Identification of machine learning model identifiers or pairing identifiers

Abstract

Various aspects of the present disclosure generally relate to wireless communications. In some aspects, a user equipment (UE) may receive a primary synchronization signal (PSS) and a secondary synchronization signal (SSS). The UE may identify a master information block (MIB) carried by a physical broadcast channel (PBCH) based at least in part on the PSS and the SSS, and identify a physical cell identifier (ID) based at least in part on one or more of the PSS or the SSS. The UE may identify a synchronization signal block (SSB) index based at least in part on the scrambling of the PBCH. The UE may identify a model ID associated with a machine learning (ML) model or a pairing ID associated with an ML model pair based at least in part on the SSB index or the physical cell ID. Numerous other aspects are described.

Description

Technical Field

[0001] All aspects of this disclosure relate to wireless communication and to techniques and apparatus for identifying machine learning models. Background Technology

[0002] Wireless communication systems are widely deployed to provide a variety of telecommunications services, such as telephone, video, data, messaging, and broadcasting. Typical wireless communication systems employ multiple access technologies that enable communication with multiple users by sharing available system resources (e.g., bandwidth, transmit power, etc.). Examples of such multiple access technologies include Code Division Multiple Access (CDMA) systems, Time Division Multiple Access (TDMA) systems, Frequency Division Multiple Access (FDMA) systems, Orthogonal Frequency Division Multiple Access (OFDMA) systems, Single Carrier Frequency Division Multiple Access (SC-FDMA) systems, Time Division Synchronous Code Division Multiple Access (TD-SCDMA) systems, and Long Term Evolution (LTE). LTE / LTE-Advanced is a set of enhancements to the Universal Mobile Telecommunications System (UMTS) mobile standard issued by the 3rd Generation Partnership Project (3GPP).

[0003] A wireless network may include one or more network nodes that support communication for wireless communication devices, such as user equipment (UE) or multiple UEs. A UE may communicate with network nodes via downlink and uplink communication. A "downlink" (or "DL") refers to the communication link from the network node to the UE, and an "uplink" (or "UL") refers to the communication link from the UE to the network node. Some wireless networks may support device-to-device communication, such as via local links (e.g., sidelinks (SL), wireless local area network (WLAN) links, and / or wireless personal area network (WPAN) links, etc.).

[0004] The aforementioned multiple access technologies have been adopted in various telecommunications standards to provide a common protocol that enables different UEs to communicate at the city, country, region, and / or global levels. New Radio (NR) (which may be referred to as 5G) is a set of enhancements to the LTE mobile standard issued by 3GPP. NR is designed to better support mobile broadband internet access by: improving spectrum efficiency; reducing costs; improving service; utilizing new spectrum; and better integrating with other open standards by using Orthogonal Frequency Division Multiplexing (OFDM) with Cyclic Prefix (CP) on the downlink (CP-OFDM), and CP-OFDM and / or Single Carrier Frequency Division Multiplexing (SC-FDM) (also known as Discrete Fourier Transform Extended OFDM (DFT-s-OFDM)) on the uplink; and supporting beamforming, Multiple-Input Multiple-Output (MIMO) antenna technologies and carrier aggregation. Further improvements to LTE, NR, and other radio access technologies remain useful as the demand for mobile broadband access continues to increase. Summary of the Invention

[0005] Some aspects described herein relate to a method for wireless communication performed at a user equipment (UE). The method may include receiving a primary synchronization signal (PSS) and a secondary synchronization signal (SSS). The method may include identifying a primary information block (MIB) carried by a physical broadcast channel (PBCH) based at least in part on the PSS and SSS, and identifying a physical cell identifier (ID) based at least in part on one or more of the PSS or SSS. The method may include identifying a synchronization signal block (SSB) index based at least in part on scrambling of the PBCH. The method may include identifying a model ID associated with a machine learning (ML) model or a pair ID associated with an ML model pair based at least in part on the SSB index or the physical cell ID.

[0006] Some aspects described herein relate to a method for performing wireless communication at a network entity. The method may include transmitting one or more SSBs, each SSB including a PSS, an SSS, and a PBCH carrying a MIB, each SSB being associated with an SSB index and a physical cell ID. The method may include transmitting one or more model IDs or one or more pair IDs in system information associated with the SSB index and the physical cell ID, each of the one or more model IDs being associated with an ML model, and each of the one or more pair IDs being associated with an ML model pair. The method may include identifying a model ID from one or more model IDs or identifying a pair ID from one or more pair IDs based at least in part on one or more of the SSB index or the physical cell ID.

[0007] Some aspects described herein relate to a method for wireless communication performed at a first network entity. This method may include selecting a pairing ID associated with an ML model pair that encodes and decodes channel state information (CSI) feedback, based at least in part on the location information of the UE. This method may include transmitting the pairing ID to one or more of the UE or a second network entity.

[0008] Some aspects described herein relate to a method for wireless communication performed at a UE. The method may include receiving a request for location information of the UE. The method may include transmitting the location information of the UE. The method may include receiving a pairing ID associated with an ML model pair.

[0009] Some aspects described herein relate to an apparatus for wireless communication at a UE. The apparatus may include one or more memories and one or more processors coupled to the one or more memories. The one or more processors may be configured to cause the UE to receive a PSS and an SSS. The one or more processors may be configured to cause the UE to identify a MIB carried by a PBCH based at least in part on the PSS and SSS. The one or more processors may be configured to identify a Physical Cell ID based at least in part on one or more of the PSS or SSS. The one or more processors may be configured to identify an SSB index based at least in part on scrambling of the PBCH. The one or more processors may be configured to identify a Model ID associated with an ML model or a Pair ID associated with an ML model pair based at least in part on the SSB index or the Physical Cell ID.

[0010] Some aspects described herein relate to an apparatus for wireless communication at a network entity. The apparatus may include one or more memories and one or more processors coupled to the one or more memories. The one or more processors may be configured to cause the network entity to transmit one or more SSBs, each SSB including a PSS, an SSS, and a PBCH carrying a MIB, each SSB being associated with an SSB index and a physical cell ID. The one or more processors may be configured to cause the network entity to transmit one or more model IDs or one or more pair IDs in system information associated with the SSB index and the physical cell ID, each of the one or more model IDs being associated with an ML model, and each of the one or more pair IDs being associated with an ML model pair. The one or more processors may be configured to cause the network entity to identify a model ID from one or more model IDs or a pair ID from one or more pair IDs, at least in part, based on one or more of the SSB index or the physical cell ID.

