Artificial intelligence machine learning model processing capability inside or outside of measurement gap

Abstract

Aspects of the disclosure are directed to a user equipment (UE) capability reporting scheme for artificial intelligence machine learning (AIML) model processing inside of a measurement gap (MG) instance and / or outside of an MG instance. In some designs, knowledge of the UE capability to perform the AIML model processing may facilitate the UE and / or a network component to select a MG configuration and / or AIML model that is compatible with the UE AIML model processing capability. Such aspects may provide various technical advantages, such as improved (e.g., faster, more accurate, etc.) positioning, (e.g., faster, more accurate, etc.) sensing, improved (e.g., faster, higher performance, etc.) beam management, improved (e.g., faster, more accurate, etc.) channel state information reference signal (CSI-RS) measurements, and so on.

Description

Qualcomm Ref. No.2403295WO ARTIFICIAL INTELLIGENCE MACHINE LEARNING MODEL PROCESSING CAPABILITY INSIDE OR OUTSIDE OF MEASUREMENT GAP TECHNICAL 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)), radio frequency (RF) sensing, and other technical enhancements. These enhancements, as well as the use of higher frequency bands, advances in PRS processes and technology, and high-density deployments for 5G, enable highly accurate 5G-based sensing and 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 1 QC2403295WOQualcomm Ref. No.2403295WO 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 the 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 operating a user equipment (UE) includes transmitting at least one indication of at least one capability of the UE to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; receiving a MG configuration that is associated with processing of at least one AIML model and is based on the at least one capability; and processing the at least one AIML model in accordance with the MG configuration.

[0006] In an aspect, a method of operating a network component includes receiving at least one indication of at least one capability of a user equipment (UE) to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; and transmitting a MG configuration that is based on the at least one capability.

[0007] In an aspect, a user equipment (UE) 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: transmit, via the one or more transceivers, at least one indication of at least one capability of the UE to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination 2 QC2403295WOQualcomm Ref. No.2403295WO thereof; receive, via the one or more transceivers, a MG configuration that is associated with processing of at least one AIML model and is based on the at least one capability; and process the at least one AIML model in accordance with the MG configuration.

[0008] In an aspect, a network component 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, at least one indication of at least one capability of a user equipment (UE) to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; and transmit, via the one or more transceivers, a MG configuration that is based on the at least one capability.

[0009] In an aspect, a user equipment (UE) includes means for transmitting at least one indication of at least one capability of the UE to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; means for receiving a MG configuration that is associated with processing of at least one AIML model and is based on the at least one capability; and means for processing the at least one AIML model in accordance with the MG configuration.

[0010] In an aspect, a network component includes means for receiving at least one indication of at least one capability of a user equipment (UE) to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; and means for transmitting a MG configuration that is based on the at least one capability. 3 QC2403295WOQualcomm Ref. No.2403295WO

[0011] In an aspect, a non-transitory computer-readable medium storing computer-executable instructions that, when executed by a user equipment (UE), cause the UE to: transmit at least one indication of at least one capability of the UE to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; receive a MG configuration that is associated with processing of at least one AIML model and is based on the at least one capability; and process the at least one AIML model in accordance with the MG configuration.

[0012] In an aspect, a non-transitory computer-readable medium storing computer-executable instructions that, when executed by a network component, cause the network component to: receive at least one indication of at least one capability of a user equipment (UE) to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; and transmit a MG configuration that is based on the at least one capability.

[0013] Other objects 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

[0014] 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.

[0015] FIG. 1 illustrates an example wireless communications system, according to aspects of the disclosure.

[0016] FIGS.2A, 2B, and 2C illustrate example wireless network structures, according to aspects of the disclosure. 4 QC2403295WOQualcomm Ref. No.2403295WO

[0017] 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.

[0018] FIG. 4 is a diagram illustrating an example frame structure, according to aspects of the disclosure.

[0019] FIG. 5 is a diagram illustrating an example downlink positioning reference signal (DL- PRS) configuration for two transmission-reception points (TRPs) operating in the same positioning frequency layer, according to aspects of the disclosure.

[0020] FIGS. 6A and 6B are diagrams of example sidelink slot structures with and without feedback resources, according to aspects of the disclosure.

[0021] FIGS.7A and 7B illustrate different types of wireless sensing, according to aspects of the disclosure.

[0022] FIGS. 8A to 8F illustrate various example monostatic and bistatic sensing use cases, according to aspects of the disclosure.

[0023] FIG.9 illustrates an example neural network, according to aspects of the disclosure.

[0024] FIG. 10A illustrates a direct artificial intelligence machine learning (AIML) use case 1000A, in accordance with aspects of the disclosure.

[0025] FIG. 10B illustrates an assisted AIML use case, in accordance with aspects of the disclosure.

[0026] FIG.10C illustrates an AIML positioning or sensing use case, in accordance with aspects of the disclosure.

[0027] FIG.10D illustrates an AIML positioning or sensing use case, in accordance with aspects of the disclosure.

[0028] FIG.10E illustrates an AIML positioning or sensing use case, in accordance with aspects of the disclosure.

[0029] FIG.10F illustrates an AIML positioning or sensing use case, in accordance with aspects of the disclosure.

[0030] FIG.10G illustrates an AIML positioning or sensing use case, in accordance with aspects of the disclosure.

[0031] FIG.11 illustrates an exemplary process of communications according to an aspect of the disclosure. 5 QC2403295WOQualcomm Ref. No.2403295WO

[0032] FIG.12 illustrates an exemplary process of communications according to an aspect of the disclosure.

[0033] FIG. 13 illustrates an example implementation of the processes of FIGS. 11-12, respectively, in accordance with aspects of the disclosure. DETAILED DESCRIPTION

[0034] 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.

[0035] Various aspects relate generally to artificial intelligence machine learning (AIML) model processing capability of a user equipment (UE) inside or outside of measurement gap (MG). In some designs, MG lengths are designed primarily for classical approaches (i.e., approaches that do not rely upon AIML models). However, these MG lengths may not be suitable for AIML model-based use cases. This is further complicated for use cases where the network configures the UE to perform both types of measurements (i.e., classical or non-AIML model technique along with AIML model-based measurements), which may require extra processing capability from the user equipment (UE).

[0036] Particular aspects of the subject matter described in this disclosure can be implemented to realize one or more of the following potential advantages. Aspects of the disclosure are directed to a user equipment (UE) capability reporting scheme for artificial intelligence machine learning (AIML) model processing inside of a measurement gap (MG) instance and / or outside of an MG instance. In some designs, knowledge of the UE capability to perform the AIML model processing may facilitate the UE and / or a network component to select a MG configuration and / or AIML model that is compatible with the UE AIML model processing capability. Such aspects may provide various technical advantages, such as improved (e.g., faster, more accurate, etc.) positioning, (e.g., faster, more accurate, etc.) sensing, improved (e.g., faster, higher performance, etc.) beam management, improved (e.g., faster, more accurate, etc.) channel state information reference signal (CSI-RS) measurements, and so on. 6 QC2403295WOQualcomm Ref. No.2403295WO

[0037] 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 other 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.

[0038] 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.

[0039] 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.

[0040] 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 (IoT) device, etc.) used by a user to communicate over a wireless communications network. A UE may 7 QC2403295WOQualcomm Ref. No.2403295WO 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 “subscriber 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.

[0041] 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.

[0042] 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) 8 QC2403295WOQualcomm Ref. No.2403295WO 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 antennas 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.

[0043] 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).

[0044] 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.

[0045] 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, 9 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0046] 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.

[0047] 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.

[0048] 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 10 QC2403295WOQualcomm Ref. No.2403295WO 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), 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 IoT (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.

[0049] 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).

[0050] 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). 11 QC2403295WOQualcomm Ref. No.2403295WO

[0051] 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). When 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.

[0052] 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®.

[0053] 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.

[0054] 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 12 QC2403295WOQualcomm Ref. No.2403295WO 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 that 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.

[0055] 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-location (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.

[0056] 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 13 QC2403295WOQualcomm Ref. No.2403295WO 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 direction 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.

[0057] 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.

[0058] 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.

[0059] 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) 14 QC2403295WOQualcomm Ref. No.2403295WO band (30 GHz – 300 GHz) which is identified by the INTERNATIONAL TELECOMMUNICATION UNION® as a “millimeter wave” band.

[0060] The frequencies between FR1 and FR2 are often referred to as mid-band frequencies. Recent 5G NR studies have identified an operating band for these mid-band frequencies as frequency range designation FR3 (7.125 GHz – 24.25 GHz). Frequency bands falling within FR3 may inherit FR1 characteristics and / or FR2 characteristics, and thus may effectively extend features of FR1 and / or FR2 into 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.

[0061] 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.

[0062] 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 15 QC2403295WOQualcomm Ref. No.2403295WO 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 network 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.

[0063] 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.

[0064] 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.

[0065] 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 a base 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) 16 QC2403295WOQualcomm Ref. No.2403295WO 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 geographic 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.

[0066] 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 802.11x 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.

[0067] 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 17 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0068] 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 SVs 112 may be part of a satellite positioning system that a UE 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.

[0069] 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 Multi- functional 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.

[0070] In an aspect, SVs 112 may additionally or alternatively be part of one or more non- terrestrial 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 18 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0071] 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.

[0072] 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.

[0073] 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 19 QC2403295WOQualcomm Ref. No.2403295WO 20 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.

[0074] 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.

[0075] 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), 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 IoT (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” 20 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0076] 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).

[0077] 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).

[0078] 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). When 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.

[0079] 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', 21 QC2403295WOQualcomm Ref. No.2403295WO 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®.

[0080] 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.

[0081] 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 that 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 22 QC2403295WOQualcomm Ref. No.2403295WO 23 radio waves from the separate antennas add together to increase the radiation in a desired direction, while cancelling to suppress radiation in undesired directions.

[0082] 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-location (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.

[0083] 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 direction 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.

[0084] 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 23 QC2403295WOQualcomm Ref. No.2403295WO 24 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.

[0085] 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.

[0086] 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.

[0087] The frequencies between FR1 and FR2 are often referred to as mid-band frequencies. Recent 5G NR studies have identified an operating band for these mid-band frequencies as frequency range designation FR3 (7.125 GHz – 24.25 GHz). Frequency bands falling within FR3 may inherit FR1 characteristics and / or FR2 characteristics, and thus may effectively extend features of FR1 and / or FR2 into 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. 24 QC2403295WOQualcomm Ref. No.2403295WO

[0088] 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.

[0089] 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 network 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.

[0090] 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 25 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0091] 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.

[0092] 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 a base 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 geographic 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. 26 QC2403295WOQualcomm Ref. No.2403295WO 27

[0093] 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 802.11x 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.

[0094] 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.

[0095] 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 SVs 112 may be part of a satellite positioning system that a UE 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. 27 QC2403295WOQualcomm Ref. No.2403295WO 28 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.

[0096] 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 Multi- functional 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.

[0097] In an aspect, SVs 112 may additionally or alternatively be part of one or more non- terrestrial 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.

[0098] 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 28 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0099] 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).

[0100] 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 core 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).

[0101] 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 29 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0102] 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 of 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 30 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0103] 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 N11 interface.

[0104] 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).

[0105] 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 information (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. 31 QC2403295WOQualcomm Ref. No.2403295WO

[0106] 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.

[0107] 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 “F1” 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 communicates 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.

[0108] 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, 32 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0109] 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).

[0110] 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 (O-RAN (such as the network configuration sponsored by the O-RAN ALLIANCE®)), or a virtualized radio access network (vRAN, also known as a cloud radio access network (C- RAN)). Disaggregation may include distributing functionality across two or more units at various physical locations, as well as distributing functionality for at least one unit virtually, which can enable flexibility in network design. The various units of the disaggregated base station, or disaggregated RAN architecture, can be configured for wired or wireless communication with at least one other unit.

[0111] 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 33 QC2403295WOQualcomm Ref. No.2403295WO or more DUs 285 (e.g., gNB-DUs 228) via respective midhaul links, such as an F1 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.

[0112] 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.

[0113] 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 into one or more CU-UP units and one or more CU-CP units. The CU-UP unit can communicate bidirectionally with the CU-CP unit via an interface, such as the E1 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.

[0114] 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 34 QC2403295WOQualcomm Ref. No.2403295WO (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.

[0115] 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.

[0116] 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 O1 interface). For 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 O2 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 O1 interface. Additionally, in some implementations, the SMO Framework 255 35 QC2403295WOQualcomm Ref. No.2403295WO can communicate directly with one or more RUs 287 via an O1 interface. The SMO Framework 255 also may include a Non-RT RIC 257 configured to support functionality of the SMO Framework 255.

[0117] 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 A1 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.

[0118] 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 O1) or via creation of RAN management policies (such as A1 policies).

[0119] 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. 2A 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 36 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0120] 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 for tuning, 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 318 and 358, respectively, and one or more receivers 312 and 352, respectively, for receiving and decoding signals 318 and 358, respectively.

[0121] 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 37 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0122] 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.

[0123] 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 non- terrestrial network (NTN) receivers, the satellite positioning / communication signals 338 and 378 may be communication signals (e.g., carrying control and / or user data) 38 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0124] 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.

[0125] 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., means 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.

[0126] 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 39 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0127] 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 wired 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.

[0128] 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 40 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0129] 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 AIML component 348, 388, and 398, respectively. The AIML 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 AIML 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 processing system, etc.). Alternatively, the AIML 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 AIML 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 AIML 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 41 QC2403295WOQualcomm Ref. No.2403295WO may be a standalone component. FIG. 3C illustrates possible locations of the AIML 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.

[0130] 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.

[0131] 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.

[0132] 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 42 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0133] The transmitter 354 and the receiver 352 may implement Layer-1 (L1) 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 spatial 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.

[0134] 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 Layer-1 functionality associated with various signal processing functions. The 43 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0135] 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.

[0136] 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, 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.

[0137] 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 44 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0138] 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.

[0139] 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.

[0140] For convenience, the UE 302, the base station 304, and / or the network entity 306 are shown in FIGS.3A, 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-Fi 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. 45 QC2403295WOQualcomm Ref. No.2403295WO

[0141] 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.

[0142] The components of FIGS.3A, 3B, and 3C may be implemented in various ways. In some implementations, the components of FIGS. 3A, 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,” “by 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 AIML component 348, 388, and 398, etc.

