with an estimated location, and / or (3) an LMF. For training data generation for AIML based positioning Case 2b, the label and its related data (e.g., timestamp) can be generated by : (1) a PRU, (2) a non-PRU UE with an estimated location, and / or (3) an LMF. For training data generation for AIML based positioning Case 3b, the label and its related data (e.g., timestamp) can be generated by: (1) a PRU and / or (2) an LMF. For training data generation for AIML based positioning Case 3a, the label and its related data (e.g., timestamp) can be generated by at least an LMF.

[0145] Third, for training data generation for AIML based positioning Case 1, the measurement and its related data (e.g., timestamp) are generated by: (1) a PRU and / or (2) a non-PRU UE. For training data generation for AIML based positioning Case 3a and 3b, the measurement and its related data (e.g., timestamp) are generated by a TRP / gNB.

[0146] Fourth, for training data collection for AIML based positioning, the collected data sample can include Part A and Part B components. Part A components include (1) a channel measurement, (2) a quality indicator of the channel measurement, and (3) a timestamp of the channel measurement. Part B components include (1) the ground truth label (or its approximation), (2) a quality indicator of the label, and (3) a timestamp of the label.

[0147] Note that “Part A” and “Part B” terminologies are used simply to differentiate the different sets of data. In addition, the contents in Part A and Part B may or may not be generated by different entities. Further, Part A and / or Part B, and their contents, may or may not apply for each AIML case.

[0148] Fifth, for training data collection for AIML based positioning, if a training data sample contains both Part A and Part B, it is assumed that Part A and Part B in one training data sample are: (1) for the same UE (PRU or Non-PRU UE), and (2) for the same location associated with Part B.

[0149] For training data collection for AIML based positioning for Cases 1, 2b, 3b, a quality indicator for a label may be represented using one of the following options: (1) reuse an existing information element that provides UE location quality or UE location uncertainty (e.g., “Locationuncertainty” in LPP, “NR-TimingQuality” in LPP, “Timing Measurement Quality” in New Radio positioning protocol type A (NRPPa)), or (2) define a new information element for UE location quality (e.g., use a “hard” value (1 or 0) or “soft” values (e.g., 0, 0.1, 0.2, . . ., 1.0), with value 1 indicating the highest quality).46QC2500148WOQualcomm Ref. No. 2500148WO47

[0150] In some cases, the format of a location estimate may be a two-dimensional (2D) point with an uncertainty ellipse or a three-dimensional (3D) point with an uncertainty ellipsoid. A “local 2D point with uncertainty ellipse” is characterised by a point described in 2D local coordinates with the origin in a known reference location, distances rl and r2, and an angle of orientation A. The local Cartesian coordinates system and the reference location may be identified with a unique identifier. It describes formally the set of points that fall within or on the boundary of an ellipse with semi-major axis of length rl oriented at angle d (0 to 180°) measured clockwise from north and semi-minor axis of length r2. The confidence level with which the position of a target entity may be included within this set of points is also included with this shape.

[0151] The “local 3D point with uncertainty ellipsoid” is characterised by a point described in 3D local coordinates with origin in a known reference location, distances rl (the “semi- maj or uncertainty”), r2 (the “semi-minor uncertainty”), and r3 (the “vertical uncertainty”) and an angle of orientation A (the “angle of the major axis”). The local Cartesian coordinates system and the reference location may be identified with a unique identifier. It describes formally the set of points that fall within or on the surface of a general (three dimensional) ellipsoid centred on a 3D point whose real semi-major, semi-mean, and semi-minor axis are some permutation of rl, r2, r3 with rl > r2. The r3 axis is aligned vertically, while the rl axis, which is the semi-major axis of the ellipse in a horizontal plane, is oriented at an angle d (0 to 180 degrees) measured clockwise from north. The confidence level with which the position of a target entity is included within the shape is also included.

[0152] The “ellipsoid point with altitude and uncertainty ellipsoid” is characterised by the coordinates of an ellipsoid point with altitude, distances rl (the “semi-major uncertainty”), r2 (the “semi-minor uncertainty”), and r3 (the “vertical uncertainty”), and an angle of orientation ^ (the “angle of the major axis”). It describes formally the set of points that fall within or on the surface of a general (three dimensional) ellipsoid centred on an ellipsoid point with altitude whose real semi -major, semi-mean, and semi -minor axis are some permutation of rl, r2, r3 with rl > r2. The r3 axis is aligned vertically, while the rl axis, which is the semi-major axis of the ellipse in a horizontal plane that bisects the ellipsoid, is oriented at an angled (0 to 180 degrees) measured clockwise from north, as illustrated in FIG. 7.47QC2500148WOQualcomm Ref. No. 2500148WO48

[0153] FIG. 7 is a diagram 700 illustrating an ellipsoid point with altitude and uncertainty ellipsoid, according to aspects of the disclosure. The typical use of this shape is to indicate a point when its horizontal position and altitude are known only with a limited accuracy, but the geometrical contributions to uncertainty can be quantified. The confidence level with which the position of a target entity is included within the shape is also included.

[0154] The confidence by which the position of a target entity is known to be within the shape description (expressed as a percentage), is directly mapped from the seven-bit binary number T, except for T=O, which is used to indicate “no information,” and 100 <K <128, which should not be used but may be interpreted as “no information” if received.

[0155] FIGS. 8A to 8D illustrate example information elements for various location information types and associated uncertainties, according to aspects of the disclosure. Specifically, FIG. 8A illustrates an example “CommonlEsRequestLocationlnformation” information element (IE) 810 that carries common IES for an LPP Request Location Information message. FIG. 8B illustrates an example “LocationCoordinateTypes” IE 820, which may be referenced by a “CommonlEsRequestLocationlnformation” IE 810. A “LocationCoordinateTypes” IE 820 defines a list of possible geographic shapes, which are the types of location estimate that a target device may return when a location estimate is obtained by the target device. Note that a “LocationCoordinateTypes” IE 820 may reference a “ellipsoidPointWithAltitudeAndUncertaintyEllipsoid” IE.

[0156] FIG. 8C illustrates an example “CommonlEsProvideLocationlnformation” IE 830, which carries common IEs for an LPP Provide Location Information message. FIG. 8D illustrates an example “LocationCoordinates” IE 840, which may be referenced by the “locationEstimate” field of the “CommonlEsProvideLocationlnformation” IE 830. Note that a “LocationCoordinates” IE 840 may reference a “ellipsoidPointWithAltitudeAndUncertaintyEllipsoid” IE.

[0157] FIG. 9 illustrates example information elements for various location information formats, according to aspects of the disclosure. Specifically, FIG. 9 illustrates an example “EllipsoidPointWithAltitudeAndUncertaintyEllipsoid” IE 910 that is used to describe an ellipsoid point with altitude and uncertainty ellipsoid. FIG. 9 further illustrates an example “EllipsoidArc” IE 920, which is used to describe an ellipsoid arc type of geographic shape.48QC2500148WOQualcomm Ref. No. 2500148WO49

[0158] Referring to location information uncertainty in greater detail, the uncertainty for latitude and longitude should be both flexible (can cover wide differences in range) and efficient. In some cases, the uncertainty r, expressed in meters, may be mapped to a number K, with the following formula: r = C((l + x)K— 1)

[0159] For standard uncertainty, C = 10 and x = 0,1. For values of K between 0 and 127, a suitably useful range between 0 and 1800 kilometers is achieved for the uncertainty, while still being able to code down to values as small as 1 meter. The uncertainty can then be coded on seven bits, as the binary encoding of K. The following table provides example values for the above uncertainty function for C = 10 and x = 0, 1.Table 1

[0160] For high accuracy uncertainty, C = 0.3 and x = 0.02. For values of K between 0 and 255, a suitably useful range between 0 and 46.49129 meters is achieved for the high accuracy49QC2500148WOQualcomm Ref. No. 2500148WO50 uncertainty, while still being able to code down to values as small as six millimeters. The uncertainty can then be coded on eight bits, as the binary encoding of K.