[0011] Some aspects described herein relate to an apparatus for wireless communication at a first network entity. The apparatus may include one or more memories and one or more processors coupled to the one or more memories. The one or more processors may be configured to cause the first network entity to select a pairing ID associated with an ML model pair that encodes and decodes CSI feedback, at least in part, based on the location information of the UE. The one or more processors may be configured to cause the first network entity to transmit the pairing ID to one or more of the UE or a second network entity.

[0012] Some aspects described herein relate to an apparatus for wireless communication at a UE. The apparatus may include one or more memories and one or more processors coupled to the one or more memories. The one or more processors may be configured to cause the UE to receive a request for location information of the UE. The one or more processors may be configured to cause the UE to transmit the UE's location information. The one or more processors may be configured to cause the UE to receive a pairing ID associated with an ML model pair.

[0013] Some aspects described herein relate to a non-transitory computer-readable medium storing a set of instructions for wireless communication by a UE. When executed by one or more processors of the UE, the set of instructions enables the UE to receive a PSS and an SSS. When executed by one or more processors of the UE, the set of instructions enables the UE to identify a MIB carried by a PBCH, at least partially based on the PSS and SSS. When executed by one or more processors of the UE, the set of instructions enables the UE to identify a Physical Cell ID, at least partially based on one or more of the PSS or SSS. When executed by one or more processors of the UE, the set of instructions enables the UE to identify an SSB index, at least partially based on PBCH scrambling. When executed by one or more processors of the UE, the set of instructions enables the UE to identify a model ID associated with an ML model or a pair ID associated with an ML model pair, at least partially based on the SSB index or the Physical Cell ID.

[0014] Some aspects described herein relate to a non-transitory computer-readable medium storing a set of instructions for wireless communication by a network entity. When executed by one or more processors of the network entity, the set of instructions causes the network entity to transmit one or more SSBs, each SSB including a PSS, an SSS, and a PBCH carrying a MIB, each SSB being associated with an SSB index and a physical cell ID. When executed by one or more processors of the network entity, the set of instructions causes the network entity to transmit one or more model IDs or one or more pair IDs in system information associated with the SSB index and the physical cell ID, each of the one or more model IDs being associated with an ML model, and each of the one or more pair IDs being associated with an ML model pair. When executed by one or more processors of the network entity, the set of instructions causes the network entity to identify a model ID from one or more model IDs or a pair ID from one or more pair IDs, at least in part, based on one or more of the SSB index or the physical cell ID.

[0015] Some aspects described herein relate to a non-transitory computer-readable medium storing a set of instructions for wireless communication by a first network entity. When executed by one or more processors of the first network entity, the set of instructions enables the first network entity to select a pairing ID associated with an ML model pair that encodes and decodes CSI feedback, at least in part, based on the location information of the UE. When executed by one or more processors of the first network entity, the set of instructions enables the first network entity to transmit the pairing ID to one or more of the UE or a second network entity.

[0016] Some aspects described herein relate to a non-transitory computer-readable medium storing a set of instructions for wireless communication by a UE. When executed by one or more processors of the UE, the set of instructions enables the UE to receive a request for location information. When executed by one or more processors of the UE, the set of instructions enables the UE to transmit its location information. When executed by one or more processors of the UE, the set of instructions enables the UE to receive a pairing ID associated with an ML model pair.

[0017] Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include components for receiving a PSS and an SSS. The apparatus may include components for identifying a MIB carried by a PBCH, at least in part based on the PSS and SSS, and for identifying a Physical Cell ID, at least in part based on one or more of the PSS or SSS. The apparatus may include components for identifying an SSB index, at least in part based on PBCH scrambling. The apparatus may include components for identifying a model ID associated with an ML model or a pair ID associated with an ML model pair, at least in part based on the SSB index or the Physical Cell ID.

[0018] Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include components for transmitting one or more SSBs, each SSB including a PSS, an SSS, and a PBCH carrying a MIB, each SSB being associated with an SSB index and a physical cell ID. The apparatus may include components for transmitting one or more model IDs or one or more pair IDs in system information associated with the SSB index and the physical cell ID, each of the one or more model IDs being associated with an ML model, and each of the one or more pair IDs being associated with an ML model pair. The apparatus may include components for identifying a model ID from one or more model IDs or a pair ID from one or more pair IDs, at least in part based on one or more of the SSB index or the physical cell ID.

[0019] Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include components for selecting a pairing ID associated with an ML model pair that encodes and decodes CSI feedback, based at least in part on location information of another device. The apparatus may also include components for transmitting the pairing ID to one or more of the other devices or network entities.

[0020] Some aspects described herein relate to an apparatus for wireless communication. The apparatus may include components for receiving a request for location information of the apparatus. The apparatus may include components for transmitting the location information of the apparatus. The apparatus may include components for receiving a pairing ID associated with an ML model pair.

[0021] The general categories include, as fully described with reference to the accompanying drawings and description and illustrated in the accompanying drawings and description, methods, apparatuses, systems, computer program products, non-transitory computer-readable media, user equipment, base stations, network entities, network nodes, wireless communication devices and / or processing systems.

[0022] The features and technical advantages of the examples according to this disclosure have been summarized rather broadly above to facilitate a better understanding of the detailed description below. Additional features and advantages will be described below. The disclosed concepts and specific examples can be readily used as the basis for modifying or designing other structures for achieving the same purpose of this disclosure. Such equivalent constructions do not depart from the scope of the appended claims. The characteristics of the concepts disclosed herein (both their organization and manner of operation) and their associated advantages will be better understood in conjunction with the accompanying drawings, based on the following description. Each of the drawings provided is for illustrative and descriptive purposes and not as a definition of limitation of the claims. Attached Figure Description

[0023] To gain a full understanding of the foregoing features of this disclosure, a more specific description of the brief overview can be obtained by referring to various aspects, some of which are illustrated in the accompanying drawings. However, it should be noted that the drawings illustrate only certain typical aspects of this disclosure and are therefore not to be considered as limiting its scope, as other equally valid aspects may be acknowledged in this description. The same reference numerals in different drawings may identify the same or similar elements.