[0143] 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 46 QC2403295WOQualcomm Ref. No.2403295WO 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).

[0144] Various frame structures may be used to support downlink and uplink transmissions between network nodes (e.g., base stations and UEs). FIG.4 is a diagram 400 illustrating an example frame structure, according to aspects of the disclosure. The frame structure may be a downlink or uplink frame structure. Other wireless communications technologies may have different frame structures and / or different channels.

[0145] LTE, and in some cases NR, utilizes orthogonal frequency-division multiplexing (OFDM) on the downlink and single-carrier frequency division multiplexing (SC-FDM) on the uplink. Unlike LTE, however, NR has an option to use OFDM on the uplink as well. OFDM and SC-FDM partition the system bandwidth into multiple (K) orthogonal subcarriers, which are also commonly referred to as tones, bins, etc. Each subcarrier may be modulated with data. In general, modulation symbols are sent in the frequency domain with OFDM and in the time domain with SC-FDM. The spacing between adjacent subcarriers may be fixed, and the total number of subcarriers (K) may be dependent on the system bandwidth. For example, the spacing of the subcarriers may be 15 kilohertz (kHz) and the minimum resource allocation (resource block) may be 12 subcarriers (or 180 kHz). Consequently, the nominal fast Fourier transform (FFT) size may be equal to 128, 256, 512, 1024, or 2048 for system bandwidth of 1.25, 2.5, 5, 10, or 20 megahertz (MHz), respectively. The system bandwidth may also be partitioned into subbands. For example, a subband may cover 1.08 MHz (i.e., 6 resource blocks), and there may be 1, 2, 4, 8, or 16 subbands for system bandwidth of 1.25, 2.5, 5, 10, or 20 MHz, respectively.

[0146] LTE supports a single numerology (subcarrier spacing (SCS), symbol length, etc.). In contrast, NR may support multiple numerologies (μ), for example, subcarrier spacings of 15 kHz (μ=0), 30 kHz (μ=1), 60 kHz (μ=2), 120 kHz (μ=3), and 240 kHz (μ=4) or greater may be available. In each subcarrier spacing, there are 14 symbols per slot. For 15 kHz SCS (μ=0), there is one slot per subframe, 10 slots per frame, the slot duration is 1 millisecond (ms), the symbol duration is 66.7 microseconds (μs), and the maximum nominal system bandwidth (in MHz) with a 4K FFT size is 50. For 30 kHz SCS (μ=1), there are two slots per subframe, 20 slots per frame, the slot duration is 0.5 ms, the symbol duration is 33.3 μs, and the maximum nominal system bandwidth (in MHz) with a 4K 47 QC2403295WOQualcomm Ref. No.2403295WO FFT size is 100. For 60 kHz SCS (μ=2), there are four slots per subframe, 40 slots per frame, the slot duration is 0.25 ms, the symbol duration is 16.7 μs, and the maximum nominal system bandwidth (in MHz) with a 4K FFT size is 200. For 120 kHz SCS (μ=3), there are eight slots per subframe, 80 slots per frame, the slot duration is 0.125 ms, the symbol duration is 8.33 μs, and the maximum nominal system bandwidth (in MHz) with a 4K FFT size is 400. For 240 kHz SCS (μ=4), there are 16 slots per subframe, 160 slots per frame, the slot duration is 0.0625 ms, the symbol duration is 4.17 μs, and the maximum nominal system bandwidth (in MHz) with a 4K FFT size is 800.

[0147] In the example of FIG. 4, a numerology of 15 kHz is used. Thus, in the time domain, a 10 ms frame is divided into 10 equally sized subframes of 1 ms each, and each subframe includes one time slot. In FIG. 4, time is represented horizontally (on the X axis) with time increasing from left to right, while frequency is represented vertically (on the Y axis) with frequency increasing (or decreasing) from bottom to top.

[0148] A resource grid may be used to represent time slots, each time slot including one or more time-concurrent resource blocks (RBs) (also referred to as physical RBs (PRBs)) in the frequency domain. The resource grid is further divided into multiple resource elements (REs). An RE may correspond to one symbol length in the time domain and one subcarrier in the frequency domain. In the numerology of FIG. 4, for a normal cyclic prefix, an RB may contain 12 consecutive subcarriers in the frequency domain and seven consecutive symbols in the time domain, for a total of 84 REs. For an extended cyclic prefix, an RB may contain 12 consecutive subcarriers in the frequency domain and six consecutive symbols in the time domain, for a total of 72 REs. The number of bits carried by each RE depends on the modulation scheme.

[0149] Some of the REs may carry reference (pilot) signals (RS). The reference signals may include positioning reference signals (PRS), tracking reference signals (TRS), phase tracking reference signals (PTRS), cell-specific reference signals (CRS), channel state information reference signals (CSI-RS), demodulation reference signals (DMRS), primary synchronization signals (PSS), secondary synchronization signals (SSS), synchronization signal blocks (SSBs), sounding reference signals (SRS), etc., depending on whether the illustrated frame structure is used for uplink or downlink communication. FIG.4 illustrates example locations of REs carrying a reference signal (labeled “R”). 48 QC2403295WOQualcomm Ref. No.2403295WO

[0150] A collection of resource elements (REs) that are used for transmission of PRS is referred to as a “PRS resource.” The collection of resource elements can span multiple PRBs in the frequency domain and ‘N’ (such as 1 or more) consecutive symbol(s) within a slot in the time domain. In a given OFDM symbol in the time domain, a PRS resource occupies consecutive PRBs in the frequency domain.

[0151] The transmission of a PRS resource within a given PRB has a particular comb size (also referred to as the “comb density”). A comb size ‘N’ represents the subcarrier spacing (or frequency / tone spacing) within each symbol of a PRS resource configuration. Specifically, for a comb size ‘N,’ PRS are transmitted in every Nth subcarrier of a symbol of a PRB. For example, for comb-4, for each symbol of the PRS resource configuration, REs corresponding to every fourth subcarrier (such as subcarriers 0, 4, 8) are used to transmit PRS of the PRS resource. Currently, comb sizes of comb-2, comb-4, comb-6, and comb-12 are supported for DL-PRS. FIG. 4 illustrates an example PRS resource configuration for comb-4 (which spans four symbols). That is, the locations of the shaded REs (labeled “R”) indicate a comb-4 PRS resource configuration.

[0152] Currently, a DL-PRS resource may span 2, 4, 6, or 12 consecutive symbols within a slot with a fully frequency-domain staggered pattern. A DL-PRS resource can be configured in any higher layer configured downlink or flexible (FL) symbol of a slot. There may be a constant energy per resource element (EPRE) for all REs of a given DL-PRS resource. The following are the frequency offsets from symbol to symbol for comb sizes 2, 4, 6, and 12 over 2, 4, 6, and 12 symbols. 2-symbol comb-2: {0, 1}; 4-symbol comb-2: {0, 1, 0, 1}; 6-symbol comb-2: {0, 1, 0, 1, 0, 1}; 12-symbol comb-2: {0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1}; 4-symbol comb-4: {0, 2, 1, 3} (as in the example of FIG. 4); 12-symbol comb-4: {0, 2, 1, 3, 0, 2, 1, 3, 0, 2, 1, 3}; 6-symbol comb-6: {0, 3, 1, 4, 2, 5}; 12-symbol comb-6: {0, 3, 1, 4, 2, 5, 0, 3, 1, 4, 2, 5}; and 12-symbol comb-12: {0, 6, 3, 9, 1, 7, 4, 10, 2, 8, 5, 11}.

[0153] A “PRS resource set” is a set of PRS resources used for the transmission of PRS signals, where each PRS resource has a PRS resource ID. In addition, the PRS resources in a PRS resource set are associated with the same TRP. A PRS resource set is identified by a PRS resource set ID and is associated with a particular TRP (identified by a TRP ID). In addition, the PRS resources in a PRS resource set have the same periodicity, a common muting pattern configuration, and the same repetition factor (such as “PRS- 49 QC2403295WOQualcomm Ref. No.2403295WO ResourceRepetitionFactor”) across slots. The periodicity is the time from the first repetition of the first PRS resource of a first PRS instance to the same first repetition of the same first PRS resource of the next PRS instance. The periodicity may have a length selected from 2^μ*{4, 5, 8, 10, 16, 20, 32, 40, 64, 80, 160, 320, 640, 1280, 2560, 5120, 10240} slots, with μ = 0, 1, 2, 3. The repetition factor may have a length selected from {1, 2, 4, 6, 8, 16, 32} slots.

[0154] A PRS resource ID in a PRS resource set is associated with a single beam (or beam ID) transmitted from a single TRP (where a TRP may transmit one or more beams). That is, each PRS resource of a PRS resource set may be transmitted on a different beam, and as such, a “PRS resource,” or simply “resource,” also can be referred to as a “beam.” Note that this does not have any implications on whether the TRPs and the beams on which PRS are transmitted are known to the UE.

[0155] A “PRS instance” or “PRS occasion” is one instance of a periodically repeated time window (such as a group of one or more consecutive slots) where PRS are expected to be transmitted. A PRS occasion also may be referred to as a “PRS positioning occasion,” a “PRS positioning instance, a “positioning occasion,” “a positioning instance,” a “positioning repetition,” or simply an “occasion,” an “instance,” or a “repetition.”

[0156] A “positioning frequency layer” (also referred to simply as a “frequency layer”) is a collection of one or more PRS resource sets across one or more TRPs that have the same values for certain parameters. Specifically, the collection of PRS resource sets has the same subcarrier spacing and cyclic prefix (CP) type (meaning all numerologies supported for the physical downlink shared channel (PDSCH) are also supported for PRS), the same Point A, the same value of the downlink PRS bandwidth, the same start PRB (and center frequency), and the same comb-size. The Point A parameter takes the value of the parameter “ARFCN-ValueNR” (where “ARFCN” stands for “absolute radio-frequency channel number”) and is an identifier / code that specifies a pair of physical radio channel used for transmission and reception. The downlink PRS bandwidth may have a granularity of four PRBs, with a minimum of 24 PRBs and a maximum of 272 PRBs. Currently, up to four frequency layers have been defined, and up to two PRS resource sets may be configured per TRP per frequency layer.

[0157] The concept of a frequency layer is somewhat like the concept of component carriers and bandwidth parts (BWPs), but different in that component carriers and BWPs are used by 50 QC2403295WOQualcomm Ref. No.2403295WO one base station (or a macro cell base station and a small cell base station) to transmit data channels, while frequency layers are used by several (usually three or more) base stations to transmit PRS. A UE may indicate the number of frequency layers it can support when it sends the network its positioning capabilities, such as during an LTE positioning protocol (LPP) session. For example, a UE may indicate whether it can support one or four positioning frequency layers.

[0158] Note that the terms “positioning reference signal” and “PRS” generally refer to specific reference signals that are used for positioning in NR and LTE systems. However, as used herein, the terms “positioning reference signal” and “PRS” may also refer to any type of reference signal that can be used for positioning, such as but not limited to, PRS as defined in LTE and NR, TRS, PTRS, CRS, CSI-RS, DMRS, PSS, SSS, SSB, SRS, UL-PRS, etc. In addition, the terms “positioning reference signal” and “PRS” may refer to downlink, uplink, or sidelink positioning reference signals, unless otherwise indicated by the context. If needed to further distinguish the type of PRS, a downlink positioning reference signal may be referred to as a “DL-PRS,” an uplink positioning reference signal (e.g., an SRS-for-positioning, PTRS) may be referred to as an “UL-PRS,” and a sidelink positioning reference signal may be referred to as an “SL-PRS.” In addition, for signals that may be transmitted in the downlink, uplink, and / or sidelink (e.g., DMRS), the signals may be prepended with “DL,” “UL,” or “SL” to distinguish the direction. For example, “UL-DMRS” is different from “DL-DMRS.”

[0159] In an aspect, the reference signal carried on the REs labeled “R” in FIG. 4 may be SRS. SRS transmitted by a UE may be used by a base station to obtain the channel state information (CSI) for the transmitting UE. CSI describes how an RF signal propagates from the UE to the base station and represents the combined effect of scattering, fading, and power decay with distance. The system uses the SRS for resource scheduling, link adaptation, massive MIMO, beam management, etc.

[0160] A collection of REs that are used for transmission of SRS is referred to as an “SRS resource,” and may be identified by the parameter “SRS-ResourceId.” The collection of resource elements can span multiple PRBs in the frequency domain and ‘N’ (e.g., one or more) consecutive symbol(s) within a slot in the time domain. In a given OFDM symbol, an SRS resource occupies one or more consecutive PRBs. An “SRS resource set” is a set 51 QC2403295WOQualcomm Ref. No.2403295WO of SRS resources used for the transmission of SRS signals, and is identified by an SRS resource set ID (“SRS-ResourceSetId”).

[0161] The transmission of SRS resources within a given PRB has a particular comb size (also referred to as the “comb density”). A comb size ‘N’ represents the subcarrier spacing (or frequency / tone spacing) within each symbol of an SRS resource configuration. Specifically, for a comb size ‘N,’ SRS are transmitted in every Nth subcarrier of a symbol of a PRB. For example, for comb-4, for each symbol of the SRS resource configuration, REs corresponding to every fourth subcarrier (such as subcarriers 0, 4, 8) are used to transmit SRS of the SRS resource. In the example of FIG.4, the illustrated SRS is comb- 4 over four symbols. That is, the locations of the shaded SRS REs indicate a comb-4 SRS resource configuration.

[0162] Currently, an SRS resource may span 1, 2, 4, 8, or 12 consecutive symbols within a slot with a comb size of comb-2, comb-4, or comb-8. The following are the frequency offsets from symbol to symbol for the SRS comb patterns that are currently supported.1-symbol comb-2: {0}; 2-symbol comb-2: {0, 1}; 2-symbol comb-4: {0, 2}; 4-symbol comb-2: {0, 1, 0, 1}; 4-symbol comb-4: {0, 2, 1, 3} (as in the example of FIG. 4); 8-symbol comb-4: {0, 2, 1, 3, 0, 2, 1, 3}; 12-symbol comb-4: {0, 2, 1, 3, 0, 2, 1, 3, 0, 2, 1, 3}; 4-symbol comb-8: {0, 4, 2, 6}; 8-symbol comb-8: {0, 4, 2, 6, 1, 5, 3, 7}; and 12-symbol comb-8: {0, 4, 2, 6, 1, 5, 3, 7, 0, 4, 2, 6}.