[0161] For high accuracy extended uncertainty, C = 0.3 and x = 0.02594, with 0 * K * 253, and r = 200 m with K=254, and r > 200 m with K=255, a suitably useful range between 0 and 200 meters is achieved for the high accuracy uncertainty, while still being able to code down to values as small as eight millimeters. The uncertainty can then be coded on eight bits, as the binary encoding of K.

[0162] AIML positioning has shown excellent positioning accuracy in stringent NLOS conditions. For data collection for training and / or monitoring the performance of a machine learning model, Part B data (e.g., ground truth label, quality indicator label, timestamp of label) is needed and should include at least the (approximate) ground truth label (e.g., location information or positioning measurements, such as RSTD, RTOA, UE Rx-Tx time difference, gNB Rx-Tx time difference, LOS indicator, etc.). The ground truth label may be generated with different positioning modalities and is subject to errors. The quality indicator label is therefore intended to express the error, confidence, or uncertainty of the ground truth label.

[0163] There are some existing IES that can be reused to convey such label quality. However, there is no signaling to indicate supported labeling features or request them during data collection. The request may also need to indicate conditions or prioritizations for labeling and considering the label quality field as part of data collection.

[0164] Accordingly, the present disclosure provides signaling techniques for requesting labeling and label quality (including prioritization and / or conditions), as well as related capability and support signaling. In some cases, the labeling assistance and generation may be signaled from the wireless device (e.g., a UE, a PRU, or gNB) to the network (e.g., an LMF or a network data analytics function (NWDAF)). In some cases, the labeling assistance and generation may be signaled from the network to the wireless device.

[0165] Note that for the techniques disclosed below, there may be separate signaling for normal AIML positioning and data collection, or there may be unified signaling for both normal AIML positioning and data collection. In the latter case, additional indications may be included in the signaling to explicitly indicate which parts are specific to data collection.50QC2500148WOQualcomm Ref. No. 2500148WO51

[0166] The following techniques are directed to the case where the wireless device (e.g., a UE or gNB) generates the Part B component for data collection and needs to provide that information to the network entity (e.g., an LMF or NWDAF).

[0167] In some cases, the network entity may transmit a request to the wireless device for labels and corresponding labeling features (e.g., timestamps, types, resolution, accuracy, quality, source) for AIML positioning data collection (training and / or monitoring), subject to the capabilities of the wireless device (as described below). Where the wireless device is a UE, the request may be transmitted via LPP signaling (e.g., in an LPP Request Location Information message or a dedicated LPP message). Where the wireless device is a gNB, the request may be transmitted via NRPPa (e.g., in an NRPPa Request Measurement message). In some cases, the request may be transmitted via dedicated signaling (e.g., a Data Collection Request message).

[0168] In some cases, the request for labels and labeling features for AIML positioning data collection may indicate one or more conditions regarding when to consider / provide labeling, such as based on whether a labeling source is available, guaranteed accuracy, guaranteed quality, device status (e.g., LOS condition), etc. For example, the request may indicate to consider / provide labeling for source X if certain measurements (e.g., RSRP, SINR, number of anchor nodes (i.e., devices with known locations), delay spread, etc.) by source X satisfy a threshold. As another example, the request may indicate to consider / provide labeling if the accuracy / quality of the label is at least X. As yet another example, the request may indicate to provide labelling if the wireless device has at least Y anchors with a LOS condition. As yet another example, the request may indicate to always provide labelling, without conditions.

[0169] In some cases, the request for labels and labeling features for AIML positioning data collection may indicate one or more conditions regarding when to provide label quality metrics / indicators in the report, such as depending on the source, guaranteed accuracy, device status (e.g., LOS condition), etc. In some cases, the request may indicate that the wireless device is to provide label quality metrics / indicators if the labeling is performed by source X, or if the labeling accuracy is less than Y, or if there are fewer than Z anchors with LOS condition, or the like. Alternatively, the request may indicate that the wireless device is to always provide label quality metrics / indicators.51QC2500148WOQualcomm Ref. No. 2500148WO52

[0170] In some cases, the request for labels and labeling features for AIML positioning data collection may indicate one or more conditions regarding prioritization. For example, the request may include a listing of preferred labeling types (e.g., ordered based preference), a listing of preferred labeling resolutions (ordered based on preference), a listing of preferred labeling accuracies (ordered based on preference), a listing of preferred labeling qualities (ordered based on preference), a listing of preferred labeling sources (ordered based on preference), and / or the like.

[0171] Referring now to the response from the wireless device, the wireless device may provide the requested labeling and corresponding label quality for Part B data (optionally based on the prioritization(s) and / or condition(s) in the request). If the wireless device cannot support the requested labeling and / or label quality, it may report a Do-Not-Use indicator for the label(s) or label quality metric(s) / indicator(s). Alternatively, if the wireless device cannot support the requested labeling and / or label quality, it may skip reporting (i.e., refrain from reporting). In some cases, the device response may be predefined or configured by the request message.

[0172] In some cases, the wireless device (e.g., a UE (PRU or non-PRU), a gNB) may indicate to the network entity (e.g., LMF, NWDAF) supported labeling and labeling features (e.g., timestamps, types, resolution, accuracy, quality, source) for AIML positioning data collection (training and / or monitoring). In some cases, the indicated capabilities may include whether or not the wireless device supports labeling (Part B), supported label types (one or more label types may be supported), one or more capabilities related to direct AIML positioning, and one or more capabilities related to AIML assisted positioning. With respect to direct AIML positioning, the device capabilities may indicate one or more types supported under the “LocationCoordinateTypes” IE 820 in FIG. 8 (e.g., an “EllipsoidPointWithAltitudeAndUncertaintyEllipsoid” IE 910). With respect to AIML assisted positioning, the device capabilities may indicate whether or not the device supports measurements such as RSTD, RTOA, UE Rx-Tx time difference, gNB Rx-Tx time difference, LOS and / or NLOS indicator(s) (hard / soft), AoD (azimuth and / or zenith), AoA (azimuth and / or zenith), RSRP, RSRPP, reference signal carrier phase (RSCP), reference signal carrier phase difference (RSCPD), or a combination thereof.52QC2500148WOQualcomm Ref. No. 2500148WO53

[0173] With respect to the wireless device’s indicated support for label resolution, the wireless device may indicate that it supports one or more label resolutions. For direct AIML positioning, the supported positioning resolution may be millimeter resolution, centimeter level resolution, meter level resolution, tens of meters resolution, latitude resolution, longitude resolution, elevation resolution, etc. For AIML assisted positioning, the supported timing resolution may be nanosecond level resolution, tens of nanoseconds level resolution, hundreds of nanoseconds level resolution, microsecond level resolution, etc. The angle resolution may be provided in degrees, minutes, etc., the LOS resolution may be provided as hard or soft value and / or a number of levels, and so on.

[0174] With respect to the wireless device’s indicated support for label accuracy, the wireless device may indicate that it supports one or more label accuracies. For direct AIML positioning, the supported accuracy resolution may be millimeter resolution, centimeter level resolution, meter level resolution, tens of meters resolution, latitude accuracy, longitude accuracy, elevation accuracy (e.g., at Kth-percentile), etc. For AIML assisted positioning, the wireless device may indicate supported timing accuracy, angle accuracy, LOS accuracy, etc. The LOS accuracy may be indicated as a hard or soft value, as a misdetection rate / probability, and / or a false-alarm probability (e.g., at the Kth-percentile).

[0175] With respect to the wireless device’s indicated support for label quality, the wireless device may indicate that it supports one or more label qualities. For direct AIML positioning, the supported label qualities may indicate an uncertainty latitude, uncertainty longitude, uncertainty elevation, location uncertainty, horizontal uncertainty, vertical uncertainty, uncertainty ellipse, uncertainty circle, uncertainty ellipsoid, uncertainty spheroid, uncertainty semi major, uncertainty semi minor, uncertainty altitude, confidence (e.g., as a value between 0 and 100), vertical confidence, horizontal confidence, etc. For AIML assisted positioning, the wireless device may indicate supported time quality, timing uncertainty, angle uncertainty, LOS uncertainty (as a hard or soft value), etc.