[0024] Figure 1 This is a diagram illustrating an example of a wireless network according to the present disclosure.

[0025] Figure 2 This is a diagram illustrating an example of communication between a network node and a user equipment (UE) in a wireless network according to the present disclosure.

[0026] Figure 3 This is a diagram illustrating an example decomposed base station architecture according to this disclosure.

[0027] Figure 4 This is a diagram illustrating an example of encoding and decoding Channel State Information (CSI) according to this disclosure.

[0028] Figure 5 This is a diagram illustrating an example of the use of a machine learning (ML) model according to this disclosure.

[0029] Figures 6A to 6B This is a diagram illustrating an example of an identifier ML model according to this disclosure.

[0030] Figure 7 This is a diagram illustrating an example of using an ML model in accordance with this disclosure.

[0031] Figure 8 This is a diagram illustrating an example of using an ML model in accordance with this disclosure.

[0032] Figure 9 This is a diagram illustrating an example process performed, for example, at a UE or a device of a UE, according to this disclosure.

[0033] Figure 10 This is a diagram illustrating an example process performed, for example, at a network entity or a device of a network entity, according to the present disclosure.

[0034] Figure 11 This is a diagram illustrating an example process performed, for example, at a first network entity or a device of the first network entity, according to the present disclosure.

[0035] Figure 12 This is a diagram illustrating an example process performed, for example, at a UE or a device of a UE, according to this disclosure.

[0036] Figure 13 This is a diagram of an example device for wireless communication according to the present disclosure.

[0037] Figure 14 This is a diagram illustrating an example of a hardware implementation of a device for employing a processing system according to the present disclosure.

[0038] Figure 15 The diagram illustrates an example of a specific implementation of the code and circuitry for a device according to this disclosure.

[0039] Figure 16 This is a diagram of an example device for wireless communication according to the present disclosure.

[0040] Figure 17 This is a diagram illustrating an example of a hardware implementation of a device for employing a processing system according to the present disclosure.

[0041] Figure 18The diagram illustrates an example of a specific implementation of the code and circuitry for a device according to this disclosure. Detailed Implementation

[0042] Channel State Information (CSI) Reference Signal (CSI-RS) can be configured to be transmitted from a network entity (e.g., a base station) to a User Equipment (UE). The CSI-RS is a reference signal that the UE can use to provide feedback to the network entity regarding transmission conditions on the channel. In some examples, the UE can measure the CSI-RS and report the CSI to the network entity. Using a model trained via machine learning (ML), the CSI can be encoded at the UE and decoded at the network entity. The UE can measure the CSI-RS and send a CSI report indicating the CSI, such as a Pre-decoder Matrix Indicator (PMI). The PMI is a matrix representing how data is transmitted at the antenna port (e.g., how signals are processed for transmission or reception at the antenna port). The CSI report may include other information, such as a Layer 1 (L1) Reference Signal Received Power (RSRP) parameter indicating signal strength on the channel, a Channel Quality Indicator (CQI) parameter indicating communication quality on the channel, and / or a resource indicator. The CSI report may include a codebook, which is a collection of one or more pre-decoders or one or more PMIs. The codebook may include a matrix (with complex-valued elements) that transforms data bits into another set of data, which is mapped to each antenna port. The UE can use the sequence of bits to report PMI.

[0043] CSI includes CSI or CSI parameters fed back by the UE to network entities. ML-based CSI feedback (including AI-based CSI feedback) includes CSI feedback that is compressed or encoded before transmission using ML. ML at the encoder can use an ML model trained for optimization of the encoding. In some examples, ML-based CSI feedback can replace the codebook with an ML-based CSI encoder and decoder. The decoder at the network entity can use ML to decode the encoded CSI feedback. ML can also use a trained ML model. Depending on one or more examples, the encoder may resemble a PMI search algorithm, and the decoder may resemble a PMI codebook used to convert CSI report bits into PMI codewords. Using ML, CSI can be encoded (e.g., compressed) at the UE and decoded (e.g., reconstructed) at the network entity. In some examples, the ML model and ML model pair (the ML model associated with encoding and the ML model used for corresponding decoding) can be explicitly indicated via Radio Resource Control (RRC) signaling. While the ML model can be explicitly indicated to the UE, this consumes signaling resources.

[0044] According to the various aspects described herein, the UE may implicitly identify ML models and / or ML model pairs. The UE may identify one or more model identifiers (IDs) for an ML model or one or more pair IDs for an ML model pair. The UE may identify the model ID or pair ID based at least in part on a Synchronization Signal Block (SSB) index and / or a Physical Cell ID. The SSB index identifies the SSB, and the Physical Cell ID identifies the cell. By identifying one or more ML models based at least in part on the SSB index and / or the Physical Cell ID, the UE can use an appropriate ML model to encode or compress UE information (e.g., CSI feedback), and network entities can use the ML model or the paired ML model to reconstruct CSI from the compressed information. In some aspects, by identifying one or more ML models based at least in part on the SSB index and / or the Physical Cell ID, the UE can use an appropriate ML model to predict CSI. The UE can use the ML model to predict beams for future communications. Prediction may include predicting narrow beams from wider beams or predicting beams for future time instances. The CSI is efficiently and optimally encoded or compressed by ML and then decoded or reconstructed, providing the network entity with an accurate representation of the CSI. The network entity can use the accurate CSI to schedule and configure the UE based on the channel conditions indicated by the CSI, thereby improving communication. By utilizing ML model selection to improve communication, latency is reduced and signaling resources are saved. Furthermore, by not explicitly sending the model ID or pairing ID, the network entity can save signaling resources.