[0163] Generally, as noted above, a UE transmits SRS to enable the receiving base station (either the serving base station or a neighboring base station) to measure the channel quality (i.e., CSI) between the UE and the base station. However, SRS can also be specifically configured as uplink positioning reference signals for uplink-based positioning procedures, such as uplink time difference of arrival (UL-TDOA), round-trip-time (RTT), uplink angle-of-arrival (UL-AoA), etc. As used herein, the term “SRS” may refer to SRS configured for channel quality measurements or SRS configured for positioning purposes. The former may be referred to herein as “SRS-for-communication” and / or the latter may be referred to as “SRS for positioning” or “positioning SRS” when needed to distinguish the two types of SRS.

[0164] Several enhancements over the previous definition of SRS may be available for SRS for positioning (also referred to as “UL-PRS”), such as a new staggered pattern within an SRS resource (except for single-symbol / comb-2), a new comb type for SRS, new 52 QC2403295WOQualcomm Ref. No.2403295WO sequences for SRS, a higher number of SRS resource sets per component carrier, and a higher number of SRS resources per component carrier. In addition, the parameters “SpatialRelationInfo” and “PathLossReference” are to be configured based on a downlink reference signal or SSB from a neighboring TRP. Further still, one SRS resource may be transmitted outside the active bandwidth part (BWP), and one SRS resource may span across multiple component carriers. Also, SRS may be configured in RRC connected state and only transmitted within an active BWP. Further, there may be no frequency hopping, no repetition factor, a single antenna port, and new lengths for SRS (e.g., 8 and 12 symbols). There also may be open-loop power control and not closed-loop power control, and comb-8 (i.e., an SRS transmitted every eighth subcarrier in the same symbol) may be used. Lastly, the UE may transmit through the same transmit beam from multiple SRS resources for UL-AoA. These features may be configured through RRC higher layer signaling (and potentially triggered or activated through a MAC control element (MAC- CE) or downlink control information (DCI)).

[0165] FIG.5 is a diagram 500 illustrating an example PRS configuration for two TRPs (labeled “TRP1” and “TRP2”) operating in the same positioning frequency layer (labeled “Positioning Frequency Layer 1”), according to aspects of the disclosure. For a positioning session, a UE may be provided with assistance data indicating the illustrated PRS configuration. In the example of FIG.5, the first TRP (“TRP1”) is associated with (e.g., transmits) two PRS resource sets, labeled “PRS Resource Set 1” and “PRS Resource Set 2,” and the second TRP (“TRP2”) is associated with one PRS resource set, labeled “PRS Resource Set 3.” Each PRS resource set comprises at least two PRS resources. Specifically, the first PRS resource set (“PRS Resource Set 1”) includes PRS resources labeled “PRS Resource 1” and “PRS Resource 2,” the second PRS resource set (“PRS Resource Set 2”) includes PRS resources labeled “PRS Resource 3” and “PRS Resource 4,” and the third PRS resource set (“PRS Resource Set 3”) includes PRS resources labeled “PRS Resource 5” and “PRS Resource 6.”

[0166] When a UE is configured in the assistance data of a positioning method with a number of PRS resources beyond its capability, the UE assumes the PRS resources in the assistance data are sorted in a decreasing order of measurement priority. Currently, the 64 TRPs per frequency layer are sorted according to priority and the two PRS resource sets per TRP of the frequency layer are sorted according to priority. However, the four frequency 53 QC2403295WOQualcomm Ref. No.2403295WO layers may or may not be sorted according to priority, and the 64 PRS resources of the PRS resource set per TRP per frequency layer may or may not be sorted according to priority. The reference indicated by the assistance data parameter “nr-DL-PRS- ReferenceInfo” for each frequency layer has the highest priority, at least for DL-TDOA positioning procedures.

[0167] Sidelink communication takes place in transmission or reception resource pools. In the frequency domain, the minimum resource allocation unit is a sub-channel (e.g., a collection of consecutive PRBs in the frequency domain). In the time domain, resource allocation is in one slot intervals. However, some slots are not available for sidelink, and some slots contain feedback resources. In addition, sidelink resources can be (pre)configured to occupy fewer than the 14 symbols of a slot.

[0168] Sidelink resources are configured at the radio resource control (RRC) layer. The RRC configuration can be by pre-configuration (e.g., preloaded on the UE) or configuration (e.g., from a serving base station).

[0169] NR sidelinks support hybrid automatic repeat request (HARQ) retransmission. FIG. 6A is a diagram 600 of an example slot structure without feedback resources, according to aspects of the disclosure. In the example of FIG.6A, time is represented horizontally and frequency is represented vertically. In the time domain, the length of each block is one orthogonal frequency division multiplexing (OFDM) symbol, and the 14 symbols make up a slot. In the frequency domain, the height of each block is one sub-channel. Currently, the (pre)configured sub-channel size can be selected from the set of {10, 15, 20, 25, 50, 75, 100} physical resource blocks (PRBs).

[0170] For a sidelink slot, the first symbol is a repetition of the preceding symbol and is used for automatic gain control (AGC) setting. This is illustrated in FIG. 6A by the vertical and horizontal hashing. As shown in FIG. 6A, for sidelink, the physical sidelink control channel (PSCCH) and the physical sidelink shared channel (PSSCH) are transmitted in the same slot. Similar to the physical downlink control channel (PDCCH), the PSCCH carries control information about sidelink resource allocation and descriptions about sidelink data transmitted to the UE. Likewise, similar to the physical downlink shared channel (PDSCH), the PSSCH carries user data for the UE. In the example of FIG.6A, the PSCCH occupies half the bandwidth of the sub-channel and only three symbols. Finally, a gap symbol is present after the PSSCH. 54 QC2403295WOQualcomm Ref. No.2403295WO

[0171] FIG.6B is a diagram 650 of an example slot structure with feedback resources, according to aspects of the disclosure. In the example of FIG.6B, time is represented horizontally and frequency is represented vertically. In the time domain, the length of each block is one OFDM symbol, and the 14 symbols make up a slot. In the frequency domain, the height of each block is one sub-channel.

[0172] The slot structure illustrated in FIG. 6B is similar to the slot structure illustrated in FIG. 6A, except that the slot structure illustrated in FIG. 6B includes feedback resources. Specifically, two symbols at the end of the slot have been dedicated to the physical sidelink feedback channel (PSFCH). The first PSFCH symbol is a repetition of the second PSFCH symbol for AGC setting. In addition to the gap symbol after the PSSCH, there is a gap symbol after the two PSFCH symbols. Currently, resources for the PSFCH can be configured with a periodicity selected from the set of {0, 1, 2, 4} slots.

[0173] NR supports a number of cellular network-based positioning technologies, including downlink-based, uplink-based, and downlink-and-uplink-based positioning methods. Downlink-based positioning methods include observed time difference of arrival (OTDOA) in LTE, downlink time difference of arrival (DL-TDOA) in NR, and downlink angle-of-departure (DL-AoD) in NR. In an OTDOA or DL-TDOA positioning procedure, a UE measures the differences between the times of arrival (ToAs) of reference signals (e.g., positioning reference signals (PRS)) received from pairs of base stations, referred to as reference signal time difference (RSTD) or time difference of arrival (TDOA) measurements, and reports them to a positioning entity. More specifically, the UE receives the identifiers (IDs) of a reference base station (e.g., a serving base station) and multiple non-reference base stations in assistance data. The UE then measures the RSTD between the reference base station and each of the non-reference base stations. Based on the known locations of the involved base stations and the RSTD measurements, the positioning entity (e.g., the UE for UE-based positioning or a location server for UE- assisted positioning) can estimate the UE’s location.

[0174] For DL-AoD positioning, the positioning entity uses a measurement report from the UE of received signal strength measurements of multiple downlink transmit beams to determine the angle(s) between the UE and the transmitting base station(s). The positioning entity can then estimate the location of the UE based on the determined angle(s) and the known location(s) of the transmitting base station(s). 55 QC2403295WOQualcomm Ref. No.2403295WO

[0175] Uplink-based positioning methods include uplink time difference of arrival (UL-TDOA) and uplink angle-of-arrival (UL-AoA). UL-TDOA is similar to DL-TDOA, but is based on uplink reference signals (e.g., sounding reference signals (SRS)) transmitted by the UE to multiple base stations. Specifically, a UE transmits one or more uplink reference signals that are measured by a reference base station and a plurality of non-reference base stations. Each base station then reports the reception time (referred to as the relative time of arrival (RTOA)) of the reference signal(s) to a positioning entity (e.g., a location server) that knows the locations and relative timing of the involved base stations. Based on the reception-to-reception (Rx-Rx) time difference between the reported RTOA of the reference base station and the reported RTOA of each non-reference base station, the known locations of the base stations, and their known timing offsets, the positioning entity can estimate the location of the UE using TDOA.

[0176] For UL-AoA positioning, one or more base stations measure the received signal strength of one or more uplink reference signals (e.g., SRS) received from a UE on one or more uplink receive beams. The positioning entity uses the signal strength measurements and the angle(s) of the receive beam(s) to determine the angle(s) between the UE and the base station(s). Based on the determined angle(s) and the known location(s) of the base station(s), the positioning entity can then estimate the location of the UE.

[0177] Downlink-and-uplink-based positioning methods include enhanced cell-ID (E-CID) positioning and multi-round-trip-time (RTT) positioning (also referred to as “multi-cell RTT” and “multi-RTT”). In an RTT procedure, a first entity (e.g., a base station or a UE) transmits a first RTT-related signal (e.g., a PRS or SRS) to a second entity (e.g., a UE or base station), which transmits a second RTT-related signal (e.g., an SRS or PRS) back to the first entity. Each entity measures the time difference between the time of arrival (ToA) of the received RTT-related signal and the transmission time of the transmitted RTT-related signal. This time difference is referred to as a reception-to-transmission (Rx- Tx) time difference. The Rx-Tx time difference measurement may be made, or may be adjusted, to include only a time difference between nearest slot boundaries for the received and transmitted signals. Both entities may then send their Rx-Tx time difference measurement to a location server (e.g., an LMF 270), which calculates the round trip propagation time (i.e., RTT) between the two entities from the two Rx-Tx time difference measurements (e.g., as the sum of the two Rx-Tx time difference measurements). 56 QC2403295WOQualcomm Ref. No.2403295WO Alternatively, one entity may send its Rx-Tx time difference measurement to the other entity, which then calculates the RTT. The distance between the two entities can be determined from the RTT and the known signal speed (e.g., the speed of light). For multi- RTT positioning, a first entity (e.g., a UE or base station) performs an RTT positioning procedure with multiple second entities (e.g., multiple base stations or UEs) to enable the location of the first entity to be determined (e.g., using multilateration) based on distances to, and the known locations of, the second entities. RTT and multi-RTT methods can be combined with other positioning techniques, such as UL-AoA and DL-AoD, to improve location accuracy.

[0178] The E-CID positioning method is based on radio resource management (RRM) measurements. In E-CID, the UE reports the serving cell ID, the timing advance (TA), and the identifiers, estimated timing, and signal strength of detected neighbor base stations. The location of the UE is then estimated based on this information and the known locations of the base station(s).

[0179] To assist positioning operations, a location server (e.g., location server 230, LMF 270, SLP 272) may provide assistance data to the UE. For example, the assistance data may include identifiers of the base stations (or the cells / TRPs of the base stations) from which to measure reference signals, the reference signal configuration parameters (e.g., the number of consecutive slots including PRS, periodicity of the consecutive slots including PRS, muting sequence, frequency hopping sequence, reference signal identifier, reference signal bandwidth, etc.), and / or other parameters applicable to the particular positioning method. Alternatively, the assistance data may originate directly from the base stations themselves (e.g., in periodically broadcasted overhead messages, etc.). In some cases, the UE may be able to detect neighbor network nodes itself without the use of assistance data.

[0180] In the case of an OTDOA or DL-TDOA positioning procedure, the assistance data may further include an expected RSTD value and an associated uncertainty, or search window, around the expected RSTD. In some cases, the value range of the expected RSTD may be + / - 500 microseconds (μs). In some cases, when any of the resources used for the positioning measurement are in FR1, the value range for the uncertainty of the expected RSTD may be + / - 32 μs. In other cases, when all of the resources used for the positioning measurement(s) are in FR2, the value range for the uncertainty of the expected RSTD may be + / - 8 μs. 57 QC2403295WOQualcomm Ref. No.2403295WO

[0181] A location estimate may be referred to by other names, such as a position estimate, location, position, position fix, fix, or the like. A location estimate may be geodetic and comprise coordinates (e.g., latitude, longitude, and possibly altitude) or may be civic and comprise a street address, postal address, or some other verbal description of a location. A location estimate may further be defined relative to some other known location or defined in absolute terms (e.g., using latitude, longitude, and possibly altitude). A location estimate may include an expected error or uncertainty (e.g., by including an area or volume within which the location is expected to be included with some specified or default level of confidence).

[0182] Wireless communication signals (e.g., radio frequency (RF) signals configured to carry orthogonal frequency division multiplexing (OFDM) symbols in accordance with a wireless communications standard, such as LTE, NR, etc.) transmitted between a UE and a base station can be used for environment sensing (also referred to as “RF sensing” or “radar”). Using wireless communication signals for environment sensing can be regarded as consumer-level radar with advanced detection capabilities that enable, among other things, touchless / device-free interaction with a device / system. The wireless communication signals may be cellular communication signals, such as LTE or NR signals, WLAN signals, such as Wi-Fi signals, etc. As a particular example, the wireless communication signals may be an OFDM waveform as utilized in LTE and NR. High- frequency communication signals, such as millimeter wave (mmW) RF signals, are especially beneficial to use as sensing signals because the higher frequency provides, at least, more accurate range (distance) detection.

[0183] Possible use cases of RF sensing include health monitoring use cases, such as heartbeat detection, respiration rate monitoring, and the like, gesture recognition use cases, such as human activity recognition, keystroke detection, sign language recognition, and the like, contextual information acquisition use cases, such as location detection / tracking, direction finding, range estimation, and the like, and automotive sensing use cases, such as smart cruise control, collision avoidance, and the like.