[0176] With respect to the wireless device’s indicated support for label source, the wireless device may indicate that it supports one or more labeling sources. A labeling “source” refers to the technology and / or method used to generate the label. For example, the wireless device may indicate supported RAT-dependent positioning method(s) / technology(ies) (e.g., downlink time difference of arrival (DL-TDOA), round-trip-time53QC2500148WOQualcomm Ref. No. 2500148WO54(RTT), downlink angle-of-departure (DL-AoD), etc.) and / or RAT-independent positioning method(s) / technology(ies) (e.g., global navigation satellite system (GNSS), Wi-Fi, UWB, BLUETOOTH®, sensors (e.g., inertial measurement unit (IMU), acoustic, graphical / camera / Lidar, etc.), synthetic (e.g., using digital twin, etc.)).

[0177] In some cases, the capability signaling may be included in an LPP capability exchange (e.g., in an LPP Provide Capabilities message), an NRPPa capability message (e.g., in an NRPPa TRP Information message), a dedicated data collection message, or in a response to a request from the network entity.

[0178] The following techniques are directed to the case where the network entity (e.g., an LMF or NWDAF) generates the Part B component for data collection and needs to provide that information to the wireless device (e.g., a UE or gNB).

[0179] In some cases, the wireless device may transmit a request to the network entity for labels and corresponding labeling features (e.g., timestamps, types, resolution, accuracy, quality, source) for AIML positioning data collection (training and / or monitoring), subject to assistance indications (as described below). Where the wireless device is a UE, the request may be transmitted via LPP signaling (e.g., in an LPP Request Assistance Data message or a dedicated LPP message). Where the wireless device is a gNB, the request may be transmitted via NRPPa (e.g., in an NRPPa Request Assistance Information message). In some cases, the request may be transmitted via dedicated signaling (e.g., a Data Collection Request message).

[0180] In some cases, the request for labels and labeling features for AIML positioning data collection may indicate one or more conditions regarding when to consider / provide labeling, such as based on whether a labeling source is available, guaranteed accuracy, guaranteed quality, device status (e.g., LOS condition), etc. For example, the request may indicate to consider / provide labeling for source X if certain measurements (e.g., RSRP, SINR, number of anchors, delay spread, etc.) by source X satisfy a threshold. As another example, the request may indicate to consider / provide labeling if the accuracy / quality of the label is at least X. As yet another example, the request may indicate to provide labelling if the wireless device has at least Y anchors with a LOS condition. As yet another example, the request may indicate to always provide labelling, without conditions.54QC2500148WOQualcomm Ref. No. 2500148WO55

[0181] In some cases, the request for labels and labeling features for AIML positioning data collection may indicate one or more conditions regarding when to provide label quality metrics / indicators in the report, such as depending on the source, guaranteed accuracy, device status (e.g., LOS condition), etc. In some cases, the request may indicate that the network entity is to provide label quality metrics / indicators if the labeling is performed by source X, or if the labeling accuracy is less than Y, or if there are fewer than Z anchors with LOS condition, or the like. Alternatively, the request may indicate that the network entity is to always provide label quality metrics / indicators.

[0182] In some cases, the request for labels and labeling features for AIML positioning data collection may indicate one or more conditions regarding prioritization. For example, the request may include a listing of preferred labeling types (e.g., ordered based preference), a listing of preferred labeling resolutions (ordered based on preference), a listing of preferred labeling accuracies (ordered based on preference), a listing of preferred labeling qualities (ordered based on preference), a listing of preferred labeling sources (ordered based on preference), and / or the like.

[0183] Referring now to the response from the network entity, the network entity may provide the requested labeling and corresponding label quality for Part B data (optionally based on the prioritization(s) and / or condition(s) in the request). If the network entity cannot support the requested labeling and / or label quality, it may report a Do-Not-Use indicator for the label(s) or label quality metric(s) / indicator(s). Alternatively, if the network entity cannot support the requested labeling and / or label quality, it may skip reporting (i.e., refrain from reporting). In some cases, the network response may be predefined or configured by the request message.

[0184] In some cases, the network entity may indicate to the wireless device the availability of assistance for labeling and labeling features (e.g., timestamps, types, resolution, accuracy, quality, source) for AIML positioning data collection (training and / or monitoring). In some cases, the indicated assistance may include whether or not assistance is available for labeling (Part B) and / or the available assistance for label types (one or more label types may be available). With respect to direct AIML positioning, the available assistance may be for one or more types supported under the “LocationCoordinateTypes” IE 820 in FIG. 8 (e.g., an “EllipsoidPointWithAltitudeAndUncertaintyEllipsoid” IE 910). With respect to AIML assisted positioning, the available assistance may be for measurements55QC2500148WOQualcomm Ref. No. 2500148WO56 such as RSTD, RTOA, UE Rx-Tx time difference, gNB Rx-Tx time difference, LOS and / or NLOS indicator(s) (hard / soft), AoD (azimuth and / or zenith), AoA (azimuth and / or zenith), RSRP, RSRPP, RSCP, RSCPD, or a combination thereof.

[0185] With respect to the available assistance for label resolution, the network entity may indicate that one or more label resolutions are available. For direct AIML positioning, the available positioning resolution may be millimeter resolution, centimeter level resolution, meter level resolution, tens of meters resolution, latitude resolution, longitude resolution, elevation resolution, etc. For AIML assisted positioning, the available timing resolution may be nanosecond level resolution, tens of nanoseconds level resolution, hundreds of nanoseconds level resolution, microsecond level resolution, etc. The angle resolution may be provided in degrees, minutes, etc., the LOS resolution may be provided as hard or soft value and / or a number of levels, and so on.

[0186] With respect to the available assistance for label accuracy, the network entity may indicate that one or more label accuracies are available. For direct AIML positioning, the available accuracy resolution may be millimeter resolution, centimeter level resolution, meter level resolution, tens of meters resolution, latitude accuracy, longitude accuracy, elevation accuracy (e.g., at Kth-percentile), etc. For AIML assisted positioning, the available assistance may include the supported timing accuracy, angle accuracy, LOS accuracy, etc. The LOS accuracy may be indicated as a hard or soft value, as a misdetection rate / probability, and / or a false-alarm probability (e.g., at the Kth-percentile).

[0187] With respect to the available label quality, the network entity may indicate that one or more label qualities are available. For direct AIML positioning, the available label qualities may include an uncertainty latitude, uncertainty longitude, uncertainty elevation, location uncertainty, horizontal uncertainty, vertical uncertainty, uncertainty ellipse, uncertainty circle, uncertainty ellipsoid, uncertainty spheroid, uncertainty semi major, uncertainty semi minor, uncertainty altitude, confidence (e.g., as a value between 0 and 100), vertical confidence, horizontal confidence, etc. For AIML assisted positioning, the available assistance may include time quality, timing uncertainty, angle uncertainty, LOS uncertainty (as a hard or soft value), etc.

[0188] With respect to the available label source, the network entity may indicate that one or more label sources are available. For example, the network entity may indicate the available RAT-dependent positioning method(s) (e.g., DL-TDOA, RTT, DL-AoD, etc.)56QC2500148WOQualcomm Ref. No. 2500148WO57 and / or RAT-independent positioning method(s) (e.g., GNSS, Wi-Fi, UWB, BLUETOOTH®, sensors (e.g., IMU, acoustic, graphical / camera / Lidar, etc.), synthetic (e.g., using digital twin, etc.)).

[0189] In some cases, the assistance signaling may be included in an LPP assistance data transfer procedure (e.g., in an LPP Provide Assistance Data message), an NRPPa assistance message, a dedicated data collection message, or in a response to a request from the wireless device.

[0190] FIG. 10 illustrates an example method 1000 of data collection for a machine learning model for positioning performed, according to aspects of the disclosure. In an aspect, method 1000 may be performed by a first device (e.g., any of the UEs, base stations, or network entities described herein).