[0045] Various aspects of this disclosure are described more fully below with reference to the accompanying drawings. However, this disclosure may be embodied in many different forms and should not be construed as limited to any particular structure or function presented throughout this disclosure. Rather, these aspects are provided so that this disclosure will be comprehensive and complete, and will fully convey the scope of this disclosure to those skilled in the art. Those skilled in the art will appreciate that the scope of this disclosure is intended to cover any aspect of this disclosure disclosed herein, whether implemented independently or in combination with any other aspect of this disclosure. For example, any number of aspects set forth herein may be used to implement an apparatus or practice. Furthermore, the scope of this disclosure is intended to cover such apparatuses or methods practiced using structures, functions, or structures and functions other than or different from the aspects of the disclosure set forth herein. It should be understood that any aspect of the disclosure herein may be embodied by one or more elements of the claims.

[0046] Various devices and techniques will now be used to illustrate several aspects of a telecommunications system. These devices and techniques will be described in detail below and illustrated in the accompanying drawings by various boxes, modules, components, circuits, steps, processes, or algorithms (collectively, “elements”). These elements can be implemented using hardware, software, or a combination thereof. Whether such elements are implemented as hardware or software depends on the specific application and the design constraints imposed on the system as a whole.

[0047] Although terms generally associated with 5G or New Radio (NR) Radio Access Technology (RAT) may be used herein to describe aspects, aspects of this disclosure may be applied to other RATs, such as 3G RAT, 4G RAT and / or 5G and later (e.g., 6G) RATs.

[0048] Figure 1 This is a diagram illustrating an example of a wireless network 100 according to the present disclosure. The wireless network 100 may be a 5G (e.g., NR) network and / or a 4G (e.g., LTE) network, or may include elements of a 5G (e.g., NR) network and / or elements of a 4G (e.g., LTE) network, etc. The wireless network 100 may include one or more network nodes 110 (shown as network node 110a, network node 110b, network node 110c, and network node 110d), one or more UEs 120 (shown as UE 120a, UE 120b, UE 120c, UE 120d, and UE 120e), and / or other entities. Network node 110 is a network node that communicates with UE 120. As shown, network node 110 may include one or more network nodes. For example, network node 110 can be an aggregated network node, meaning that an aggregated network node is configured to utilize a radio protocol stack that is physically or logically integrated within a single radio access network (RAN) node (e.g., within a single device or unit). As another example, network node 110 can be a decomposed network node (sometimes referred to as a decomposed base station), meaning that network node 110 is configured to utilize a protocol stack that is physically or logically distributed among two or more nodes (such as one or more central units (CUs), one or more distributed units (DUs), or one or more radio units (RUs)).

[0049] In some examples, network node 110 is or includes network nodes (such as RUs) that communicate with UE 120 via a radio access link. In some examples, network node 110 is or includes network nodes (such as DUs) that communicate with other network nodes 110 via a fronthaul or midhaul link. In some examples, network node 110 is or includes network nodes (such as CUs) that communicate with other network nodes 110 via a midhaul link or with the core network via a backhaul link. In some examples, network node 110 (such as aggregated network node 110 or decomposed network node 110) may include multiple network nodes, such as one or more RUs, one or more CUs, and / or one or more DUs. Network node 110 may include, for example, NR base stations, LTE base stations, Node Bs, eNBs (e.g., in 4G), gNBs (e.g., in 5G), access points, Transmit / Receive Points (TRPs), DUs, RUs, CUs, network mobility elements, core network nodes, network elements, network equipment, RAN nodes, or combinations thereof. In some examples, network nodes 110 can interconnect with each other or to one or more other network nodes 110 in the wireless network 100 using any suitable transport network through various types of fronthaul, midhaul, and / or backhaul interfaces (such as direct physical connections, air interfaces, or virtual networks).

[0050] In some examples, network node 110 may provide communication coverage for a specific geographic area. In the 3rd Generation Partnership Project (3GPP), depending on the context of terminology use, the term "cell" may refer to the coverage area of ​​network node 110 and / or the network node subsystem serving that coverage area. Network node 110 may provide communication coverage for macrocells, picocells, femtocells, and / or another type of cell. A macrocell may cover a relatively large geographic area (e.g., with a radius of several kilometers) and may allow unrestricted access by UE 120 with a service subscription. A picocell may cover a relatively small geographic area and may allow unrestricted access by UE 120 with a service subscription. A femtocell may cover a relatively small geographic area (e.g., a home) and may allow restricted access by UE 120 associated with the femtocell (e.g., UE 120 in a Closed Subscriber Group (CSG)). Network node 110 used for macrocells may be referred to as a macro network node. Network node 110 used for picocells may be referred to as a pico network node. The network node 110 used for femtocells can be referred to as a femtocell network node or a home network node. Figure 1In the example shown, network node 110a can be a macro network node for macro cell 102a, network node 110b can be a pico network node for pico cell 102b, and network node 110c can be a femto network node for femto cell 102c. Network nodes can support one or more (e.g., three) cells. In some examples, the cells may not necessarily be stationary, and the geographical area of ​​the cells may move depending on the location of the mobile network node 110 (e.g., a mobile network node).

[0051] In some aspects, the term "base station" or "network node" may refer to an aggregated base station, a decomposed base station, an integrated access and backhaul (IAB) node, a relay node, or one or more components thereof. For example, in some aspects, "base station" or "network node" may refer to a CU, DU, RU, a near real-time (near RT) RAN intelligent controller (RIC), or a non-real-time (non-RT) RIC, or a combination thereof. In some aspects, the term "base station" or "network node" may refer to a device configured to perform one or more functions (such as those described herein in conjunction with network node 110). In some aspects, the term "base station" or "network node" may refer to multiple devices configured to perform one or more functions. For example, in some distributed systems, each of multiple different devices (which may be located in the same geographical location or different geographical locations) may be configured to perform at least a portion of a function, or to repeatedly perform at least a portion of that function, and the term "base station" or "network node" may refer to any one or more of these different devices. In some aspects, the term "base station" or "network node" may refer to one or more virtual base stations or one or more virtual base station functions. For example, in some aspects, two or more base station functions can be instantiated on a single device. In some aspects, the term "base station" or "network node" may refer to one base station function rather than another. In this way, a single device may include more than one base station.

[0052] Wireless network 100 may include one or more relay stations. A relay station is a network node that can receive data transmissions from upstream nodes (e.g., network node 110 or UE 120) and transmit data to downstream nodes (e.g., UE 120 or network node 110). A relay station may be a UE 120 that can relay transmissions for other UE 120s. Figure 1 In the example shown, network node 110d (e.g., a relay network node) can communicate with network node 110a (e.g., a macro network node) and UE 120d to facilitate communication between network node 110a and UE 120d. The network node 110 for relay communication may be referred to as a relay station, relay base station, relay network node, relay node, repeater, etc.