[0184] There are different types of sensing, including monostatic sensing (also referred to as “active sensing”) and bistatic sensing (also referred to as “passive sensing”). FIGS. 7A and 7B illustrate these different types of sensing. Specifically, FIG.7A is a diagram 700 illustrating a monostatic sensing scenario and FIG. 7B is a diagram 730 illustrating a 58 QC2403295WOQualcomm Ref. No.2403295WO bistatic sensing scenario. In FIG. 7A, the transmitter (Tx) and receiver (Rx) are co- located in the same sensing device 704 (e.g., a UE). The sensing device 704 transmits one or more RF sensing signals 734 (e.g., uplink or sidelink positioning reference signals (PRS) where the sensing device 704 is a UE), and some of the RF sensing signals 734 reflect off a target object 706 (e.g., an unmanned aerial vehicle (UAV)). The sensing device 704 can measure various properties (e.g., times of arrival (ToAs), angles of arrival (AoAs), phase shift, etc.) of the reflections 736 of the RF sensing signals 734 to determine characteristics of the target object 706 (e.g., size, shape, speed, motion state, etc.).

[0185] In FIG. 7B, the transmitter (Tx) and receiver (Rx) are not co-located, that is, they are separate devices (e.g., a UE and a base station). Note that while FIG.7B illustrates using a downlink RF signal as the RF sensing signal 732, uplink RF signals or sidelink RF signals can also be used as RF sensing signals 732. In a downlink scenario, as shown, the transmitter device 702 is a base station (e.g., a gNB) and the receiver device 708 is a UE (e.g., a mobile phone, a V2X-capable vehicle, a roadside unit (RSU), etc.), whereas in an uplink scenario, the transmitter device 702 is a UE and the receiver device 708 is a base station. Where the transmitter device 702 is a base station and the receiver device 708 a UE, the sensing is referred to as UE-assisted sensing. In UE-assisted sensing, the position of receiver device 708 should be known by the network (e.g., by GPS or other UE positioning method).

[0186] Referring to FIG. 7B in greater detail, the transmitter device 702 transmits RF sensing signals 732 and 734 (e.g., positioning reference signals (PRS)) to the receiver device 708, but some of the RF sensing signals 734 reflect off a target object 706. The receiver device 708 (also referred to as the “sensing device”) can measure the times of arrival (ToAs) of the RF sensing signals 732 received directly from the transmitter device 702 and the ToAs of the reflections 736 of the RF sensing signals 734 reflected from the target object 706.

[0187] More specifically, as described above, a transmitter device (e.g., a base station) may transmit a single RF signal or multiple RF signals to a receiver device (e.g., a UE). 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. Each path may be associated with a cluster of one or more channel taps. Generally, the time at which the receiver detects the first cluster of channel taps is considered the ToA of the RF signal on the line-of-site (LOS) path (i.e., the shortest path between the 59 QC2403295WOQualcomm Ref. No.2403295WO transmitter and the receiver). Later clusters of channel taps are considered to have reflected off objects between the transmitter and the receiver and therefore to have followed non-LOS (NLOS) paths between the transmitter and the receiver.

[0188] Thus, referring back to FIG. 7B, the RF sensing signals 732 followed the LOS path between the transmitter device 702 and the receiver device 708, and the RF sensing signals 734 followed an NLOS path between the transmitter device 702 and the receiver device 708 due to reflecting off the target object 706. The transmitter device 702 may have transmitted multiple RF sensing signals 732, 734, some of which followed the LOS path and others of which followed the NLOS path. Alternatively, the transmitter device 702 may have transmitted a single RF sensing signal in a broad enough beam that a portion of the RF sensing signal followed the LOS path (RF sensing signal 732) and a portion of the RF sensing signal followed the NLOS path (RF sensing signal 734).

[0189] Based on the ToA of the LOS path, the ToA of the NLOS path, and the speed of light, the receiver device 708 can determine the distance to the target object(s). For example, the receiver device 708 can calculate the distance to the target object as the difference between the ToA of the LOS path and the ToA of the NLOS path multiplied by the speed of light. In addition, if the receiver device 708 is capable of receive beamforming, the receiver device 708 may be able to determine the general direction to a target object 706 as the direction (angle) of the receive beam on which the RF sensing signal following the NLOS path was received. That is, the receiver device 708 may determine the direction to the target object 706 as the AoA of the RF sensing signal, which is the angle of the receive beam used to receive the RF sensing signal. The receiver device 708 may then optionally report this information to the transmitter device 702, its serving base station, an application server associated with the core network, an external client, a third-party application, or some other sensing entity. Alternatively, the receiver device 708 may report the ToA measurements to the transmitter device 702, or other sensing entity (e.g., if the receiver device 708 does not have the processing capability to perform the calculations itself), and the transmitter device 702 may determine the distance and, optionally, the direction to the target object 706.

[0190] Note that if the RF sensing signals are uplink RF signals transmitted by a UE to a base station, the base station would perform object detection based on the uplink RF signals just like the UE does based on the downlink RF signals. 60 QC2403295WOQualcomm Ref. No.2403295WO

[0191] Like conventional radar, wireless communication-based sensing signals can be used to estimate the range (distance), velocity (Doppler), and angle (AoA) of a target object. However, the performance (e.g., resolution and maximum values of range, velocity, and angle) may depend on the design of the reference signal.

[0192] FIGS. 8A to 8F illustrate various example monostatic and bistatic sensing use cases, according to aspects of the disclosure. In FIG. 8A, a gNB1-to-gNB1 monostatic sensing use case 800 is depicted. In FIG.8B, a UE1-to-UE1 monostatic sensing use case 810 is depicted. In FIG.8C, a gNB1-to-gNB2 bistatic sensing use case 820 is depicted. In FIG. 8D, a gNB1-to-UE1 bistatic sensing use case 830 is depicted. In FIG.8E, a UE1-to-gNB1 bistatic sensing use case 840 is depicted. In FIG.8F, a UE1-to-UE2 bistatic sensing use case 850 is depicted.

[0193] 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.

[0194] 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).

[0195] 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. 61 QC2403295WOQualcomm Ref. No.2403295WO

[0196] 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.

[0197] 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.

[0198] FIG.9 illustrates an example neural network 900, according to aspects of the disclosure. The neural network 900 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 ‘h1,’ ‘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.

[0199] 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 Naïve 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. 62 QC2403295WOQualcomm Ref. No.2403295WO

[0200] 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.

[0201] 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, 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.

[0202] 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).

[0203] In some designs, a device (e.g., target UE, server UE, anchor UE, gNB, LMF, a sensing management function (SnMF), etc.) may utilize a “direct” AIML model. In this case, a direct (D)-AIML model is trained so as to accept input data (e.g., DL-PRS measurements, UL-PRS measurements, SL-PRS measurements, sensing measurements, beam measurements, CSI-RS measurements, etc.) that is processed to provide a final result (i.e., a direct label, such as a target location which may correspond to a UE location for positioning or a target object location for sensing). 63 QC2403295WOQualcomm Ref. No.2403295WO

[0204] In some designs, an assisted (or indirect) AIML model is utilized. In this case, an assisted (A)-AIML model is trained so as to accept input data (e.g., DL-PRS measurements, UL- PRS measurements, SL-PRS measurements, sensing measurements (e.g., measurements of sensing signal reflections off of a target object), beam measurements, CSI-RS measurements, etc.) that is processed to provide intermediate data as an output (i.e., or intermediate label, sometimes referred to in a positioning context as positioning feature extraction, such as timing / angle information, LOS identification, etc.), with the intermediate data in turn provided as an input to another AIML model. Note that the other position estimation model may be another AIML model (e.g., another A-AIML model or a D-AIML model) or a non-AI model (e.g., Chan’s algorithm, a Kalman Filter (KF) algorithm, etc.). Also the A-AIML model and the another model may be implemented at the same entity (e.g., UE, LMF, gNB, SnMF, etc.) or at different entities (e.g., for network-assisted positioning, UE applies the A-AIML model to compress the measurement data, which is then reported to the LMF, which then applies the other position estimation model; for UE-based positioning, network component such as gNB or LMF or another UE for sidelink applies the A-AIML model to compress the measurement data, which is then reported to the UE, which then applies the other position estimation model).

[0205] Note that, as used herein, an AIML model (e.g., A-AIML model or D-AIML model) may be alternatively referred to as an “ML model” or an “AI model” or an “ML-based model” or an “AI-based model,” and so on.

[0206] FIG. 10A illustrates a D-AIML use case 1000A, in accordance with aspects of the disclosure. In particular, the D-AIML use case 1000A is for either positioning or sensing. In FIG. 10A, A D-AIML model 1005A at a device (e.g., UE, gNB, LMF, SnMF, etc.) receives and processes positioning or sensing measurement(s) to produce final (or non- intermediate) result(s) (i.e., a positioning or sensing result).

[0207] FIG. 10B illustrates an A-AIML use case 1000B, in accordance with aspects of the disclosure. In particular, the A-AIML use case 1000B is for either positioning or sensing. In FIG. 10B, an A-AIML model 1005B at a device (e.g., UE, gNB, LMF, SnMF, etc.) receives and processes positioning or sensing measurement(s) to produce intermediate positioning or sensing measurement(s) (e.g., features, etc.). Another model 1010B (e.g., a D-AIML model or a non-AIML model) at the same device or a different device (e.g., 64 QC2403295WOQualcomm Ref. No.2403295WO UE, gNB, LMF, SnMF, etc.) receives and processes the intermediate positioning or sensing measurement(s) to produce final (or non-intermediate) result(s) (i.e., a positioning or sensing result). Note that in other designs, the intermediate positioning or sensing result(s) output by the A-AIML model 1005B may one or more intervening A-AIML models (or non-AIML models) before the positioning or sensing result(s) are output by the model 1010B.

[0208] FIG.10C illustrates an AIML positioning or sensing use case 1000C, in accordance with aspects of the disclosure. The AIML positioning or sensing use case 1000C may be characterized as Case 1, and includes UE-based positioning or sensing with UE-side D- AIML model (e.g., an A-AIML or D-AIML).

[0209] FIG. 10D illustrates AIML positioning or sensing use case 1000D, in accordance with aspects of the disclosure. The AIML positioning or sensing use case 1000D may be characterized as Case 2a, and includes UE-assisted, LMF-based positioning or SnMF- based sensing with UE-side A-AIML model.

[0210] FIG. 10E illustrates AIML positioning or sensing use case 1000E, in accordance with aspects of the disclosure. The AIML positioning or sensing use case 1000E may be characterized as Case 2b, and includes UE-assisted, LMF-based positioning or SnMF- based sensing with LMF / SnMF-side D-AIML model.

[0211] FIG. 10F illustrates AIML positioning or sensing use case 1000F, in accordance with aspects of the disclosure. The AIML positioning or sensing use case 1000F may be characterized as Case 3a, and includes wireless node (e.g., gNB or a server UE) assisted positioning or sensing with wireless node-side A-AIML model.

[0212] FIG. 10G illustrates AIML positioning or sensing use case 1000G, in accordance with aspects of the disclosure. The AIML positioning or sensing use case 1000G may be characterized as Case 3b, and includes wireless node (e.g., gNB or server UE) assisted positioning or sensing with LMF / SnMF-side D-AIML model.

[0213] It is noted that FIGS.10A-10G depict example AIML model use cases, and other AIML model use cases are also possible. Also, while the sensing use cases in FIGS. 10C-10G involve sensing signals transmitted by one device and measured at another device (i.e., bistatic sensing), other sensing use cases to which AIML models may be utilized include monostatic sensing (i.e., sensing signals transmitted and measured by same device). 65 QC2403295WOQualcomm Ref. No.2403295WO

[0214] It is further noted that AIML models may execute in a training mode or an inferencing mode. In training mode, AIML models are provided with pre-validated input data along with pre-validated output data to derive or modify weights (i.e., to increase a reliability of the AIML models 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 inferencing mode, AIML models utilize 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 models return to the training mode). The (unvalidated) output data may be characterized as an “inference”. With this in mind, the “final” positioning or sensing result described above with respect to FIGS.10A-10G 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.

[0215] In some designs, for inter-frequency, intra-RAT measurements (if measurements are done outside the active BWP), and inter-RAT measurements, measurements gaps may be utilized. In some designs, the need for MG depends on the UE capability, the active BWP of the UE, and the operating frequency. In some designs, a MG configuration has the following elements, e.g.: MG Repetition Period: Specifies the gap period. Values include 20, 40, 80, 160 ms. For example, for 40 ms the gap repeats every four frames. Gap Offset: Specifies the starting subframe when the gap starts. Being relative to period, its range is 0 to mgrp-1. MG Length (MGL): Specifies the duration of the gap in milliseconds. Values include 1.5, 3, 3.5, 4, 5.5, and 6 ms. For positioning measurements, 10 and 20 ms are applicable. MG Timing Advance (TA): UE starts measurements in advance of the subframe when the gap starts. This could be 0, 0.25 or 0.5ms. For FR2, 0 and 0.25 ms are applicable. Reference Serving Cell Indicator: Applicable for NR E-UTRA Dual Connectivity (NE-DC) and NR Dual Connectivity (NR-DC), this indicates which cell's System Number (SFN) and subframe numbering to use for gap calculation.

[0216] In some designs, MG lengths are designed primarily for classical approaches (i.e., approaches that do not rely upon AIML models). However, these MG lengths may not be 66 QC2403295WOQualcomm Ref. No.2403295WO suitable for AIML model-based use cases. This is further complicated for use cases where the network configures the UE to perform both types of measurements (i.e., classical or non-AIML model technique along with AIML model-based measurements), which may require extra processing capability from the UE.

[0217] Aspects of the disclosure are directed to a user equipment (UE) capability reporting scheme for artificial intelligence machine learning (AIML) model processing inside of a measurement gap (MG) instance and / or outside of an MG instance. In some designs, knowledge of the UE capability to perform the AIML model processing may facilitate the UE and / or a network component to select a MG configuration and / or AIML model that is compatible with the UE AIML model processing capability. Such aspects may provide various technical advantages, such as improved (e.g., faster, more accurate, etc.) positioning, (e.g., faster, more accurate, etc.) sensing, improved (e.g., faster, higher performance, etc.) beam management, improved (e.g., faster, more accurate, etc.) channel state information reference signal (CSI-RS) measurements, and so on.