[0191] At operation 1010, the first device may receive, from a second device (e.g., any of the UEs, base stations, or network entities described herein), a request for labels for training or monitoring the machine learning model and labeling features corresponding to the labels.

[0192] In an aspect, where the first device is a UE, operation 1010 may be performed by the one or more WWAN transceivers 310, the one or more short-range wireless transceivers 320, the one or more processors 342, memory 340, and / or positioning component 348, any or all of which may be considered means for performing this operation.

[0193] In an aspect, where the first device is a base station or base station component, operation 1010 may be performed by the one or more WWAN transceivers 350, the one or more short-range wireless transceivers 360, the one or more network transceivers 380, the one or more processors 384, memory 386, and / or positioning component 388, any or all of which may be considered means for performing this operation.

[0194] In an aspect, where the first device is a network entity, operation 1010 may be performed by the one or more network transceivers 390, the one or more processors 394, memory 396, and / or positioning component 398, any or all of which may be considered means for performing this operation.

[0195] At operation 1020, the first device may generate a set of labels and a set of labeling features, where the set of labels includes at least a set of ground truth labels for output by the machine learning model based on a set of channel measurements for input into the57QC2500148WOQualcomm Ref. No. 2500148WO58 machine learning model, and where the set of labeling features includes at least a set of quality indicators associated with the set of ground truth labels.

[0196] In an aspect, where the first device is a UE, operation 1020 may be performed by the one or more WWAN transceivers 310, the one or more short-range wireless transceivers 320, the one or more processors 342, memory 340, and / or positioning component 348, any or all of which may be considered means for performing this operation.

[0197] In an aspect, where the first device is a base station or base station component, operation 1020 may be performed by the one or more WWAN transceivers 350, the one or more short-range wireless transceivers 360, the one or more network transceivers 380, the one or more processors 384, memory 386, and / or positioning component 388, any or all of which may be considered means for performing this operation.

[0198] In an aspect, where the first device is a network entity, operation 1020 may be performed by the one or more network transceivers 390, the one or more processors 394, memory 396, and / or positioning component 398, any or all of which may be considered means for performing this operation.

[0199] As will be appreciated, by enabling the second device to request the set of labels and the corresponding set of labeling features, a technical advantage of the method 1000 is improved data collection for machine learning model positioning.

[0200] In the detailed description above it can be seen that different features are grouped together in examples. This manner of disclosure should not be understood as an intention that the example clauses have more features than are explicitly mentioned in each clause. Rather, the various aspects of the disclosure may include fewer than all features of an individual example clause disclosed. Therefore, the following clauses should hereby be deemed to be incorporated in the description, wherein each clause by itself can stand as a separate example. Although each dependent clause can refer in the clauses to a specific combination with one of the other clauses, the aspect(s) of that dependent clause are not limited to the specific combination. It will be appreciated that other example clauses can also include a combination of the dependent clause aspect(s) with the subject matter of any other dependent clause or independent clause or a combination of any feature with other dependent and independent clauses. The various aspects disclosed herein expressly include these combinations, unless it is explicitly expressed or can be readily inferred that a specific combination is not intended (e.g., contradictory aspects, such as defining an58QC2500148WOQualcomm Ref. No. 2500148WO59 element as both an electrical insulator and an electrical conductor). Furthermore, it is also intended that aspects of a clause can be included in any other independent clause, even if the clause is not directly dependent on the independent clause.

[0201] Implementation examples are described in the following numbered clauses:

[0202] Clause 1. A method of data collection for a machine learning model for positioning performed by a first device, comprising: receiving, from a second device, a request for labels for training or monitoring the machine learning model and labeling features corresponding to the labels; and generating a set of labels and a set of labeling features, wherein the set of labels includes at least a set of ground truth labels for output by the machine learning model based on a set of channel measurements for input into the machine learning model, and wherein the set of labeling features includes at least a set of quality indicators associated with the set of ground truth labels.

[0203] Clause 2. The method of clause 1, wherein the request is received in: a Long-Term Evolution (LTE) positioning protocol (LPP) request location information message, a New Radio positioning protocol type A (NRPPa) measurement request message, mobile originated location request (MO-LR), or a data collection request message.

[0204] Clause 3. The method of any of clauses 1 to 2, wherein the request includes one or more conditions indicating whether to provide the labels.

[0205] Clause 4. The method of clause 3, wherein the one or more conditions comprise: a condition indicating to provide the labels based on channel measurements from one or more sources of the labels satisfying a measurement threshold, a condition indicating to provide the labels based on accuracies associated with the labels satisfying an accuracy threshold, a condition indicating to provide the labels based on quality indicators associated with the labels satisfying a quality threshold, a condition indicating to provide the labels based on a number of anchor nodes in a line-of-sight (LOS) condition satisfying an anchor threshold, or any combination thereof.

[0206] Clause 5. The method of any of clauses 1 to 4, wherein the request includes one or more conditions indicating whether to provide quality indicators associated with the labels.

[0207] Clause 6. The method of clause 5, wherein the one or more conditions comprise: a condition indicating to provide the quality indicators associated with the set of labels based on whether one or more sources provided the set of labels, a condition indicating to provide the quality indicators associated with the set of labels based on accuracies59QC2500148WOQualcomm Ref. No. 2500148WO60 associated with the set of labels satisfying an accuracy threshold, a condition indicating to provide the quality indicators associated with the set of labels based on a number of anchor nodes in an LOS condition satisfying an anchor threshold, or any combination thereof.

[0208] Clause 7. The method of any of clauses 1 to 6, wherein: the request indicates one or more preferences for label types, label resolution, label accuracy, label quality, label source, or any combination thereof of the labeling features, and the one or more preferences are indicated based on an order of the label types, the label resolution, the label accuracy, the label quality, the label source, or the combination thereof in the request.

[0209] Clause 8. The method of any of clauses 1 to 7, further comprising: transmitting, to the second device, a do-not-use indicator indicating that the set of labels is not to be used.

[0210] Clause 9. The method of any of clauses 1 to 8, further comprising: transmitting the set of labels to the second device; and transmitting the set of labeling features to the second device.

[0211] Clause 10. The method of clause 9, wherein: the set of labels is a subset of the labels requested by the second device, the set of labeling features is a subset of the labeling features requested by the second device, or a combination thereof.

[0212] Clause 11. The method of clause 10, wherein: the set of labels is a subset of the labels requested by the second device based on capabilities of the first device related to labeling, the set of labeling features is a subset of the labeling features requested by the second device based on the capabilities of the first device related to labeling, or a combination thereof.

[0213] Clause 12. The method of any of clauses 1 to 11, further comprising: transmitting, to the second device, a capability message indicating one or more capabilities of the first device related to whether the first device supports labeling, one or more label types supported by the first device, or both.

[0214] Clause 13. The method of clause 12, wherein the one or more label types comprise: an ellipsoid point, an ellipsoid point with uncertainty circle, an ellipsoid point with uncertainty ellipse, a polygon, an ellipsoid point with altitude, an ellipsoid point with altitude and uncertainty ellipsoid, an ellipsoid arc, a high accuracy ellipsoid point with uncertainty ellipse, a high accuracy ellipsoid point with altitude and uncertainty ellipsoid, a high accuracy ellipsoid point with scalable uncertainty ellipse, a high accuracy ellipsoid60QC2500148WOQualcomm Ref. No. 2500148WO61 point with altitude and scalable uncertainty ellipsoid, a local two-dimensional point with uncertainty ellipse, a local three-dimensional point with uncertainty ellipsoid, or any combination thereof.

[0215] Clause 14. The method of any of clauses 12 to 13, wherein the one or more label types comprise one or more measurement types comprising: reference signal time difference (RSTD), relative time of arrival (RTOA), reception-to-transmission (Rx-Tx) time difference, line-of-sight (LOS) indicator, non-line-of-sight (NLOS) indicator, angle of departure (AoD), angle of arrival (AoA), reference signal received power (RSRP), path RSRP (RSRPP), reference signal carrier phase (RSCP), reference signal carrier phase difference (RSCPD), or any combination thereof.