[0053] Wireless network 100 can be a heterogeneous network, comprising different types of network nodes 110, such as macro network nodes, pico network nodes, femto network nodes, relay network nodes, etc. These different types of network nodes 110 may have different transmit power levels, different coverage areas, and / or different effects on interference in wireless network 100. For example, macro network nodes may have high transmit power levels (e.g., 5 watts to 40 watts), while pico network nodes, femto network nodes, and relay network nodes may have lower transmit power levels (e.g., 0.1 watts to 2 watts).

[0054] Network controller 130 may be coupled to or communicate with a group of network nodes 110, and may provide coordination and control for these network nodes 110. Network controller 130 may communicate with network nodes 110 via a backhaul or midhaul link. Network nodes 110 may communicate directly with each other, or indirectly via a wireless or wired backhaul link. In some aspects, network controller 130 may be a CU or a core network device, or may include a CU or a core network device.

[0055] UE 120 may be distributed throughout the wireless network 100, and each UE 120 may be stationary or mobile. UE 120 may include, for example, access terminals, terminals, mobile stations, and / or subscriber units. UE 120 may be a cellular phone (e.g., a smartphone), a personal digital assistant (PDA), a wireless modem, a wireless communication device, a handheld device, a laptop computer, a cordless phone, a wireless local loop (WLL) station, a tablet computer, a camera, a gaming device, a netbook, a smartbook, an ultrabook, a medical device, a biometric device, a wearable device (e.g., a smartwatch, smart clothing, smart glasses, a smart wristband, smart jewelry (e.g., a smart ring or smart bracelet)), an entertainment device (e.g., a music device, a video device, and / or a satellite radio), a vehicle component or sensor, a smart meter / sensor, industrial manufacturing equipment, a GPS device, a UE function of a network node, and / or any other suitable device configured to communicate via wireless or wired media.

[0056] Some UEs 120 may be considered Machine-Type Communication (MTC) or Evolved or Enhanced Machine-Type Communication (eMTC) UEs. MTC UEs and / or eMTC UEs may include, for example, robots, unmanned aerial vehicles, remote devices, sensors, instruments, monitors, and / or location tags that can communicate with network nodes, another device (e.g., a remote device), or some other entity. Some UEs 120 may be considered Internet of Things (IoT) devices, and / or may be implemented as NB-IoT (Narrowband IoT) devices. Some UEs 120 may be considered customer premises equipment. UEs 120 may be housed within a housing containing components such as processor components and / or memory components. In some examples, the processor components and memory components may be coupled together. For example, the processor components (e.g., one or more processors) and memory components (e.g., memory) may be operatively coupled, communicatively coupled, electronically coupled, and / or electrically coupled.

[0057] Generally, any number of wireless networks 100 can be deployed in a given geographical area. Each wireless network 100 can support a specific RAT and can operate on one or more frequencies. A RAT may be referred to as a radio technology, air interface, etc. A frequency may be referred to as a carrier, frequency channel, etc. Each frequency in a given geographical area can support a single RAT to avoid interference between wireless networks using different RATs. In some cases, NR or 5G RAT networks can be deployed.

[0058] In some examples, two or more UEs 120 (e.g., shown as UE 120a and UE 120e) may communicate directly using one or more sidelink channels (e.g., without using network node 110 as an intermediary device to communicate with each other). For example, UE 120 may communicate using peer-to-peer (P2P) communication, device-to-device (D2D) communication, vehicle-to-everything (V2X) protocols (e.g., which may include vehicle-to-vehicle (V2V) protocols, vehicle-to-infrastructure (V2I) protocols, or vehicle-to-pedestrian (V2P) protocols) and / or mesh networks. In such examples, UE 120 may perform scheduling operations, resource selection operations, and / or other operations described elsewhere herein as being performed by network node 110.

[0059] The electromagnetic spectrum is typically subdivided into various categories, bands, channels, etc., by frequency / wavelength. In 5G NR, two initial operating bands have been designated as frequency ranges FR1 (410MHz to 7.125GHz) and FR2 (24.25GHz to 52.6GHz). It should be understood that although a portion of FR1 is greater than 6GHz, in various documents and articles, FR1 is often (interchangeably) referred to as the "sub-6GHz" band. Similar naming issues sometimes occur with FR2, which is often (interchangeably) referred to as the "millimeter wave" band in documents and articles, although this is different from the Extremely High Frequency (EHF) band (30GHz to 300GHz) designated as "millimeter wave" by the International Telecommunication Union (ITU).

[0060] The frequencies between FR1 and FR2 are generally referred to as intermediate frequency (IF) bands. Recent 5G NR studies have identified the operating bands used for these IF bands as the frequency range designation FR3 (7.125 GHz to 24.25 GHz). Bands falling within FR3 can inherit FR1 and / or FR2 characteristics, thus effectively extending the features of FR1 and / or FR2 to IF band frequencies. Furthermore, higher frequency bands are currently being explored to extend 5G NR operation beyond 52.6 GHz. For example, three higher operating frequency bands have been identified as the frequency range designations FR4a or FR4-1 (52.6 GHz to 71 GHz), FR4 (52.6 GHz to 114.25 GHz), and FR5 (114.25 GHz to 300 GHz). Each of these higher frequency bands falls within the EHF band.

[0061] Considering the examples above, unless otherwise specifically stated, it should be understood that if the term "below 6 GHz" is used herein, it can broadly refer to frequencies below 6 GHz, within FR1, or including intermediate frequency bands. Furthermore, unless otherwise specifically stated, it should be understood that if the term "millimeter wave" is used herein, it can broadly refer to frequencies that can include intermediate frequency bands, within FR2, FR4, FR4-a, or FR4-1 and / or FR5, or within the EHF band. Modifications to frequencies included in these operating frequency bands (e.g., FR1, FR2, FR3, FR4, FR4-a, FR4-1, and / or FR5) are contemplated, and the techniques described herein are applicable to those modified frequency ranges.