[0218] FIG.11 illustrates an exemplary process 1100 of communications according to an aspect of the disclosure. The process 1100 of FIG.11 is performed by a UE, such as UE 302.

[0219] Referring to FIG.11, at 1110, the UE (e.g., transmitter 314 or 324, etc.) transmits at least one indication of at least one capability of the UE to perform artificial intelligence machine learning (AIML) model processing. In an aspect, the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance. In some designs, a means for performing the transmission of 1110 includes transmitter 314 or 324, etc., of FIG.3A.

[0220] Referring to FIG. 11, at 1120, the UE (e.g., receiver 312 or 322, etc.) receives a MG configuration that is associated with processing of at least one AIML model and is based on the at least one capability. In some designs, a means for performing the reception of 1120 includes receiver 312 or 322, etc., of FIG.3A.

[0221] Referring to FIG.11, at 1130, the UE (e.g., processor(s) 342, AIML component 348, etc.) processes the at least one AIML model in accordance with the MG configuration. In an aspect, the at least one AIML model may be an A-AIML model or a D-AIML model, and the processing may correspond to the training mode or the inferencing mode. Also, this 67 QC2403295WOQualcomm Ref. No.2403295WO processing may be performed either inside of MG instances or outside of MG instances (e.g., subject to the reported UE capability). In some designs, a means for performing the processing of 1130 includes processor(s) 342, AIML component 348, etc., of FIG.3A.

[0222] Referring to FIG. 11, in some designs, the processing of the at least one AIML model is associated with a position estimation session, or the processing of the at least one AIML model is associated with a sensing session, or the processing of the at least one AIML model is associated with channel state information (CSI) measurements, or the processing of the at least one AIML model is associated with beam management.

[0223] Referring to FIG. 11, in some designs, the processing of the at least one AIML model is associated with AIML model training, or the processing of the at least one AIML model is associated with AIML model inferencing.

[0224] Referring to FIG.11, in some designs, the at least one capability comprises, e.g.: a first maximum number of AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML models the UE is capable of processing outside of the MG instance, or a first maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing outside of the MG instance, or a first inference time per inference for a second AIML model inside of the MG instance, or a second inference time per inference for the second AIML model outside of the MG instance, or a first buffering limit inside of the MG instance, or a second buffering limit outside of the MG instance, or a first number of inference processing units for a third AIML model inside of the MG instance, or a second number of inference processing units for the third AIML model outside of the MG instance, or 68 QC2403295WOQualcomm Ref. No.2403295WO any combination thereof.

[0225] Referring to FIG. 11, in some designs, the processing of the at least one AIML model is performed inside of one or more MG instances configured by the MG configuration. In an aspect, the UE further transmits AIML model processing time information associated with a set of AIML models to a network component, and the one or more MG instances are configured with a MG instance length (which may alternatively be characterized as a MG instance duration) that is based on the AIML model processing time information. In an aspect, the UE further transmits a request associated with a MG instance length to a network component, and the one or more MG instances are configured with the MG instance length in response to the request. In an aspect, the request comprises an explicit reference to the MG instance length, or the request comprises a range of MG instance lengths, or the request comprises a minimum MG instance length, or the request comprises a maximum MG instance length.

[0226] Referring to FIG. 11, in some designs, the processing of the at least one AIML model is performed outside of one or more MG instances configured by the MG configuration.

[0227] Referring to FIG.11, in some designs, the UE further receives AIML model information associated with a set of AIML models. In an aspect, the AIML model information comprises, e.g.: a first indication that a first AIML model is permitted for processing inside of MG instances only, or a second indication that a second AIML model is not permitted for processing outside of MG instances only, or a third indication that a third AIML model is permitted for processing both inside of MG instances and outside of MGs, or a fourth indication that a fourth AIML model is permitted for processing inside of MG instances only if a MG instance length associated with the MG configuration exceeds a MG instance length threshold, or any combination thereof.

[0228] Referring to FIG. 11, in some designs, the UE further receives a set of processing configurations for a given AIML model, and selects a processing configuration from the set of processing configurations. In an aspect, the processing processes the given AIML model inside or outside of one or more MG instances configured by the MG configuration 69 QC2403295WOQualcomm Ref. No.2403295WO in accordance with the selected processing configuration. In an aspect, the set of processing configurations are associated with different processing times or power consumptions or accuracies or any combination thereof, or the set of processing configurations comprises a first subset of processing configurations for processing of the given AIML model inside of the one or more MG instances, or the set of processing configurations comprises a second subset of processing configurations for processing of the given AIML model outside of the one or more MG instances, or any combination thereof. In an aspect, the selecting is based on priority information associated with the given AIML model.

[0229] Referring to FIG.11, in some designs, the MG configuration configures one or more MG instances for processing of a given AIML model associated with a functionality or output. In an aspect, a MG instance length is based on a set of criteria comprising, e.g.: whether a non-AIML model associated with the same functionality or output is concurrently processed with the given AIML model during the one or more MG instances, or whether at least one additional AIML model is concurrently processed with the given AIML model during the one or more MG instances, or AIML model processing time information associated with the given AIML model, or any combination thereof.

[0230] Referring to FIG.11, in some designs, the UE further performs one or more transmission operations during the one or more MG instances. In some designs, the UE further receives another MG configuration that configures one or more other MG instances inside of which no AIML models are processed. In an aspect, the MG configuration and the another MG configuration are triggered or configured via different signaling types, or the MG configuration is configured based on a first set of candidate MG instance lengths or MG periodicities and the another MG configuration is configured based on a second set of candidate MG instance lengths or MG periodicities, or an explicit association between the MG configuration the given AIML model or the functionality of the given AIML model or the output of the given AIML model is defined.

[0231] FIG.12 illustrates an exemplary process 1200 of communications according to an aspect of the disclosure. The process 1200 of FIG.12 is performed by a network component. In some designs, the network component may correspond to a wireless network component 70 QC2403295WOQualcomm Ref. No.2403295WO (e.g., gNB / BS 304 or O-RAN component such as RU) or a network server (e.g., network entity 306, LMF, SnMF, etc.). In other designs, the network component may correspond to another UE (e.g., sidelink anchor UE or sidelink server UE).

[0232] Referring to FIG. 12, at 1210, the network component (e.g., receiver 312 or 322 or 352 or 362, network transceiver(s) 380 or 390, etc.) receives at least one indication of at least one capability of a user equipment (UE) to perform artificial intelligence machine learning (AIML) model processing. In an aspect, the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof. In some designs, a means for performing the reception of 1210 includes receiver 312 or 322 or 352 or 362, network transceiver(s) 380 or 390, etc., of FIGS.3A-3C.

[0233] Referring to FIG.12, at 1220, the network component (e.g., transmitter 314 or 324 or 354 or 364, network transceiver(s) 380 or 390, etc.) transmits a MG configuration that is based on the at least one capability. In some designs, a means for performing the transmission of 1220 includes transmitter 314 or 324 or 354 or 364, network transceiver(s) 380 or 390, etc., of FIGS.3A-3C.

[0234] Referring to FIG. 12, in some designs, the network component receives AIML model processing time information associated with a set of AIML models from the UE. In an aspect, the network component configures one or more MG instances of the MG configuration with a MG instance length that is based on the AIML model processing time information. In an aspect, the network component further transmits associated with a MG instance length to a wireless network component. In an aspect, the request comprises an explicit reference to the MG instance length, or the request comprises a range of MG instance lengths, or the request comprises a minimum MG instance length, or the request comprises a maximum MG instance length. In an aspect, the network component further determines AIML model processing time uncertainty information based on the AIML model processing time information and the at least one capability, and transmits the AIML model processing time uncertainty information to a wireless network component.

[0235] Referring to FIG. 12, in some designs, the AIML model processing is associated with a position estimation session, or the AIML model processing is associated with a sensing 71 QC2403295WOQualcomm Ref. No.2403295WO session, or the AIML model processing is associated with channel state information (CSI) measurements, or the AIML model processing is associated with beam management.

[0236] Referring to FIG. 12, in some designs, the AIML model processing is associated with AIML model training, or the AIML model processing is associated with AIML model inferencing.

[0237] Referring to FIG.12, in some designs, the at least one capability comprises, e.g.: a first maximum number of AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML models the UE is capable of processing outside of the MG instance, or a first maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing outside of the MG instance, or a first inference time per inference for a second AIML model inside of the MG instance, or a second inference time per inference for the second AIML model outside of the MG instance, or a first buffering limit inside of the MG instance, or a second buffering limit outside of the MG instance, or a first number of inference processing units for a third AIML model inside of the MG instance, or a second number of inference processing units for the third AIML model outside of the MG instance, or any combination thereof.

[0238] Referring to FIG. 12, in some designs, the at least one capability comprises the first capability. In some designs, the at least one capability comprises the second capability.

[0239] Referring to FIGS. 11-12, in a specific example, UE capabilities to support AIML processing with and without MG may be reported. In a specific example, AIML model processing time may be reported. In an aspect, LMF may provide MG length suggestion 72 QC2403295WOQualcomm Ref. No.2403295WO for the AIML model ID. In an aspect, LMF / gNB may provide the minimum model processing time (e.g., may be direct or indirect function of the UE capabilities). In an aspect, a larger MG may be utilized for AIML model processing (e.g., in case AIML model and classical model run inside the same MG to derive the same output type, or in case multiple AIML models run inside the same MG, or in case the AIML model is in training mode, etc.).

[0240] Referring to FIGS. 11-12, in a specific example, the reported UE capabilit(ies) include UE capabilities to do AIML model processing with and without MGs, UE capabilities to perform multiple AIML model processing inside the same MG instance, a maximum number of the AIML models that can be processed inside the same MG, and / or different processing capabilities associated with processing of AIML models (e.g. inference time, inference processing units, number of inferences, buffering) when the UE is performing such processing within a MG or outside a MG, e.g.: Smaller number of inferences if the AIML model is processed outside a MG, and / or Longer inference time if the AIML model is processed outside a MG, and / or Smaller buffering limit if the AIML model is processed outside a MG (per inference or across inferences) , and / or Higher number of inference processing units if the AIML model is processed outside a MG, and / or When processing outside an MG, the maximum number of inference processing units is smaller compared to the maximum number when processing within a MG.

[0241] Referring to FIGS. 11-12, in a specific example, AIML model processing time reported by the UE to the LMF / gNB / network entity (e.g., UE is capable of processing AIML model 1 in processing time P1, UE is capable of processing AIML model 2 in processing time P2, etc.). In an aspect, if reported to the gNB, the gNB is expected to configured an MG instance according to the requested processing time. In another aspect, if reported to the LMF (or SnMF), then, then LMF (or SnMF) sends a request to the gNB to configure an MG instance according to the requested processing time.

[0242] Referring to FIGS.11-12, in a specific example, the UE requests a specific MG instance length given the processing time it requires to finish a AIML processing within a MG. 73 QC2403295WOQualcomm Ref. No.2403295WO

[0243] Referring to FIGS. 11-12, in a specific example, LMF can also provide to the serving gNB the expected model processing with some uncertainty by using report UE capabilities of positioning PRS resource.

[0244] Referring to FIGS. 11-12, in a specific example, the AIML model processing time may be defined in various ways, including, e.g.: constant clock, number of OFDM symbols / slots, total number of multiply-accumulate operations MACs (complex multiplication and additions, e.g., “a * b + c”), etc.

[0245] FIG.13 illustrates an example implementation 1300 of the processes 1100-1200 of FIGS. 11-12, respectively, in accordance with aspects of the disclosure. In FIG.13, the network component corresponds to a gNB.

[0246] Referring to FIG. 13, at 1310, the UE is configured with AIML model IDs 1, 2 and 3. AIML model 1 is associated with a 3 ms MG requirement (i.e., UE needs MG length of 3 ms to guarantee AIML model 1 can be processed during the MG), AIML model 2 is associated with a 6 ms MG requirement (i.e., UE needs MG length of 6 ms to guarantee AIML model 2 can be processed during the MG), and AIML model 3 is associated with a 10 ms MG requirement (i.e., UE needs MG length of 10 ms to guarantee AIML model 3 can be processed during the MG). At 1320, the UE transmits a request for an MG with MG length of 10 ms. At 1330, the gNB transmits a MG configuration that configures MG instances with a MG length of 6 ms. Since the UE is unable to obtain its desired MG length of 10 ms, the UE is unable to select AIML model 3 due to its 10 ms MG requirement, and the UE may instead select between UE model 1 or 3. In this case, at 1340, the UE selects model ID 2 because model ID 2 is associated with higher accuracy than UE model 1 (e.g., model IDs with higher MG length requirements may generally be associated with more accuracy). At 1350, the UE reports measurement data (e.g., positioning measurements and / or positioning result, sensing measurements and / or sensing result, etc.) that is based on processing via the selected model ID 2 to the gNB.

[0247] Referring to FIGS.11-12, in a specific example, new signaling between the LMF and UE, or UE to the gNB may be defined to provide information related to which model ID(s) may be utilized by the UE during MGs, e.g.: Model 1 can be used without MG, and / or Model 2 cannot be used without MG, and / or. Mandatory vs optional MG information 74 QC2403295WOQualcomm Ref. No.2403295WO

[0248] Referring to FIGS. 11-12, in a specific example, LMF may provide expected measurement gap length in case the MG is needed to process the AIML model ID, e.g.: Model 1 can used with MG length greater than 3 msec, and / or Model 2 can used with MG length greater than 10 msec.

[0249] Referring to FIGS. 11-12, in a specific example, LMF may provide multiple processing model IDs for the same configuration, model request, and / or functionality of model output. For example, for RSTD measurement, LMF can configure the 3 model ID, or the UE may report to a network entity, e.g.: Model ID1, Processing Time N1, and / or Power P1 and / or Accuracy A1 Model ID2, Processing Time N2, and / or Power P2 and / or Accuracy A3 Model ID3, Processing Time N3, and / or Power P3 and / or Accuracy A4, whereby N1>N2>N3 , P1>P2>P3 and A1>A2>A3

[0250] Referring to FIGS. 11-12, in a specific example, considerations such as higher accuracy vs. low power may factor into the model ID selection. For example, a high processing UE may perform a positioning session with model ID1, whereas a low processing UE may perform a positioning session based on the model ID3. As noted above, some AIML models may be utilized inside MGs while other AIML models may be utilized outside of MGs.