[0216] Clause 15. The method of any of clauses 12 to 14, wherein the one or more capabilities include: one or more label resolutions supported by the first device, one or more label accuracies supported by the first device, one or more label quality indicators supported by the first device, one or more label sources supported by the first device, or any combination thereof.

[0217] Clause 16. The method of any of clauses 12 to 15, wherein the capabilities message is: an LPP provide capabilities message, an NRPPa transmission-reception point (TRP) information message, a data collection message, or a response to a request from the second device.

[0218] Clause 17. The method of any of clauses 1 to 16, wherein the set of quality indicators indicate: an uncertainty latitude, an uncertainty longitude, an uncertainty elevation, a location uncertainty, a horizontal uncertainty, a vertical uncertainty, an uncertainty ellipse, an uncertainty circle, an uncertainty ellipsoid, an uncertainty spheroid, an uncertainty semi major, an uncertainty semi minor, an uncertainty altitude, a confidence, a vertical confidence, a horizontal confidence, a time quality, a timing uncertainty, an angle uncertainty, a line-of-sight (LOS) uncertainty, or any combination thereof.

[0219] Clause 18. The method of any of clauses 1 to 17, further comprising: training the machine learning model with the set of channel measurements for input into the machine learning model and the set of labels for output by the machine learning model; or monitoring performance of the machine learning model using the set of channel measurements for input into the machine learning model and the set of labels for output by the machine learning model.61QC2500148WOQualcomm Ref. No. 2500148WO62

[0220] Clause 19. The method of any of clauses 1 to 18, wherein: the first device is a user equipment (UE) or a base station, and the second device is a network entity.

[0221] Clause 20. The method of any of clauses 1 to 19, wherein: the first device is a network entity, and the second device is a UE or a base station.

[0222] Clause 21. A first device, comprising: one or more memories; one or more transceivers; and one or more processors communicatively coupled to the one or more memories and the one or more transceivers, the one or more processors, either alone or in combination, configured to: receive, via the one or more transceivers, from a second device, a request for labels for training or monitoring the machine learning model and labeling features corresponding to the labels; and generate a set of labels and a set of labeling features, wherein the set of labels includes at least a set of ground truth labels for output by the machine learning model based on a set of channel measurements for input into the machine learning model, and wherein the set of labeling features includes at least a set of quality indicators associated with the set of ground truth labels.

[0223] Clause 22. The first device of clause 21, wherein the request is received in: a Long-Term Evolution (LTE) positioning protocol (LPP) request location information message, a New Radio positioning protocol type A (NRPPa) measurement request message, mobile originated location request (MO-LR), or a data collection request message.

[0224] Clause 23. The first device of any of clauses 21 to 22, wherein the request includes one or more conditions indicating whether to provide the labels.

[0225] Clause 24. The first device of clause 23, wherein the one or more conditions comprise: a condition indicating to provide the labels based on channel measurements from one or more sources of the labels satisfying a measurement threshold, a condition indicating to provide the labels based on accuracies associated with the labels satisfying an accuracy threshold, a condition indicating to provide the labels based on quality indicators associated with the labels satisfying a quality threshold, a condition indicating to provide the labels based on a number of anchor nodes in a line-of-sight (LOS) condition satisfying an anchor threshold, or any combination thereof.

[0226] Clause 25. The first device of any of clauses 21 to 24, wherein the request includes one or more conditions indicating whether to provide quality indicators associated with the labels.62QC2500148WOQualcomm Ref. No. 2500148WO63

[0227] Clause 26. The first device of clause 25, wherein the one or more conditions comprise: a condition indicating to provide the quality indicators associated with the set of labels based on whether one or more sources provided the set of labels, a condition indicating to provide the quality indicators associated with the set of labels based on accuracies associated with the set of labels satisfying an accuracy threshold, a condition indicating to provide the quality indicators associated with the set of labels based on a number of anchor nodes in an LOS condition satisfying an anchor threshold, or any combination thereof.

[0228] Clause 27. The first device of any of clauses 21 to 26, wherein: the request indicates one or more preferences for label types, label resolution, label accuracy, label quality, label source, or any combination thereof of the labeling features, and the one or more preferences are indicated based on an order of the label types, the label resolution, the label accuracy, the label quality, the label source, or the combination thereof in the request.

[0229] Clause 28. The first device of any of clauses 21 to 27, wherein the one or more processors, either alone or in combination, are further configured to: transmit, via the one or more transceivers, to the second device, a do-not-use indicator indicating that the set of labels is not to be used.

[0230] Clause 29. The first device of any of clauses 21 to 28, wherein the one or more processors, either alone or in combination, are further configured to: transmit, via the one or more transceivers, the set of labels to the second device; and transmit, via the one or more transceivers, the set of labeling features to the second device.

[0231] Clause 30. The first device of clause 29, wherein: the set of labels is a subset of the labels requested by the second device, the set of labeling features is a subset of the labeling features requested by the second device, or a combination thereof.

[0232] Clause 31. The first device of clause 30, wherein: the set of labels is a subset of the labels requested by the second device based on capabilities of the first device related to labeling, the set of labeling features is a subset of the labeling features requested by the second device based on the capabilities of the first device related to labeling, or a combination thereof.

[0233] Clause 32. The first device of any of clauses 21 to 31, wherein the one or more processors, either alone or in combination, are further configured to: transmit, via the one or more63QC2500148WOQualcomm Ref. No. 2500148WO64 transceivers, to the second device, a capability message indicating one or more capabilities of the first device related to whether the first device supports labeling, one or more label types supported by the first device, or both.

[0234] Clause 33. The first device of clause 32, wherein the one or more label types comprise: an ellipsoid point, an ellipsoid point with uncertainty circle, an ellipsoid point with uncertainty ellipse, a polygon, an ellipsoid point with altitude, an ellipsoid point with altitude and uncertainty ellipsoid, an ellipsoid arc, a high accuracy ellipsoid point with uncertainty ellipse, a high accuracy ellipsoid point with altitude and uncertainty ellipsoid, a high accuracy ellipsoid point with scalable uncertainty ellipse, a high accuracy ellipsoid point with altitude and scalable uncertainty ellipsoid, a local two-dimensional point with uncertainty ellipse, a local three-dimensional point with uncertainty ellipsoid, or any combination thereof.

[0235] Clause 34. The first device of any of clauses 32 to 33, wherein the one or more label types comprise one or more measurement types comprising: reference signal time difference (RSTD), relative time of arrival (RTOA), reception-to-transmission (Rx-Tx) time difference, line-of-sight (LOS) indicator, non-line-of-sight (NLOS) indicator, angle of departure (AoD), angle of arrival (AoA), reference signal received power (RSRP), path RSRP (RSRPP), reference signal carrier phase (RSCP), reference signal carrier phase difference (RSCPD), or any combination thereof.

[0236] Clause 35. The first device of any of clauses 32 to 34, wherein the one or more capabilities include: one or more label resolutions supported by the first device, one or more label accuracies supported by the first device, one or more label quality indicators supported by the first device, one or more label sources supported by the first device, or any combination thereof.

[0237] Clause 36. The first device of any of clauses 32 to 35, wherein the capabilities message is: an LPP provide capabilities message, an NRPPa transmission-reception point (TRP) information message, a data collection message, or a response to a request from the second device.

[0238] Clause 37. The first device of any of clauses 21 to 36, wherein the set of quality indicators indicate: an uncertainty latitude, an uncertainty longitude, an uncertainty elevation, a location uncertainty, a horizontal uncertainty, a vertical uncertainty, an uncertainty ellipse, an uncertainty circle, an uncertainty ellipsoid, an uncertainty spheroid, an64QC2500148WOQualcomm Ref. No. 2500148WO65 uncertainty semi major, an uncertainty semi minor, an uncertainty altitude, a confidence, a vertical confidence, a horizontal confidence, a time quality, a timing uncertainty, an angle uncertainty, a line-of-sight (LOS) uncertainty, or any combination thereof.