[0062] In some aspects, the UE (e.g., UE 120) may include a communication manager 140. As described in more detail elsewhere herein, the communication manager 140 may receive a primary synchronization signal (PSS) and a secondary synchronization signal (SSS). The communication manager 140 may identify the primary information block (MIB) carried by the physical broadcast channel (PBCH) based at least in part on the PSS and SSS, and identify the physical cell ID based at least in part on one or more of the PSS or SSS. The communication manager 140 may identify the SSB index based at least in part on the scrambling of the PBCH. The communication manager 140 may identify the model ID associated with an ML model or the pair ID associated with an ML model pair based at least in part on the SSB index or the physical cell ID.

[0063] In some respects, as described in more detail elsewhere herein, the communication manager 140 may receive requests for the location information of the UE. The communication manager 140 may transmit the location information of the UE. The communication manager 140 may receive a pairing ID associated with an ML model pair. Additionally or alternatively, the communication manager 140 may perform one or more other operations described herein.

[0064] In some aspects, network entities (e.g., network node 110) may include a communication manager 150. As described in more detail elsewhere herein, the communication manager 150 may send one or more SSBs, each SSB including a PSS, an SSS, and a PBCH carrying a MIB, each SSB associated with an SSB index and a physical cell ID. The communication manager 150 may send one or more model IDs or one or more pair IDs in system information associated with the SSB index and physical cell ID, each of the one or more model IDs being associated with an ML model, and each of the one or more pair IDs being associated with an ML model pair. The communication manager 150 may identify a model ID from one or more model IDs or a pair ID from one or more pair IDs based at least in part on one or more of the SSB index or physical cell ID. Additionally or alternatively, the communication manager 150 may perform one or more other operations described herein.

[0065] In some respects, as described in more detail elsewhere herein, the communication manager 150 may select a pairing ID associated with the ML model pair that encodes and decodes CSI feedback, based at least in part on the UE's location information. The communication manager 150 may send the pairing ID to one or more of the UE or other network entities. Additionally or alternatively, the communication manager 150 may perform one or more other operations described herein.

[0066] As indicated above, Figure 1 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 1 The examples described are different.

[0067] Figure 2 This is a diagram illustrating example 200 of communication between network node 110 and UE 120 in a wireless network 100 according to this disclosure. Network node 110 may be equipped with a set of antennas 234a to 234t, such as... T One antenna ( T ≥1). The UE 120 may be equipped with a set of antennas 252a to 252r, such as R One antenna ( R ≥1). Network node 110 of Example 200 includes one or more radio frequency components, such as antenna 234 and modem 232. In some examples, network node 110 may include an interface, communication components, or another component that facilitates communication with UE 120 or another network node. Some network node 110 may not include radio frequency components that facilitate direct communication with UE 120, such as one or more CUs or one or more DUs.

[0068] At network node 110, transmitting processor 220 can receive data from data source 212 intended for use by UE 120 (or a group of UEs 120). Transmitting processor 220 can select one or more modulation and decoding schemes (MCS) for UE 120, at least in part, based on one or more CQIs received from UE 120. Network node 110 can process (e.g., encode and modulate) the data for UE 120, at least in part, based on the MCS selected for UE 120, and can provide data symbols for UE 120. Transmitting processor 220 can process system information (e.g., semi-static resource partitioning information (SRPI)) and control information (e.g., CQI requests, grants, and / or upper-layer signaling), and provide overhead symbols and control symbols. Transmitting processor 220 can generate reference symbols for reference signals (e.g., cell-specific reference signals (CRS) or demodulation reference signals (DMRS)) and synchronization signals (e.g., PSS or SSS). The transmit (TX) multiple-input multiple-output (MIMO) processor 230 can perform spatial processing (e.g., pre-decoding) on ​​data symbols, control symbols, overhead symbols, and / or reference symbols where applicable, and can transmit a set of output symbol streams (e.g., T Each output symbol stream is provided to a corresponding set of modems 232 (e.g., ...). TEach modem 232a to 232t may be used to process a corresponding output symbol stream (e.g., for OFDM) to obtain an output sample stream. For example, each output symbol stream may be provided to a modulator component (MOD) of modem 232. Each modem 232 may use a corresponding modulator component to process the corresponding output symbol stream (e.g., for OFDM) to obtain an output sample stream. Each modem 232 may also use a corresponding modulator component to process the output sample stream (e.g., convert to analog, amplify, filter, and / or up-convert) to obtain a downlink signal. Modems 232a to 232t may be used via a corresponding set of antennas 234 (e.g., T Each antenna (shown as antennas 234a to 234t) is used to transmit a set of downlink signals (e.g., ...). T (One downlink signal).

[0069] At UE 120, a set of antennas 252 (shown as antennas 252a to 252r) can receive downlink signals from network node 110 and / or other network nodes 110 and can transmit a set of received signals (e.g., R The received signals are provided to a group of modems 254 (e.g., R Each modem 254 (shown as modems 254a to 254r) may receive a signal. For example, each received signal may be provided to a demodulator component (shown as DEMOD) of modem 254. Each modem 254 may use a corresponding demodulator component to condition (e.g., filter, amplify, down-convert, and / or digitize) the received signal to obtain an input sample. Each modem 254 may use a demodulator component to further process the input sample (e.g., for OFDM) to obtain a received symbol. MIMO detector 256 may obtain the received symbols from modem 254, perform MIMO detection on the received symbols where applicable, and provide the detected symbols. Receiver processor 258 may process (e.g., demodulate and decode) the detected symbols, provide the decoded data for UE 120 to data sink 260, and provide the decoded control information and system information to controller / processor 280. The term "controller / processor" may refer to one or more controllers, one or more processors, or a combination thereof. The channel processor can determine RSRP parameters, Received Signal Strength Indicator (RSSI) parameters, Reference Signal Received Quality (RSRQ) parameters, and / or CQI parameters, etc. In some examples, one or more components of the UE 120 may be included in the housing 284.

[0070] Network controller 130 may include communication unit 294, controller / processor 290, and memory 292. Network controller 130 may include one or more devices, for example, in a core network. Network controller 130 may communicate with network node 110 via communication unit 294.