[0251] Referring to FIGS.11-12, in a specific example, the selection of AIML model ID, in case multiple AIML model ID for same configuration / requirement, may be left up to UE implementation. In another example, the selection of AIML model ID, in case multiple AIML model ID for same configuration / requirement, may be based on a priority order of the respective AIML model IDs under consideration.

[0252] Referring to FIGS. 11-12, in a specific example, larger MG lengths may be utilized for certain scenarios, including, e.g.: AIML model and classical model run inside the same MG instance, and / or Multiple AIML models run inside the same MG instance, and / or AIML model is associated with a very high processing time.

[0253] Referring to FIGS. 11-12, in a specific example, MGs for AIML model processing may be defined in various ways, some of which may be different than legacy MGs for non- AIML model purposes. Such differences may include any combination of the following, e.g.: 75 QC2403295WOQualcomm Ref. No.2403295WO A UE may be able to transmit reference signals / channels within the new AIML gap (note that this is not permitted in legacy MGs), and / or A UE may be triggered / configured / activated with one or more of the AIML-specific gaps with new dedicated signaling that is separate from the signaling used for MG, and / or New lengths, periodicities that are different from the legacy MGs may be introduced for the AIML-specific gaps, and / or Each AIML-specific gap may be explicitly associated with one or more models, or one or more AIML-functionalities (e.g., positioning, sensing, CSI, beam management).

[0254] Note that some specific examples for FIGS.11-12 are provided above with respect to the LMF for positioning use cases. Such aspects may also be applicable to non-positioning use cases such as sensing where the SnMF is utilized instead of the LMF, and so on.

[0255] 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 an 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.

[0256] Implementation examples are described in the following numbered clauses: 76 QC2403295WOQualcomm Ref. No.2403295WO

[0257] Clause 1. A method of operating a user equipment (UE), comprising: transmitting at least one indication of at least one capability of the UE to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; receiving a MG configuration that is associated with processing of at least one AIML model and is based on the at least one capability; and processing the at least one AIML model in accordance with the MG configuration.

[0258] Clause 2. The method of clause 1, wherein the processing of the at least one AIML model is associated with a position estimation session, or wherein the processing of the at least one AIML model is associated with a sensing session, or wherein the processing of the at least one AIML model is associated with channel state information (CSI) measurements, or wherein the processing of the at least one AIML model is associated with beam management.

[0259] Clause 3. The method of any of clauses 1 to 2, wherein the processing of the at least one AIML model is associated with AIML model training, or wherein the processing of the at least one AIML model is associated with AIML model inferencing.

[0260] Clause 4. The method of any of clauses 1 to 3, wherein the at least one capability comprises: a first maximum number of AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML models the UE is capable of processing outside of the MG instance, or a first maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing outside of the MG instance, or a first inference time per inference for a second AIML model inside of the MG instance, or a second inference time per inference for the second AIML model outside of the MG instance, or a first buffering limit inside of the MG instance, or a second buffering limit outside of the MG instance, or a first number of inference processing units for a third AIML model inside of the MG instance, or a second number of inference processing units for the third AIML model outside of the MG instance, or any combination thereof. 77 QC2403295WOQualcomm Ref. No.2403295WO

[0261] Clause 5. The method of any of clauses 1 to 4, wherein the processing of the at least one AIML model is performed inside of one or more MG instances configured by the MG configuration.

[0262] Clause 6. The method of clause 5, further comprising: transmitting AIML model processing time information associated with a set of AIML models to a network component, wherein the one or more MG instances are configured with a MG instance length that is based on the AIML model processing time information.

[0263] Clause 7. The method of any of clauses 5 to 6, further comprising: transmitting a request associated with a MG instance length to a network component, wherein the one or more MG instances are configured with the MG instance length in response to the request.

[0264] Clause 8. The method of clause 7, wherein the request comprises an explicit reference to the MG instance length, or wherein the request comprises a range of MG instance lengths, or wherein the request comprises a minimum MG instance length, or wherein the request comprises a maximum MG instance length.

[0265] Clause 9. The method of any of clauses 1 to 8, wherein the processing of the at least one AIML model is performed outside of one or more MG instances configured by the MG configuration.

[0266] Clause 10. The method of any of clauses 1 to 9, further comprising: receiving AIML model information associated with a set of AIML models, wherein the AIML model information comprises: a first indication that a first AIML model is permitted for processing inside of MG instances only, or a second indication that a second AIML model is not permitted for processing outside of MG instances only, or a third indication that a third AIML model is permitted for processing both inside of MG instances and outside of MGs, or a fourth indication that a fourth AIML model is permitted for processing inside of MG instances only if a MG instance length associated with the MG configuration exceeds a MG instance length threshold, or any combination thereof.

[0267] Clause 11. The method of any of clauses 1 to 10, further comprising: receiving a set of processing configurations for a given AIML model; and selecting a processing configuration from the set of processing configurations, wherein the processing processes the given AIML model inside or outside of one or more MG instances configured by the MG configuration in accordance with the selected processing configuration. 78 QC2403295WOQualcomm Ref. No.2403295WO

[0268] Clause 12. The method of clause 11, wherein the set of processing configurations are associated with different processing times or power consumptions or accuracies or any combination thereof, or wherein the set of processing configurations comprises a first subset of processing configurations for processing of the given AIML model inside of the one or more MG instances, or wherein the set of processing configurations comprises a second subset of processing configurations for processing of the given AIML model outside of the one or more MG instances, or any combination thereof.

[0269] Clause 13. The method of any of clauses 11 to 12, wherein the selecting is based on priority information associated with the given AIML model.

[0270] Clause 14. The method of any of clauses 1 to 13, wherein the MG configuration configures one or more MG instances for processing of a given AIML model associated with a functionality or output.

[0271] Clause 15. The method of clause 14, wherein a MG instance length is based on a set of criteria comprising: whether a non-AIML model associated with the same functionality or output is concurrently processed with the given AIML model during the one or more MG instances, or whether at least one additional AIML model is concurrently processed with the given AIML model during the one or more MG instances, or AIML model processing time information associated with the given AIML model, or any combination thereof.

[0272] Clause 16. The method of any of clauses 14 to 15, further comprising: performing one or more transmission operations during the one or more MG instances.

[0273] Clause 17. The method of any of clauses 14 to 16, further comprising: receiving another MG configuration that configures one or more other MG instances inside of which no AIML models are processed.

[0274] Clause 18. The method of clause 17, wherein the MG configuration and the another MG configuration are triggered or configured via different signaling types, or wherein the MG configuration is configured based on a first set of candidate MG instance lengths or MG periodicities and the another MG configuration is configured based on a second set of candidate MG instance lengths or MG periodicities, or wherein an explicit association between the MG configuration the given AIML model or the functionality of the given AIML model or the output of the given AIML model is defined. 79 QC2403295WOQualcomm Ref. No.2403295WO

[0275] Clause 19. A method of operating a network component, comprising: receiving at least one indication of at least one capability of a user equipment (UE) to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; and transmitting a MG configuration that is based on the at least one capability.

[0276] Clause 20. The method of clause 19, further comprising: receiving AIML model processing time information associated with a set of AIML models from the UE.

[0277] Clause 21. The method of clause 20, further comprising; configuring one or more MG instances of the MG configuration with a MG instance length that is based on the AIML model processing time information.

[0278] Clause 22. The method of any of clauses 20 to 21, further comprising: transmitting a request associated with a MG instance length to a wireless network component.

[0279] Clause 23. The method of clause 22, wherein the request comprises an explicit reference to the MG instance length, or wherein the request comprises a range of MG instance lengths, or wherein the request comprises a minimum MG instance length, or wherein the request comprises a maximum MG instance length.

[0280] Clause 24. The method of any of clauses 20 to 23, further comprising: determining AIML model processing time uncertainty information based on the AIML model processing time information and the at least one capability; and transmitting the AIML model processing time uncertainty information to a wireless network component.

[0281] Clause 25. The method of any of clauses 19 to 24, wherein the AIML model processing is associated with a position estimation session, or wherein the AIML model processing is associated with a sensing session, or wherein the AIML model processing is associated with channel state information (CSI) measurements, or wherein the AIML model processing is associated with beam management.

[0282] Clause 26. The method of any of clauses 19 to 25, wherein the AIML model processing is associated with AIML model training, or wherein the AIML model processing is associated with AIML model inferencing. 80 QC2403295WOQualcomm Ref. No.2403295WO

[0283] Clause 27. The method of any of clauses 19 to 26, wherein the at least one capability comprises: a first maximum number of AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML models the UE is capable of processing outside of the MG instance, or a first maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing outside of the MG instance, or a first inference time per inference for a second AIML model inside of the MG instance, or a second inference time per inference for the second AIML model outside of the MG instance, or a first buffering limit inside of the MG instance, or a second buffering limit outside of the MG instance, or a first number of inference processing units for a third AIML model inside of the MG instance, or a second number of inference processing units for the third AIML model outside of the MG instance, or any combination thereof.

[0284] Clause 28. The method of any of clauses 19 to 27, wherein the at least one capability comprises the first capability.

[0285] Clause 29. The method of any of clauses 19 to 28, wherein the at least one capability comprises the second capability.

[0286] Clause 30. A user equipment (UE), 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: transmit, via the one or more transceivers, at least one indication of at least one capability of the UE to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; receive, via the one or more transceivers, a MG configuration that is associated with processing of at least one AIML model and is based on the at least one capability; and process the at least one AIML model in accordance with the MG configuration.

[0287] Clause 31. The UE of clause 30, wherein the processing of the at least one AIML model is associated with a position estimation session, or wherein the processing of the at least 81 QC2403295WOQualcomm Ref. No.2403295WO one AIML model is associated with a sensing session, or wherein the processing of the at least one AIML model is associated with channel state information (CSI) measurements, or wherein the processing of the at least one AIML model is associated with beam management.

[0288] Clause 32. The UE of any of clauses 30 to 31, wherein the processing of the at least one AIML model is associated with AIML model training, or wherein the processing of the at least one AIML model is associated with AIML model inferencing.

[0289] Clause 33. The UE of any of clauses 30 to 32, wherein the at least one capability comprises: a first maximum number of AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML models the UE is capable of processing outside of the MG instance, or a first maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing outside of the MG instance, or a first inference time per inference for a second AIML model inside of the MG instance, or a second inference time per inference for the second AIML model outside of the MG instance, or a first buffering limit inside of the MG instance, or a second buffering limit outside of the MG instance, or a first number of inference processing units for a third AIML model inside of the MG instance, or a second number of inference processing units for the third AIML model outside of the MG instance, or any combination thereof.

[0290] Clause 34. The UE of any of clauses 30 to 33, wherein the processing of the at least one AIML model is performed inside of one or more MG instances configured by the MG configuration.

[0291] Clause 35. The UE of clause 34, wherein the one or more processors, either alone or in combination, are further configured to: transmit, via the one or more transceivers, AIML model processing time information associated with a set of AIML models to a network component, wherein the one or more MG instances are configured with a MG instance length that is based on the AIML model processing time information.

[0292] Clause 36. The UE of any of clauses 34 to 35, wherein the one or more processors, either alone or in combination, are further configured to: transmit, via the one or more transceivers, a request associated with a MG instance length to a network component, 82 QC2403295WOQualcomm Ref. No.2403295WO wherein the one or more MG instances are configured with the MG instance length in response to the request.

[0293] Clause 37. The UE of clause 36, wherein the request comprises an explicit reference to the MG instance length, or wherein the request comprises a range of MG instance lengths, or wherein the request comprises a minimum MG instance length, or wherein the request comprises a maximum MG instance length.

[0294] Clause 38. The UE of any of clauses 30 to 37, wherein the processing of the at least one AIML model is performed outside of one or more MG instances configured by the MG configuration.

[0295] Clause 39. The UE of any of clauses 30 to 38, wherein the one or more processors, either alone or in combination, are further configured to: receive, via the one or more transceivers, AIML model information associated with a set of AIML models, wherein the AIML model information comprises: a first indication that a first AIML model is permitted for processing inside of MG instances only, or a second indication that a second AIML model is not permitted for processing outside of MG instances only, or a third indication that a third AIML model is permitted for processing both inside of MG instances and outside of MGs, or a fourth indication that a fourth AIML model is permitted for processing inside of MG instances only if a MG instance length associated with the MG configuration exceeds a MG instance length threshold, or any combination thereof.

[0296] Clause 40. The UE of any of clauses 30 to 39, wherein the one or more processors, either alone or in combination, are further configured to: receive, via the one or more transceivers, a set of processing configurations for a given AIML model; and select a processing configuration from the set of processing configurations, wherein the processing processes the given AIML model inside or outside of one or more MG instances configured by the MG configuration in accordance with the selected processing configuration.

[0297] Clause 41. The UE of clause 40, wherein the set of processing configurations are associated with different processing times or power consumptions or accuracies or any combination thereof, or wherein the set of processing configurations comprises a first subset of processing configurations for processing of the given AIML model inside of the one or more MG instances, or wherein the set of processing configurations comprises a 83 QC2403295WOQualcomm Ref. No.2403295WO second subset of processing configurations for processing of the given AIML model outside of the one or more MG instances, or any combination thereof.

[0298] Clause 42. The UE of any of clauses 40 to 41, wherein the selecting is based on priority information associated with the given AIML model.

[0299] Clause 43. The UE of any of clauses 30 to 42, wherein the MG configuration configures one or more MG instances for processing of a given AIML model associated with a functionality or output.

[0300] Clause 44. The UE of clause 43, wherein a MG instance length is based on a set of criteria comprising: whether a non-AIML model associated with the same functionality or output is concurrently processed with the given AIML model during the one or more MG instances, or whether at least one additional AIML model is concurrently processed with the given AIML model during the one or more MG instances, or AIML model processing time information associated with the given AIML model, or any combination thereof.

[0301] Clause 45. The UE of any of clauses 43 to 44, wherein the one or more processors, either alone or in combination, are further configured to: perform one or more transmission operations during the one or more MG instances.