[0239] Clause 38. The first device of any of clauses 21 to 37, wherein the one or more processors, either alone or in combination, are further configured to: train the machine learning model with the set of channel measurements for input into the machine learning model and the set of labels for output by the machine learning model; or monitor performance of the machine learning model using the set of channel measurements for input into the machine learning model and the set of labels for output by the machine learning model.

[0240] Clause 39. The first device of any of clauses 21 to 38, wherein: the first device is a user equipment (UE) or a base station, and the second device is a network entity.

[0241] Clause 40. The first device of any of clauses 21 to 39, wherein: the first device is a network entity, and the second device is a UE or a base station.

[0242] Clause 41. A first device, comprising: means for receiving, from a second device, a request for labels for training or monitoring the machine learning model and labeling features corresponding to the labels; and means for generating a set of labels and a set of labeling features, wherein the set of labels includes at least a set of ground truth labels for output by the machine learning model based on a set of channel measurements for input into the machine learning model, and wherein the set of labeling features includes at least a set of quality indicators associated with the set of ground truth labels.

[0243] Clause 42. The first device of clause 41, wherein the request is received in: a Long-Term Evolution (LTE) positioning protocol (LPP) request location information message, a New Radio positioning protocol type A (NRPPa) measurement request message, mobile originated location request (MO-LR), or a data collection request message.

[0244] Clause 43. The first device of any of clauses 41 to 42, wherein the request includes one or more conditions indicating whether to provide the labels.

[0245] Clause 44. The first device of clause 43, wherein the one or more conditions comprise: a condition indicating to provide the labels based on channel measurements from one or more sources of the labels satisfying a measurement threshold, a condition indicating to provide the labels based on accuracies associated with the labels satisfying an accuracy threshold, a condition indicating to provide the labels based on quality indicators associated with the labels satisfying a quality threshold, a condition indicating to provide65QC2500148WOQualcomm Ref. No. 2500148WO66 the labels based on a number of anchor nodes in a line-of-sight (LOS) condition satisfying an anchor threshold, or any combination thereof.

[0246] Clause 45. The first device of any of clauses 41 to 44, wherein the request includes one or more conditions indicating whether to provide quality indicators associated with the labels.

[0247] Clause 46. The first device of clause 45, wherein the one or more conditions comprise: a condition indicating to provide the quality indicators associated with the set of labels based on whether one or more sources provided the set of labels, a condition indicating to provide the quality indicators associated with the set of labels based on accuracies associated with the set of labels satisfying an accuracy threshold, a condition indicating to provide the quality indicators associated with the set of labels based on a number of anchor nodes in an LOS condition satisfying an anchor threshold, or any combination thereof.

[0248] Clause 47. The first device of any of clauses 41 to 46, wherein: the request indicates one or more preferences for label types, label resolution, label accuracy, label quality, label source, or any combination thereof of the labeling features, and the one or more preferences are indicated based on an order of the label types, the label resolution, the label accuracy, the label quality, the label source, or the combination thereof in the request.

[0249] Clause 48. The first device of any of clauses 41 to 47, further comprising: means for transmitting, to the second device, a do-not-use indicator indicating that the set of labels is not to be used.

[0250] Clause 49. The first device of any of clauses 41 to 48, further comprising: means for transmitting the set of labels to the second device; and means for transmitting the set of labeling features to the second device.

[0251] Clause 50. The first device of clause 49, wherein: the set of labels is a subset of the labels requested by the second device, the set of labeling features is a subset of the labeling features requested by the second device, or a combination thereof.

[0252] Clause 51. The first device of clause 50, wherein: the set of labels is a subset of the labels requested by the second device based on capabilities of the first device related to labeling, the set of labeling features is a subset of the labeling features requested by the second66QC2500148WOQualcomm Ref. No. 2500148WO67 device based on the capabilities of the first device related to labeling, or a combination thereof.

[0253] Clause 52. The first device of any of clauses 41 to 51, further comprising: means for transmitting, to the second device, a capability message indicating one or more capabilities of the first device related to whether the first device supports labeling, one or more label types supported by the first device, or both.

[0254] Clause 53. The first device of clause 52, wherein the one or more label types comprise: an ellipsoid point, an ellipsoid point with uncertainty circle, an ellipsoid point with uncertainty ellipse, a polygon, an ellipsoid point with altitude, an ellipsoid point with altitude and uncertainty ellipsoid, an ellipsoid arc, a high accuracy ellipsoid point with uncertainty ellipse, a high accuracy ellipsoid point with altitude and uncertainty ellipsoid, a high accuracy ellipsoid point with scalable uncertainty ellipse, a high accuracy ellipsoid point with altitude and scalable uncertainty ellipsoid, a local two-dimensional point with uncertainty ellipse, a local three-dimensional point with uncertainty ellipsoid, or any combination thereof.

[0255] Clause 54. The first device of any of clauses 52 to 53, wherein the one or more label types comprise one or more measurement types comprising: reference signal time difference (RSTD), relative time of arrival (RTOA), reception-to-transmission (Rx-Tx) time difference, line-of-sight (LOS) indicator, non-line-of-sight (NLOS) indicator, angle of departure (AoD), angle of arrival (AoA), reference signal received power (RSRP), path RSRP (RSRPP), reference signal carrier phase (RSCP), reference signal carrier phase difference (RSCPD), or any combination thereof.

[0256] Clause 55. The first device of any of clauses 52 to 54, wherein the one or more capabilities include: one or more label resolutions supported by the first device, one or more label accuracies supported by the first device, one or more label quality indicators supported by the first device, one or more label sources supported by the first device, or any combination thereof.

[0257] Clause 56. The first device of any of clauses 52 to 55, wherein the capabilities message is: an LPP provide capabilities message, an NRPPa transmission-reception point (TRP) information message, a data collection message, or a response to a request from the second device.67QC2500148WOQualcomm Ref. No. 2500148WO68

[0258] Clause 57. The first device of any of clauses 41 to 56, wherein the set of quality indicators indicate: an uncertainty latitude, an uncertainty longitude, an uncertainty elevation, a location uncertainty, a horizontal uncertainty, a vertical uncertainty, an uncertainty ellipse, an uncertainty circle, an uncertainty ellipsoid, an uncertainty spheroid, an uncertainty semi major, an uncertainty semi minor, an uncertainty altitude, a confidence, a vertical confidence, a horizontal confidence, a time quality, a timing uncertainty, an angle uncertainty, a line-of-sight (LOS) uncertainty, or any combination thereof.

[0259] Clause 58. The first device of any of clauses 41 to 57, further comprising: means for training the machine learning model with the set of channel measurements for input into the machine learning model and the set of labels for output by the machine learning model; or means for monitoring performance of the machine learning model using the set of channel measurements for input into the machine learning model and the set of labels for output by the machine learning model.

[0260] Clause 59. The first device of any of clauses 41 to 58, wherein: the first device is a user equipment (UE) or a base station, and the second device is a network entity.

[0261] Clause 60. The first device of any of clauses 41 to 59, wherein: the first device is a network entity, and the second device is a UE or a base station.

[0262] Clause 61. A non-transitory computer-readable medium storing computer-executable instructions that, when executed by a first device, cause the first device to: receive, from a second device, a request for labels for training or monitoring the machine learning model and labeling features corresponding to the labels; and generate a set of labels and a set of labeling features, wherein the set of labels includes at least a set of ground truth labels for output by the machine learning model based on a set of channel measurements for input into the machine learning model, and wherein the set of labeling features includes at least a set of quality indicators associated with the set of ground truth labels.

[0263] Clause 62. The non-transitory computer-readable medium of clause 61, wherein the request is received in: a Long-Term Evolution (LTE) positioning protocol (LPP) request location information message, a New Radio positioning protocol type A (NRPPa) measurement request message, mobile originated location request (MO-LR), or a data collection request message.68QC2500148WOQualcomm Ref. No. 2500148WO69

[0264] Clause 63. The non -transitory computer-readable medium of any of clauses 61 to 62, wherein the request includes one or more conditions indicating whether to provide the labels.