[0071] One or more antennas (e.g., antennas 234a to 234t and / or antennas 252a to 252r) may include one or more antenna panels, one or more antenna groups, one or more sets of antenna elements and / or one or more antenna arrays, etc., or may be included within one or more antenna panels, one or more antenna groups, one or more sets of antenna elements and / or one or more antenna arrays, etc. Antenna panels, antenna groups, sets of antenna elements and / or antenna arrays may include one or more antenna elements (within a single housing or multiple housings), a set of coplanar antenna elements, a set of non-coplanar antenna elements and / or coupled to one or more transmitting and / or receiving components (such as...). Figure 2 One or more antenna elements (one or more components in a )

[0072] On the uplink, at UE 120, the transmit processor 264 can receive and process data from data source 262 and control information from controller / processor 280 (e.g., for reporting including RSRP, RSSI, RSRQ, and / or CQI). The transmit processor 264 can generate reference symbols for one or more reference signals. The symbols from the transmit processor 264 can be pre-decoded by the TX MIMO processor 266, where applicable, further processed by the modem 254 (e.g., for DFT-s-OFDM or CP-OFDM), and transmitted to network node 110. In some examples, the modem 254 of UE 120 may include a modulator and demodulator. In some examples, UE 120 includes a transceiver. This transceiver may include any combination of antenna 252, modem 254, MIMO detector 256, receive processor 258, transmit processor 264, and / or TX MIMO processor 266. The transceiver may be used by a processor (e.g., controller / processor 280) and memory 282 to perform aspects of any of the methods described herein.

[0073] At network node 110, uplink signals from UE 120 and / or other UEs may be received by antenna 234, processed by modem 232 (e.g., demodulator component of modem 232 (shown as DEMOD)), detected by MIMO detector 236, and further processed by receiver processor 238 to obtain decoded data and control information transmitted by UE 120. Receiver processor 238 may provide the decoded data to data sink 239 and the decoded control information to controller / processor 240. Network node 110 may include communication unit 244 and may communicate with network controller 130 via communication unit 244. Network node 110 may include scheduler 246 to schedule one or more UEs 120 for downlink and / or uplink communication. In some examples, modem 232 of network node 110 may include modulator and demodulator. In some examples, network node 110 includes transceiver. The transceiver may include any combination of antenna 234, modem 232, MIMO detector 236, receive processor 238, transmit processor 220 and / or TX MIMO processor 230. The transceiver may be used by a processor (e.g., controller / processor 240) and memory 242 to perform aspects of any of the methods described herein.

[0074] The controller / processor 240 of network node 110, the controller / processor 280 of UE 120 and / or Figure 2 Any other component may perform one or more technologies associated with the identification model ID or pairing ID, as described in more detail elsewhere herein. For example, the controller / processor 240 of network node 110, the controller / processor 280 of UE 120, and / or Figure 2 Any other component that can execute or direct, for example Figure 9 The process 900 Figure 10 Process 1000 Figure 11 Process 1100 Figure 12 The operation of process 1200 and / or other processes as described herein. Memory 242 and memory 282 may store data and program code for network node 110 and UE 120, respectively. In some examples, memory 242 and / or memory 282 may include a non-transitory computer-readable medium storing one or more instructions (e.g., code and / or program code) for wireless communication. For example, the one or more instructions may cause the one or more processors, UE 120 and / or network node 110 to perform or direct, for example, when executed by one or more processors of network node 110 and / or UE 120 (e.g., direct execution, or execution after compilation, transformation and / or interpretation). Figure 9 The process 900 Figure 10 Process 1000 Figure 11 Process 1100 Figure 12 The operation of process 1200 and / or other processes as described herein. In some examples, the execution instructions may include run instructions, transform instructions, compile instructions and / or interpret instructions, etc.

[0075] In some aspects, the UE (e.g., UE 120) includes: components for receiving PSS and SSS; components for identifying a MIB carried by the PBCH based at least in part on the PSS and SSS; components for identifying a physical cell ID based at least in part on one or more of the PSS or SSS; components for identifying an SSB index based at least in part on scrambling of the PBCH; and / or components for identifying a model ID associated with an ML model or a pair ID associated with an ML model pair based at least in part on the SSB index or the physical cell ID.

[0076] In some aspects, the UE includes: components for receiving a request for location information of the UE; components for transmitting the location information of the UE; and / or components for receiving a pairing ID associated with an ML model pair. Components for the UE to perform the operations described herein may include, for example, one or more of the following: a communication manager 140, an antenna 252, a modem 254, a MIMO detector 256, a receive processor 258, a transmit processor 264, a TX MIMO processor 266, a controller / processor 280, or a memory 282.

[0077] In some aspects, a network entity (e.g., network node 110) includes: components for transmitting one or more SSBs, each SSB including a PSS, an SSS, and a PBCH carrying a MIB, each SSB associated with an SSB index and a physical cell ID; components for transmitting one or more model IDs or one or more pair IDs in system information associated with the SSB index and the physical cell ID, each of the one or more model IDs being associated with an ML model, and each of the one or more pair IDs being associated with an ML model pair; and / or components for identifying a model ID from one or more model IDs or a pair ID from one or more pair IDs, at least in part based on one or more of the SSB index or the physical cell ID. In some aspects, components for the network entity to perform the operations described herein may include, for example, one or more of a communication manager 150, a transmit processor 220, a TX MIMO processor 230, a modem 232, an antenna 234, a MIMO detector 236, a receive processor 238, a controller / processor 240, a memory 242, or a scheduler 246.

[0078] In some aspects, the first network entity (e.g., network node 110) includes: components for selecting a pairing ID associated with an ML model pair that encodes and decodes CSI feedback, at least in part based on the UE's location information; and / or components for transmitting the pairing ID to the UE or one or more of the second network entities. In some aspects, components for the first network entity to perform the operations described herein may include, for example, one or more of the following: a communication manager 150, a transmit processor 220, a TX MIMO processor 230, a modem 232, an antenna 234, a MIMO detector 236, a receive processor 238, a controller / processor 240, a memory 242, or a scheduler 246.