[0302] Clause 46. The UE of any of clauses 43 to 45, wherein the one or more processors, either alone or in combination, are further configured to: receive, via the one or more transceivers, another MG configuration that configures one or more other MG instances inside of which no AIML models are processed.

[0303] Clause 47. The UE of clause 46, wherein the MG configuration and the another MG configuration are triggered or configured via different signaling types, or wherein the MG configuration is configured based on a first set of candidate MG instance lengths or MG periodicities and the another MG configuration is configured based on a second set of candidate MG instance lengths or MG periodicities, or wherein an explicit association between the MG configuration the given AIML model or the functionality of the given AIML model or the output of the given AIML model is defined.

[0304] Clause 48. A network component, 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, at least one indication of at least one capability of a user equipment (UE) to perform artificial 84 QC2403295WOQualcomm Ref. No.2403295WO intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; and transmit, via the one or more transceivers, a MG configuration that is based on the at least one capability.

[0305] Clause 49. The network component of clause 48, wherein the one or more processors, either alone or in combination, are further configured to: receive, via the one or more transceivers, AIML model processing time information associated with a set of AIML models from the UE.

[0306] Clause 50. The network component of clause 49, wherein the one or more processors, either alone or in combination, are further configured to: configure one or more MG instances of the MG configuration with a MG instance length that is based on the AIML model processing time information.

[0307] Clause 51. The network component of any of clauses 49 to 50, wherein the one or more processors, either alone or in combination, are further configured to: transmit, via the one or more transceivers, a request associated with a MG instance length to a wireless network component.

[0308] Clause 52. The network component of clause 51, wherein the request comprises an explicit reference to the MG instance length, or wherein the request comprises a range of MG instance lengths, or wherein the request comprises a minimum MG instance length, or wherein the request comprises a maximum MG instance length.

[0309] Clause 53. The network component of any of clauses 49 to 52, wherein the one or more processors, either alone or in combination, are further configured to: determine AIML model processing time uncertainty information based on the AIML model processing time information and the at least one capability; and transmit, via the one or more transceivers, the AIML model processing time uncertainty information to a wireless network component.

[0310] Clause 54. The network component of any of clauses 48 to 53, wherein the AIML model processing is associated with a position estimation session, or wherein the AIML model processing is associated with a sensing session, or wherein the AIML model processing 85 QC2403295WOQualcomm Ref. No.2403295WO is associated with channel state information (CSI) measurements, or wherein the AIML model processing is associated with beam management.

[0311] Clause 55. The network component of any of clauses 48 to 54, wherein the AIML model processing is associated with AIML model training, or wherein the AIML model processing is associated with AIML model inferencing.

[0312] Clause 56. The network component of any of clauses 48 to 55, wherein the at least one capability comprises: a first maximum number of AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML models the UE is capable of processing outside of the MG instance, or a first maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing outside of the MG instance, or a first inference time per inference for a second AIML model inside of the MG instance, or a second inference time per inference for the second AIML model outside of the MG instance, or a first buffering limit inside of the MG instance, or a second buffering limit outside of the MG instance, or a first number of inference processing units for a third AIML model inside of the MG instance, or a second number of inference processing units for the third AIML model outside of the MG instance, or any combination thereof.

[0313] Clause 57. The network component of any of clauses 48 to 56, wherein the at least one capability comprises the first capability.

[0314] Clause 58. The network component of any of clauses 48 to 57, wherein the at least one capability comprises the second capability.

[0315] Clause 59. A user equipment (UE), comprising: means for transmitting at least one indication of at least one capability of the UE to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; means for receiving a MG configuration that is associated with processing of at 86 QC2403295WOQualcomm Ref. No.2403295WO least one AIML model and is based on the at least one capability; and means for processing the at least one AIML model in accordance with the MG configuration.

[0316] Clause 60. The UE of clause 59, wherein the processing of the at least one AIML model is associated with a position estimation session, or wherein the processing of the at least one AIML model is associated with a sensing session, or wherein the processing of the at least one AIML model is associated with channel state information (CSI) measurements, or wherein the processing of the at least one AIML model is associated with beam management.

[0317] Clause 61. The UE of any of clauses 59 to 60, wherein the processing of the at least one AIML model is associated with AIML model training, or wherein the processing of the at least one AIML model is associated with AIML model inferencing.

[0318] Clause 62. The UE of any of clauses 59 to 61, wherein the at least one capability comprises: a first maximum number of AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML models the UE is capable of processing outside of the MG instance, or a first maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing outside of the MG instance, or a first inference time per inference for a second AIML model inside of the MG instance, or a second inference time per inference for the second AIML model outside of the MG instance, or a first buffering limit inside of the MG instance, or a second buffering limit outside of the MG instance, or a first number of inference processing units for a third AIML model inside of the MG instance, or a second number of inference processing units for the third AIML model outside of the MG instance, or any combination thereof.

[0319] Clause 63. The UE of any of clauses 59 to 62, wherein the processing of the at least one AIML model is performed inside of one or more MG instances configured by the MG configuration.

[0320] Clause 64. The UE of clause 63, further comprising: means for transmitting AIML model processing time information associated with a set of AIML models to a network component, wherein the one or more MG instances are configured with a MG instance length that is based on the AIML model processing time information. 87 QC2403295WOQualcomm Ref. No.2403295WO

[0321] Clause 65. The UE of any of clauses 63 to 64, further comprising: means for transmitting a request associated with a MG instance length to a network component, wherein the one or more MG instances are configured with the MG instance length in response to the request.

[0322] Clause 66. The UE of clause 65, wherein the request comprises an explicit reference to the MG instance length, or wherein the request comprises a range of MG instance lengths, or wherein the request comprises a minimum MG instance length, or wherein the request comprises a maximum MG instance length.

[0323] Clause 67. The UE of any of clauses 59 to 66, wherein the processing of the at least one AIML model is performed outside of one or more MG instances configured by the MG configuration.

[0324] Clause 68. The UE of any of clauses 59 to 67, further comprising: means for receiving AIML model information associated with a set of AIML models, wherein the AIML model information comprises: a first indication that a first AIML model is permitted for processing inside of MG instances only, or a second indication that a second AIML model is not permitted for processing outside of MG instances only, or a third indication that a third AIML model is permitted for processing both inside of MG instances and outside of MGs, or a fourth indication that a fourth AIML model is permitted for processing inside of MG instances only if a MG instance length associated with the MG configuration exceeds a MG instance length threshold, or any combination thereof.

[0325] Clause 69. The UE of any of clauses 59 to 68, further comprising: means for receiving a set of processing configurations for a given AIML model; and means for selecting a processing configuration from the set of processing configurations, wherein the processing processes the given AIML model inside or outside of one or more MG instances configured by the MG configuration in accordance with the selected processing configuration.

[0326] Clause 70. The UE of clause 69, wherein the set of processing configurations are associated with different processing times or power consumptions or accuracies or any combination thereof, or wherein the set of processing configurations comprises a first subset of processing configurations for processing of the given AIML model inside of the one or more MG instances, or wherein the set of processing configurations comprises a 88 QC2403295WOQualcomm Ref. No.2403295WO second subset of processing configurations for processing of the given AIML model outside of the one or more MG instances, or any combination thereof.

[0327] Clause 71. The UE of any of clauses 69 to 70, wherein the selecting is based on priority information associated with the given AIML model.

[0328] Clause 72. The UE of any of clauses 59 to 71, wherein the MG configuration configures one or more MG instances for processing of a given AIML model associated with a functionality or output.

[0329] Clause 73. The UE of clause 72, wherein a MG instance length is based on a set of criteria comprising: whether a non-AIML model associated with the same functionality or output is concurrently processed with the given AIML model during the one or more MG instances, or whether at least one additional AIML model is concurrently processed with the given AIML model during the one or more MG instances, or AIML model processing time information associated with the given AIML model, or any combination thereof.

[0330] Clause 74. The UE of any of clauses 72 to 73, further comprising: means for performing one or more transmission operations during the one or more MG instances.

[0331] Clause 75. The UE of any of clauses 72 to 74, further comprising: means for receiving another MG configuration that configures one or more other MG instances inside of which no AIML models are processed.

[0332] Clause 76. The UE of clause 75, wherein the MG configuration and the another MG configuration are triggered or configured via different signaling types, or wherein the MG configuration is configured based on a first set of candidate MG instance lengths or MG periodicities and the another MG configuration is configured based on a second set of candidate MG instance lengths or MG periodicities, or wherein an explicit association between the MG configuration the given AIML model or the functionality of the given AIML model or the output of the given AIML model is defined.

[0333] Clause 77. A network component, comprising: means for receiving at least one indication of at least one capability of a user equipment (UE) to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a 89 QC2403295WOQualcomm Ref. No.2403295WO combination thereof; and means for transmitting a MG configuration that is based on the at least one capability.

[0334] Clause 78. The network component of clause 77, further comprising: means for receiving AIML model processing time information associated with a set of AIML models from the UE.

[0335] Clause 79. The network component of clause 78, further comprising; means for configuring one or more MG instances of the MG configuration with a MG instance length that is based on the AIML model processing time information.

[0336] Clause 80. The network component of any of clauses 78 to 79, further comprising: means for transmitting a request associated with a MG instance length to a wireless network component.

[0337] Clause 81. The network component of clause 80, wherein the request comprises an explicit reference to the MG instance length, or wherein the request comprises a range of MG instance lengths, or wherein the request comprises a minimum MG instance length, or wherein the request comprises a maximum MG instance length.

[0338] Clause 82. The network component of any of clauses 78 to 81, further comprising: means for determining AIML model processing time uncertainty information based on the AIML model processing time information and the at least one capability; and means for transmitting the AIML model processing time uncertainty information to a wireless network component.

[0339] Clause 83. The network component of any of clauses 77 to 82, wherein the AIML model processing is associated with a position estimation session, or wherein the AIML model processing is associated with a sensing session, or wherein the AIML model processing is associated with channel state information (CSI) measurements, or wherein the AIML model processing is associated with beam management.

[0340] Clause 84. The network component of any of clauses 77 to 83, wherein the AIML model processing is associated with AIML model training, or wherein the AIML model processing is associated with AIML model inferencing.

[0341] Clause 85. The network component of any of clauses 77 to 84, wherein the at least one capability comprises: a first maximum number of AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML models the UE is capable of processing outside of the MG instance, or a first maximum number 90 QC2403295WOQualcomm Ref. No.2403295WO of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing outside of the MG instance, or a first inference time per inference for a second AIML model inside of the MG instance, or a second inference time per inference for the second AIML model outside of the MG instance, or a first buffering limit inside of the MG instance, or a second buffering limit outside of the MG instance, or a first number of inference processing units for a third AIML model inside of the MG instance, or a second number of inference processing units for the third AIML model outside of the MG instance, or any combination thereof.

[0342] Clause 86. The network component of any of clauses 77 to 85, wherein the at least one capability comprises the first capability.

[0343] Clause 87. The network component of any of clauses 77 to 86, wherein the at least one capability comprises the second capability.

[0344] Clause 88. A non-transitory computer-readable medium storing computer-executable instructions that, when executed by a user equipment (UE), cause the UE to: transmit at least one indication of at least one capability of the UE to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; receive a MG configuration that is associated with processing of at least one AIML model and is based on the at least one capability; and process the at least one AIML model in accordance with the MG configuration.

[0345] Clause 89. The non-transitory computer-readable medium of clause 88, wherein the processing of the at least one AIML model is associated with a position estimation session, or wherein the processing of the at least one AIML model is associated with a sensing session, or wherein the processing of the at least one AIML model is associated with channel state information (CSI) measurements, or wherein the processing of the at least one AIML model is associated with beam management. 91 QC2403295WOQualcomm Ref. No.2403295WO

[0346] Clause 90. The non-transitory computer-readable medium of any of clauses 88 to 89, wherein the processing of the at least one AIML model is associated with AIML model training, or wherein the processing of the at least one AIML model is associated with AIML model inferencing.

[0347] Clause 91. The non-transitory computer-readable medium of any of clauses 88 to 90, wherein the at least one capability comprises: a first maximum number of AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML models the UE is capable of processing outside of the MG instance, or a first maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing outside of the MG instance, or a first inference time per inference for a second AIML model inside of the MG instance, or a second inference time per inference for the second AIML model outside of the MG instance, or a first buffering limit inside of the MG instance, or a second buffering limit outside of the MG instance, or a first number of inference processing units for a third AIML model inside of the MG instance, or a second number of inference processing units for the third AIML model outside of the MG instance, or any combination thereof.

[0348] Clause 92. The non-transitory computer-readable medium of any of clauses 88 to 91, wherein the processing of the at least one AIML model is performed inside of one or more MG instances configured by the MG configuration.

[0349] Clause 93. The non-transitory computer-readable medium of clause 92, further comprising computer-executable instructions that, when executed by the UE, cause the UE to: transmit AIML model processing time information associated with a set of AIML models to a network component, wherein the one or more MG instances are configured with a MG instance length that is based on the AIML model processing time information.

[0350] Clause 94. The non-transitory computer-readable medium of any of clauses 92 to 93, further comprising computer-executable instructions that, when executed by the UE, cause the UE to: transmit a request associated with a MG instance length to a network component, wherein the one or more MG instances are configured with the MG instance length in response to the request. 92 QC2403295WOQualcomm Ref. No.2403295WO

[0351] Clause 95. The non-transitory computer-readable medium of clause 94, wherein the request comprises an explicit reference to the MG instance length, or wherein the request comprises a range of MG instance lengths, or wherein the request comprises a minimum MG instance length, or wherein the request comprises a maximum MG instance length.

[0352] Clause 96. The non-transitory computer-readable medium of any of clauses 88 to 95, wherein the processing of the at least one AIML model is performed outside of one or more MG instances configured by the MG configuration.

[0353] Clause 97. The non-transitory computer-readable medium of any of clauses 88 to 96, further comprising computer-executable instructions that, when executed by the UE, cause the UE to: receive AIML model information associated with a set of AIML models, wherein the AIML model information comprises: a first indication that a first AIML model is permitted for processing inside of MG instances only, or a second indication that a second AIML model is not permitted for processing outside of MG instances only, or a third indication that a third AIML model is permitted for processing both inside of MG instances and outside of MGs, or a fourth indication that a fourth AIML model is permitted for processing inside of MG instances only if a MG instance length associated with the MG configuration exceeds a MG instance length threshold, or any combination thereof.