[0265] Clause 64. The non-transitory computer-readable medium of clause 63, wherein the one or more conditions comprise: a condition indicating to provide the labels based on channel measurements from one or more sources of the labels satisfying a measurement threshold, a condition indicating to provide the labels based on accuracies associated with the labels satisfying an accuracy threshold, a condition indicating to provide the labels based on quality indicators associated with the labels satisfying a quality threshold, a condition indicating to provide the labels based on a number of anchor nodes in a line-of-sight (LOS) condition satisfying an anchor threshold, or any combination thereof.

[0266] Clause 65. The non-transitory computer-readable medium of any of clauses 61 to 64, wherein the request includes one or more conditions indicating whether to provide quality indicators associated with the labels.

[0267] Clause 66. The non-transitory computer-readable medium of clause 65, wherein the one or more conditions comprise: a condition indicating to provide the quality indicators associated with the set of labels based on whether one or more sources provided the set of labels, a condition indicating to provide the quality indicators associated with the set of labels based on accuracies associated with the set of labels satisfying an accuracy threshold, a condition indicating to provide the quality indicators associated with the set of labels based on a number of anchor nodes in an LOS condition satisfying an anchor threshold, or any combination thereof.

[0268] Clause 67. The non-transitory computer-readable medium of any of clauses 61 to 66, wherein: the request indicates one or more preferences for label types, label resolution, label accuracy, label quality, label source, or any combination thereof of the labeling features, and the one or more preferences are indicated based on an order of the label types, the label resolution, the label accuracy, the label quality, the label source, or the combination thereof in the request.

[0269] Clause 68. The non-transitory computer-readable medium of any of clauses 61 to 67, further comprising computer-executable instructions that, when executed by the first device, cause the first device to: transmit, to the second device, a do-not-use indicator indicating that the set of labels is not to be used.69QC2500148WOQualcomm Ref. No. 2500148WO70

[0270] Clause 69. The non-transitory computer-readable medium of any of clauses 61 to 68, further comprising computer-executable instructions that, when executed by the first device, cause the first device to: transmit the set of labels to the second device; and transmit the set of labeling features to the second device.

[0271] Clause 70. The non-transitory computer-readable medium of clause 69, wherein: the set of labels is a subset of the labels requested by the second device, the set of labeling features is a subset of the labeling features requested by the second device, or a combination thereof.

[0272] Clause 71. The non-transitory computer-readable medium of clause 70, wherein: the set of labels is a subset of the labels requested by the second device based on capabilities of the first device related to labeling, the set of labeling features is a subset of the labeling features requested by the second device based on the capabilities of the first device related to labeling, or a combination thereof.

[0273] Clause 72. The non-transitory computer-readable medium of any of clauses 61 to 71, further comprising computer-executable instructions that, when executed by the first device, cause the first device to: transmit, to the second device, a capability message indicating one or more capabilities of the first device related to whether the first device supports labeling, one or more label types supported by the first device, or both.

[0274] Clause 73. The non-transitory computer-readable medium of clause 72, wherein the one or more label types comprise: an ellipsoid point, an ellipsoid point with uncertainty circle, an ellipsoid point with uncertainty ellipse, a polygon, an ellipsoid point with altitude, an ellipsoid point with altitude and uncertainty ellipsoid, an ellipsoid arc, a high accuracy ellipsoid point with uncertainty ellipse, a high accuracy ellipsoid point with altitude and uncertainty ellipsoid, a high accuracy ellipsoid point with scalable uncertainty ellipse, a high accuracy ellipsoid point with altitude and scalable uncertainty ellipsoid, a local two- dimensional point with uncertainty ellipse, a local three-dimensional point with uncertainty ellipsoid, or any combination thereof.

[0275] Clause 74. The non-transitory computer-readable medium of any of clauses 72 to 73, wherein the one or more label types comprise one or more measurement types comprising: reference signal time difference (RSTD), relative time of arrival (RTOA), reception-to-transmission (Rx-Tx) time difference, line-of-sight (LOS) indicator, non- line-of-sight (NLOS) indicator, angle of departure (AoD), angle of arrival (AoA),70QC2500148WOQualcomm Ref. No. 2500148WO71 reference signal received power (RSRP), path RSRP (RSRPP), reference signal carrier phase (RSCP), reference signal carrier phase difference (RSCPD), or any combination thereof.

[0276] Clause 75. The non -transitory computer-readable medium of any of clauses 72 to 74, wherein the one or more capabilities include: one or more label resolutions supported by the first device, one or more label accuracies supported by the first device, one or more label quality indicators supported by the first device, one or more label sources supported by the first device, or any combination thereof.

[0277] Clause 76. The non-transitory computer-readable medium of any of clauses 72 to 75, wherein the capabilities message is: an LPP provide capabilities message, an NRPPa transmission-reception point (TRP) information message, a data collection message, or a response to a request from the second device.

[0278] Clause 77. The non-transitory computer-readable medium of any of clauses 61 to 76, wherein the set of quality indicators indicate: an uncertainty latitude, an uncertainty longitude, an uncertainty elevation, a location uncertainty, a horizontal uncertainty, a vertical uncertainty, an uncertainty ellipse, an uncertainty circle, an uncertainty ellipsoid, an uncertainty spheroid, an uncertainty semi major, an uncertainty semi minor, an uncertainty altitude, a confidence, a vertical confidence, a horizontal confidence, a time quality, a timing uncertainty, an angle uncertainty, a line-of-sight (LOS) uncertainty, or any combination thereof.

[0279] Clause 78. The non-transitory computer-readable medium of any of clauses 61 to 77, further comprising computer-executable instructions that, when executed by the first device, cause the first device to: train the machine learning model with the set of channel measurements for input into the machine learning model and the set of labels for output by the machine learning model; or monitor performance of the machine learning model using the set of channel measurements for input into the machine learning model and the set of labels for output by the machine learning model.

[0280] Clause 79. The non-transitory computer-readable medium of any of clauses 61 to 78, wherein: the first device is a user equipment (UE) or a base station, and the second device is a network entity.71QC2500148WOQualcomm Ref. No. 2500148WO72

[0281] Clause 80. The non-transitory computer-readable medium of any of clauses 61 to 79, wherein: the first device is a network entity, and the second device is a UE or a base station.

[0282] Those of skill in the art will appreciate that information and signals may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

[0283] Further, those of skill in the art will appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the aspects disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.

[0284] The various illustrative logical blocks, modules, and circuits described in connection with the aspects disclosed herein may be implemented or performed with a general purpose processor, a digital signal processor (DSP), an ASIC, a field-programable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general -purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, for example, a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.72QC2500148WOQualcomm Ref. No. 2500148WO73

[0285] The methods, sequences and / or algorithms described in connection with the aspects disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in random access memory (RAM), flash memory, read-only memory (ROM), erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An example storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal (e.g., UE). In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.

[0286] In one or more example aspects, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Also, any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a website, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers.73QC2500148WOQualcomm Ref. No. 2500148WO74Combinations of the above should also be included within the scope of computer-readable media.