[0354] Clause 98. The non-transitory computer-readable medium of any of clauses 88 to 97, further comprising computer-executable instructions that, when executed by the UE, cause the UE to: receive a set of processing configurations for a given AIML model; and select a processing configuration from the set of processing configurations, wherein the processing processes the given AIML model inside or outside of one or more MG instances configured by the MG configuration in accordance with the selected processing configuration.

[0355] Clause 99. The non-transitory computer-readable medium of clause 98, wherein the set of processing configurations are associated with different processing times or power consumptions or accuracies or any combination thereof, or wherein the set of processing configurations comprises a first subset of processing configurations for processing of the given AIML model inside of the one or more MG instances, or wherein the set of processing configurations comprises a second subset of processing configurations for 93 QC2403295WOQualcomm Ref. No.2403295WO processing of the given AIML model outside of the one or more MG instances, or any combination thereof.

[0356] Clause 100. The non-transitory computer-readable medium of any of clauses 98 to 99, wherein the selecting is based on priority information associated with the given AIML model.

[0357] Clause 101. The non-transitory computer-readable medium of any of clauses 88 to 100, wherein the MG configuration configures one or more MG instances for processing of a given AIML model associated with a functionality or output.

[0358] Clause 102. The non-transitory computer-readable medium of clause 101, wherein a MG instance length is based on a set of criteria comprising: whether a non-AIML model associated with the same functionality or output is concurrently processed with the given AIML model during the one or more MG instances, or whether at least one additional AIML model is concurrently processed with the given AIML model during the one or more MG instances, or AIML model processing time information associated with the given AIML model, or any combination thereof.

[0359] Clause 103. The non-transitory computer-readable medium of any of clauses 101 to 102, further comprising computer-executable instructions that, when executed by the UE, cause the UE to: perform one or more transmission operations during the one or more MG instances.

[0360] Clause 104. The non-transitory computer-readable medium of any of clauses 101 to 103, further comprising computer-executable instructions that, when executed by the UE, cause the UE to: receive another MG configuration that configures one or more other MG instances inside of which no AIML models are processed.

[0361] Clause 105. The non-transitory computer-readable medium of clause 104, wherein the MG configuration and the another MG configuration are triggered or configured via different signaling types, or wherein the MG configuration is configured based on a first set of candidate MG instance lengths or MG periodicities and the another MG configuration is configured based on a second set of candidate MG instance lengths or MG periodicities, or wherein an explicit association between the MG configuration the given AIML model or the functionality of the given AIML model or the output of the given AIML model is defined. 94 QC2403295WOQualcomm Ref. No.2403295WO

[0362] Clause 106. A non-transitory computer-readable medium storing computer-executable instructions that, when executed by a network component, cause the network component to: receive at least one indication of at least one capability of a user equipment (UE) to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; and transmit a MG configuration that is based on the at least one capability.

[0363] Clause 107. The non-transitory computer-readable medium of clause 106, further comprising computer-executable instructions that, when executed by the network component, cause the network component to: receive AIML model processing time information associated with a set of AIML models from the UE.

[0364] Clause 108. The non-transitory computer-readable medium of clause 107, further comprising computer-executable instructions that, when executed by the network component, cause the network component to; configure one or more MG instances of the MG configuration with a MG instance length that is based on the AIML model processing time information.

[0365] Clause 109. The non-transitory computer-readable medium of any of clauses 107 to 108, further comprising computer-executable instructions that, when executed by the network component, cause the network component to: transmit a request associated with a MG instance length to a wireless network component.

[0366] Clause 110. The non-transitory computer-readable medium of clause 109, wherein the request comprises an explicit reference to the MG instance length, or wherein the request comprises a range of MG instance lengths, or wherein the request comprises a minimum MG instance length, or wherein the request comprises a maximum MG instance length.

[0367] Clause 111. The non-transitory computer-readable medium of any of clauses 107 to 110, further comprising computer-executable instructions that, when executed by the network component, cause the network component to: determine AIML model processing time uncertainty information based on the AIML model processing time information and the at least one capability; and transmit the AIML model processing time uncertainty information to a wireless network component. 95 QC2403295WOQualcomm Ref. No.2403295WO

[0368] Clause 112. The non-transitory computer-readable medium of any of clauses 106 to 111, wherein the AIML model processing is associated with a position estimation session, or wherein the AIML model processing is associated with a sensing session, or wherein the AIML model processing is associated with channel state information (CSI) measurements, or wherein the AIML model processing is associated with beam management.

[0369] Clause 113. The non-transitory computer-readable medium of any of clauses 106 to 112, wherein the AIML model processing is associated with AIML model training, or wherein the AIML model processing is associated with AIML model inferencing.

[0370] Clause 114. The non-transitory computer-readable medium of any of clauses 106 to 113, wherein the at least one capability comprises: a first maximum number of AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML models the UE is capable of processing outside of the MG instance, or a first maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing outside of the MG instance, or a first inference time per inference for a second AIML model inside of the MG instance, or a second inference time per inference for the second AIML model outside of the MG instance, or a first buffering limit inside of the MG instance, or a second buffering limit outside of the MG instance, or a first number of inference processing units for a third AIML model inside of the MG instance, or a second number of inference processing units for the third AIML model outside of the MG instance, or any combination thereof.

[0371] Clause 115. The non-transitory computer-readable medium of any of clauses 106 to 114, wherein the at least one capability comprises the first capability.

[0372] Clause 116. The non-transitory computer-readable medium of any of clauses 106 to 115, wherein the at least one capability comprises the second capability.

[0373] 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, 96 QC2403295WOQualcomm Ref. No.2403295WO electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

[0374] 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.

[0375] 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.

[0376] 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 97 QC2403295WOQualcomm Ref. No.2403295WO 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.

[0377] 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. Combinations of the above should also be included within the scope of computer-readable media.

[0378] 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 98 QC2403295WOQualcomm Ref. No.2403295WO 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. 99 QC2403295WO

Claims

Qualcomm Ref. No.2403295WO CLAIMS What is claimed is:

1. A user equipment (UE), 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: transmit, via the one or more transceivers, at least one indication of at least one capability of the UE to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; receive, via the one or more transceivers, a MG configuration that is associated with processing of at least one AIML model and is based on the at least one capability; and process the at least one AIML model in accordance with the MG configuration.

2. The UE of claim 1, wherein the processing of the at least one AIML model is associated with a position estimation session, or wherein the processing of the at least one AIML model is associated with a sensing session, or wherein the processing of the at least one AIML model is associated with channel state information (CSI) measurements, or wherein the processing of the at least one AIML model is associated with beam management. 100 QC2403295WOQualcomm Ref. No.2403295WOwherein the processing of the at least one AIML model is associated with AIML model training, or wherein the processing of the at least one AIML model is associated with AIML model inferencing.

4. The UE of claim 1, wherein the at least one capability comprises: a first maximum number of AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML models the UE is capable of processing outside of the MG instance, or a first maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing outside of the MG instance, or a first inference time per inference for a second AIML model inside of the MG instance, or a second inference time per inference for the second AIML model outside of the MG instance, or a first buffering limit inside of the MG instance, or a second buffering limit outside of the MG instance, or a first number of inference processing units for a third AIML model inside of the MG instance, or a second number of inference processing units for the third AIML model outside of the MG instance, or any combination thereof.

5. The UE of claim 1, wherein the processing of the at least one AIML model is performed inside of one or more MG instances configured by the MG configuration. 101 QC2403295WOQualcomm Ref. No.2403295WO 6. The UE of claim 5, wherein the one or more processors, either alone or in combination, are further configured to: transmit, via the one or more transceivers, AIML model processing time information associated with a set of AIML models to a network component, wherein the one or more MG instances are configured with a MG instance length that is based on the AIML model processing time information.

7. The UE of claim 5, wherein the one or more processors, either alone or in combination, are further configured to: transmit, via the one or more transceivers, a request associated with a MG instance length to a network component, wherein the one or more MG instances are configured with the MG instance length in response to the request.

8. The UE of claim 7, wherein the request comprises an explicit reference to the MG instance length, or wherein the request comprises a range of MG instance lengths, or wherein the request comprises a minimum MG instance length, or wherein the request comprises a maximum MG instance length.

9. The UE of claim 1, wherein the processing of the at least one AIML model is performed outside of one or more MG instances configured by the MG configuration.

10. The UE of claim 1, wherein the one or more processors, either alone or in combination, are further configured to: receive, via the one or more transceivers, AIML model information associated with a set of AIML models, wherein the AIML model information comprises: a first indication that a first AIML model is permitted for processing inside of MG instances only, or a second indication that a second AIML model is not permitted for processing outside of MG instances only, or 102 QC2403295WOQualcomm Ref. No.2403295WO a third indication that a third AIML model is permitted for processing both inside of MG instances and outside of MGs, or a fourth indication that a fourth AIML model is permitted for processing inside of MG instances only if a MG instance length associated with the MG configuration exceeds a MG instance length threshold, or any combination thereof.

11. The UE of claim 1, wherein the one or more processors, either alone or in combination, are further configured to: receive, via the one or more transceivers, a set of processing configurations for a given AIML model; and select a processing configuration from the set of processing configurations, wherein the processing processes the given AIML model inside or outside of one or more MG instances configured by the MG configuration in accordance with the selected processing configuration.

12. The UE of claim 11, wherein the set of processing configurations are associated with different processing times or power consumptions or accuracies or any combination thereof, or wherein the set of processing configurations comprises a first subset of processing configurations for processing of the given AIML model inside of the one or more MG instances, or wherein the set of processing configurations comprises a second subset of processing configurations for processing of the given AIML model outside of the one or more MG instances, or any combination thereof.

13. The UE of claim 11, wherein the selecting is based on priority information associated with the given AIML model. 103 QC2403295WOQualcomm Ref. No.2403295WO 14. The UE of claim 1, wherein the MG configuration configures one or more MG instances for processing of a given AIML model associated with a functionality or output.

15. The UE of claim 14, wherein a MG instance length is based on a set of criteria comprising: whether a non-AIML model associated with the same functionality or output is concurrently processed with the given AIML model during the one or more MG instances, or whether at least one additional AIML model is concurrently processed with the given AIML model during the one or more MG instances, or AIML model processing time information associated with the given AIML model, or any combination thereof.

16. The UE of claim 14, wherein the one or more processors, either alone or in combination, are further configured to: perform one or more transmission operations during the one or more MG instances.

17. The UE of claim 14, wherein the one or more processors, either alone or in combination, are further configured to: receive, via the one or more transceivers, another MG configuration that configures one or more other MG instances inside of which no AIML models are processed.

18. The UE of claim 17, wherein the MG configuration and the another MG configuration are triggered or configured via different signaling types, or wherein the MG configuration is configured based on a first set of candidate MG instance lengths or MG periodicities and the another MG configuration is configured based on a second set of candidate MG instance lengths or MG periodicities, or 104 QC2403295WOQualcomm Ref. No.2403295WO wherein an explicit association between the MG configuration the given AIML model or the functionality of the given AIML model or the output of the given AIML model is defined.

19. A network component, 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, at least one indication of at least one capability of a user equipment (UE) to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; and transmit, via the one or more transceivers, a MG configuration that is based on the at least one capability.

20. The network component of claim 19, wherein the one or more processors, either alone or in combination, are further configured to: receive, via the one or more transceivers, AIML model processing time information associated with a set of AIML models from the UE.

21. The network component of claim 20, wherein the one or more processors, either alone or in combination, are further configured to: configure one or more MG instances of the MG configuration with a MG instance length that is based on the AIML model processing time information. 105 QC2403295WOQualcomm Ref. No.2403295WO 22. The network component of claim 20, wherein the one or more processors, either alone or in combination, are further configured to: transmit, via the one or more transceivers, a request associated with a MG instance length to a wireless network component.

23. The network component of claim 22, wherein the request comprises an explicit reference to the MG instance length, or wherein the request comprises a range of MG instance lengths, or wherein the request comprises a minimum MG instance length, or wherein the request comprises a maximum MG instance length.

24. The network component of claim 20, wherein the one or more processors, either alone or in combination, are further configured to: determine AIML model processing time uncertainty information based on the AIML model processing time information and the at least one capability; and transmit, via the one or more transceivers, the AIML model processing time uncertainty information to a wireless network component.

25. The network component of claim 19, wherein the AIML model processing is associated with a position estimation session, or wherein the AIML model processing is associated with a sensing session, or wherein the AIML model processing is associated with channel state information (CSI) measurements, or wherein the AIML model processing is associated with beam management.

26. The network component of claim 19, wherein the AIML model processing is associated with AIML model training, or wherein the AIML model processing is associated with AIML model inferencing.

27. The network component of claim 19, wherein the at least one capability comprises: 106 QC2403295WOQualcomm Ref. No.2403295WO a first maximum number of AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML models the UE is capable of processing outside of the MG instance, or a first maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing inside of the MG instance, or a second maximum number of AIML model inferences per AIML model or per AIML model functionality or for all AIML models the UE is capable of processing outside of the MG instance, or a first inference time per inference for a second AIML model inside of the MG instance, or a second inference time per inference for the second AIML model outside of the MG instance, or a first buffering limit inside of the MG instance, or a second buffering limit outside of the MG instance, or a first number of inference processing units for a third AIML model inside of the MG instance, or a second number of inference processing units for the third AIML model outside of the MG instance, or any combination thereof.

28. The network component of claim 19, wherein the at least one capability comprises the first capability.

29. A method of operating a user equipment (UE), comprising: transmitting at least one indication of at least one capability of the UE to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or 107 QC2403295WOQualcomm Ref. No.2403295WO a combination thereof; receiving a MG configuration that is associated with processing of at least one AIML model and is based on the at least one capability; and processing the at least one AIML model in accordance with the MG configuration.

30. A method of operating a network component, comprising: receiving at least one indication of at least one capability of a user equipment (UE) to perform artificial intelligence machine learning (AIML) model processing, wherein the at least one capability comprises a first capability of the UE to perform the AIML model processing during a measurement gap (MG) instance, or wherein the at least one capability comprises a second capability of the UE to perform the AIML model processing outside of the MG instance, or a combination thereof; and transmitting a MG configuration that is based on the at least one capability. 108 QC2403295WO

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