[0287] While the foregoing disclosure shows illustrative aspects of the disclosure, it should be noted that various changes and modifications could be made herein without departing from the scope of the disclosure as defined by the appended claims. For example, the functions, steps and / or actions of the method claims in accordance with the aspects of the disclosure described herein need not be performed in any particular order. Further, no component, function, action, or instruction described or claimed herein should be construed as critical or essential unless explicitly described as such. Furthermore, as used herein, the terms “set,” “group,” and the like are intended to include one or more of the stated elements. Also, as used herein, the terms “has,” “have,” “having,” “comprises,” “comprising,” “includes,” “including,” and the like does not preclude the presence of one or more additional elements (e.g., an element “having” A may also have B). Further, the phrase “based on” is intended to mean “based, at least in part, on” unless explicitly stated otherwise. Also, as used herein, the term “or” is intended to be inclusive when used in a series and may be used interchangeably with “and / or,” unless explicitly stated otherwise (e.g., if used in combination with “either” or “only one of’) or the alternatives are mutually exclusive (e.g., “one or more” should not be interpreted as “one and more”). Furthermore, although components, functions, actions, and instructions may be described or claimed in the singular, the plural is contemplated unless limitation to the singular is explicitly stated. Accordingly, as used herein, the articles “a,” “an,” “the,” and “said” are intended to include one or more of the stated elements. Additionally, as used herein, the terms “at least one” and “one or more” encompass “one” component, function, action, or instruction performing or capable of performing a described or claimed functionality and also “two or more” components, functions, actions, or instructions performing or capable of performing a described or claimed functionality in combination.74QC2500148WO

Claims

Qualcomm Ref. No. 2500148WO75CLAIMSWhat is claimed is:

1. A first device, comprising: one or more memories; one or more transceivers; and one or more processors communicatively coupled to the one or more memories and the one or more transceivers, the one or more processors, either alone or in combination, configured to: receive, via the one or more transceivers, from a second device, a request for labels for training or monitoring the machine learning model and labeling features corresponding to the labels; and generate a set of labels and a set of labeling features, wherein the set of labels includes at least a set of ground truth labels for output by the machine learning model based on a set of channel measurements for input into the machine learning model, and wherein the set of labeling features includes at least a set of quality indicators associated with the set of ground truth labels.

2. The first device of claim 1, wherein the request is received in: a Long-Term Evolution (LTE) positioning protocol (LPP) request location information message, a New Radio positioning protocol type A (NRPPa) measurement request message, mobile originated location request (MO-LR), or a data collection request message.

3. The first device of claim 1, wherein the request includes one or more conditions indicating whether to provide the labels.

4. The first device of claim 3, wherein the one or more conditions comprise: a condition indicating to provide the labels based on channel measurements from one or more sources of the labels satisfying a measurement threshold,75QC2500148WOQualcomm Ref. No. 2500148WO76 a condition indicating to provide the labels based on accuracies associated with the labels satisfying an accuracy threshold, a condition indicating to provide the labels based on quality indicators associated with the labels satisfying a quality threshold, a condition indicating to provide the labels based on a number of anchor nodes in a line-of-sight (LOS) condition satisfying an anchor threshold, or any combination thereof.

5. The first device of claim 1, wherein the request includes one or more conditions indicating whether to provide quality indicators associated with the labels.

6. The first device of claim 5, wherein the one or more conditions comprise: a condition indicating to provide the quality indicators associated with the set of labels based on whether one or more sources provided the set of labels, a condition indicating to provide the quality indicators associated with the set of labels based on accuracies associated with the set of labels satisfying an accuracy threshold, a condition indicating to provide the quality indicators associated with the set of labels based on a number of anchor nodes in an LOS condition satisfying an anchor threshold, or any combination thereof.

7. The first device of claim 1, wherein: the request indicates one or more preferences for label types, label resolution, label accuracy, label quality, label source, or any combination thereof of the labeling features, and the one or more preferences are indicated based on an order of the label types, the label resolution, the label accuracy, the label quality, the label source, or the combination thereof in the request.

8. The first device of claim 1, wherein the one or more processors, either alone or in combination, are further configured to:76QC2500148WOQualcomm Ref. No. 2500148WO77 transmit, via the one or more transceivers, to the second device, a do-not-use indicator indicating that the set of labels is not to be used.

9. The first device of claim 1, wherein the one or more processors, either alone or in combination, are further configured to: transmit, via the one or more transceivers, the set of labels to the second device; and transmit, via the one or more transceivers, the set of labeling features to the second device.

10. The first device of claim 9, wherein: the set of labels is a subset of the labels requested by the second device, the set of labeling features is a subset of the labeling features requested by the second device, or a combination thereof.

11. The first device of claim 10, wherein: the set of labels is a subset of the labels requested by the second device based on capabilities of the first device related to labeling, the set of labeling features is a subset of the labeling features requested by the second device based on the capabilities of the first device related to labeling, or a combination thereof.

12. The first device of claim 1, wherein the one or more processors, either alone or in combination, are further configured to: transmit, via the one or more transceivers, to the second device, a capability message indicating one or more capabilities of the first device related to whether the first device supports labeling, one or more label types supported by the first device, or both.

13. The first device of claim 12, wherein the one or more label types comprise: an ellipsoid point,77QC2500148WOQualcomm Ref. No. 2500148WO78 an ellipsoid point with uncertainty circle, an ellipsoid point with uncertainty ellipse, a polygon, an ellipsoid point with altitude, an ellipsoid point with altitude and uncertainty ellipsoid, an ellipsoid arc, a high accuracy ellipsoid point with uncertainty ellipse, a high accuracy ellipsoid point with altitude and uncertainty ellipsoid, a high accuracy ellipsoid point with scalable uncertainty ellipse, a high accuracy ellipsoid point with altitude and scalable uncertainty ellipsoid, a local two-dimensional point with uncertainty ellipse, a local three-dimensional point with uncertainty ellipsoid, or any combination thereof.

14. The first device of claim 12, wherein the one or more label types comprise one or more measurement types comprising: reference signal time difference (RSTD), relative time of arrival (RTOA), reception-to-transmission (Rx-Tx) time difference, line-of-sight (LOS) indicator, non-line-of-sight (NLOS) indicator, angle of departure (AoD), angle of arrival (AoA), reference signal received power (RSRP), path RSRP (RSRPP), reference signal carrier phase (RSCP), reference signal carrier phase difference (RSCPD), or any combination thereof.

15. The first device of claim 12, wherein the one or more capabilities include: one or more label resolutions supported by the first device, one or more label accuracies supported by the first device,78QC2500148WOQualcomm Ref. No. 2500148WO79 one or more label quality indicators supported by the first device, one or more label sources supported by the first device, or any combination thereof.

16. The first device of claim 12, wherein the capabilities message is: an LPP provide capabilities message, an NRPPa transmission-reception point (TRP) information message, a data collection message, or a response to a request from the second device.

17. The first device of claim 1, wherein the set of quality indicators indicate: an uncertainty latitude, an uncertainty longitude, an uncertainty elevation, a location uncertainty, a horizontal uncertainty, a vertical uncertainty, an uncertainty ellipse, an uncertainty circle, an uncertainty ellipsoid, an uncertainty spheroid, an uncertainty semi major, an uncertainty semi minor, an uncertainty altitude, a confidence, a vertical confidence, a horizontal confidence, a time quality, a timing uncertainty, an angle uncertainty, a line-of-sight (LOS) uncertainty, or any combination thereof.79QC2500148WOQualcomm Ref. No. 2500148WO8018. The first device of claim 1, wherein the one or more processors, either alone or in combination, are further configured to: train the machine learning model with the set of channel measurements for input into the machine learning model and the set of labels for output by the machine learning model; or monitor performance of the machine learning model using the set of channel measurements for input into the machine learning model and the set of labels for output by the machine learning model.

19. A method of data collection for a machine learning model for positioning performed by a first device, comprising: receiving, from a second device, a request for labels for training or monitoring the machine learning model and labeling features corresponding to the labels; and generating a set of labels and a set of labeling features, wherein the set of labels includes at least a set of ground truth labels for output by the machine learning model based on a set of channel measurements for input into the machine learning model, and wherein the set of labeling features includes at least a set of quality indicators associated with the set of ground truth labels.

20. A first device, comprising: means for receiving, from a second device, a request for labels for training or monitoring the machine learning model and labeling features corresponding to the labels; and means for generating a set of labels and a set of labeling features, wherein the set of labels includes at least a set of ground truth labels for output by the machine learning model based on a set of channel measurements for input into the machine learning model, and wherein the set of labeling features includes at least a set of quality indicators associated with the set of ground truth labels.80QC2500148WO

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