[0079] Although Figure 2 The boxes in the diagram are illustrated as different components, but the functions described above with respect to these boxes may be implemented in a single hardware, software, or combined component, or in various combinations of components. For example, the functions described with respect to transmit processor 264, receive processor 258, and / or TX MIMO processor 266 may be performed by or under the control of controller / processor 280.

[0080] In some respects, a single processor can perform all the functions described as being performed by that one or more processors. In other respects, the one or more processors can jointly perform a set of functions. For example, a first group(s) of the one or more processors can perform a first function described as being performed by that one or more processors, and a second group(s) of the one or more processors can perform a second function described as being performed by that one or more processors. The first group and the second group of processors can be the same group of processors or can be different groups of processors. The reference to "one or more processors" should be understood as referring to a combination of functions. Figure 2 Any one or more processors described. The reference to "one or more memories" should be understood to refer to any one or more memories of the corresponding device, such as those in conjunction with... Figure 2 The memory described. For example, a function described as being performed by one or more memories can be performed by the same subset of the one or more memories or by different subsets of the one or more memories.

[0081] As indicated above, Figure 2 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 2 The examples described are different.

[0082] Communication systems (such as 5G NR systems) can be deployed in various ways with a variety of components or parts. In a 5G NR system or network, network nodes, network entities, network mobility elements, RAN nodes, core network nodes, network elements, base stations, or network equipment can be implemented in either a converged or decomposed architecture. For example, a base station (such as a Node B (NB), evolved NB (eNB), NR base station, 5G NB, access point (AP), TRP, or cell, etc.) or one or more units (or components) performing base station functionality can be implemented as a converged base station (also known as a standalone base station or monolithic base station) or a decomposed base station. A "network entity" or "network node" can refer to a decomposed base station or one or more units of a decomposed base station (such as one or more CUs, one or more DUs, one or more RUs, or combinations thereof).

[0083] Aggregated base stations (e.g., aggregated network nodes) can be configured to utilize a radio protocol stack that is physically or logically integrated within a single RAN node (e.g., within a single device or cell). Decomposed base stations (e.g., decomposed network nodes) can be configured to utilize a protocol stack that is physically or logically distributed across two or more cells (such as one or more CUs, one or more DUs, or one or more RUs). In some examples, the CU may be implemented within a network node, and one or more DUs may be co-located with the CU, or alternatively, may be geographically or virtually distributed across one or more other network nodes. DUs may be implemented to communicate with one or more RUs. Each of the CU, DU, and RU may also be implemented as a virtual cell, such as a Virtual Central Unit (VCU), a Virtual Distributed Unit (VDU), or a Virtual Radio Unit (VRU), etc.

[0084] Base station type operation or network design can take into account the aggregation characteristics of base station functionality. For example, decomposed base stations can be utilized in IAB networks, Open Radio Access Networks (O-RAN (such as network configurations initiated by the O-RAN Alliance)), or Virtualized Radio Access Networks (vRAN, also known as Cloud Radio Access Networks (C-RAN)) to facilitate the scaling of communication systems by separating base station functionality into one or more units that can be deployed independently. Decomposed base stations can include functionality implemented across two or more units at various physical locations, as well as functionality virtually implemented for at least one unit, which enables flexibility in network design. Each unit of a decomposed base station can be configured for wired or wireless communication with at least one other unit of the decomposed base station.

[0085] Figure 3This is an illustration of an example disaggregated base station architecture 300 according to this disclosure. The disaggregated base station architecture 300 may include a CU 310 that can communicate directly with the core network 320 via a backhaul link, or indirectly with the core network 320 via one or more disaggregated control units (such as a near-RT RIC 325 via an E2 link, or a non-RT RIC 315 associated with a Service Management and Orchestration (SMO) framework 305, or both). The CU 310 may communicate with one or more DUs 330 via a corresponding midhaul link (such as via an F1 interface). Each DU 330 may communicate with one or more RUs 340 via a corresponding fronthaul link. Each RU 340 may communicate with one or more UEs 120 via a corresponding radio frequency (RF) access link. In some implementations, a UE 120 may be served simultaneously by multiple RUs 340.

[0086] Each of these units (including CU 310, DU 330, RU 340) and the near-RT RIC 325, non-RT RIC 315, and SMO frame 305 may include or be coupled to one or more interfaces configured to receive or transmit signals, data, or information (collectively, signals) via wired or wireless transmission media. Each of these units, or an associated processor or controller providing instructions to one or more communication interfaces of the respective unit, may be configured to communicate with one or more units in other units via transmission media. In some examples, each unit may include a wired interface and a wireless interface configured to receive signals via a wired transmission media or transmit signals to one or more units in other units, and the wireless interface may include a receiver, transmitter, or transceiver (such as an RF transceiver) configured to receive signals via a wireless transmission media or transmit signals to one or more units in other units, or both.

[0087] In some aspects, the CU 310 can host one or more higher-level control functions. Such control functions may include RRC functions, Packet Data Convergence Protocol (PDCP) functions, or Service Data Adaptation Protocol (SDAP) functions, etc. Each control function can be implemented using an interface configured to signal to other control functions hosted by the CU 310. The CU 310 can be configured to handle user plane functions (e.g., Central Unit-User Plane (CU-UP) functions), control plane functions (e.g., Central Unit-Control Plane (CU-CP) functions), or combinations thereof. In some implementations, the CU 310 can be logically split into one or more CU-UP units and one or more CU-CP units. When implemented in an O-RAN configuration, the CU-UP units can communicate bidirectionally with the CU-CP units via an interface such as an E1 interface. The CU 310 can be implemented to communicate with the DU330 for network control and signaling purposes, as needed.

[0088] Each DU 330 may correspond to a logical unit comprising one or more base station functions for controlling the operation of one or more RU 340s. In some aspects, the DU 330 may, at least in part, host one or more of the Radio Link Control (RLC) layer, Medium Access Control (MAC) layer, and one or more high physical (PHY) layers, depending on functional splits (such as those defined by 3GPP). In some aspects, the one or more high PHY layers may be implemented by one or more modules for forward error correction (FEC) encoding and decoding, scrambling, and modulation and demodulation, etc. In some aspects, the DU 330 may also host one or more low PHY layers, such as those implemented by one or more modules for Fast Fourier Transform (FFT), Inverse FFT (iFFT), Digital Beamforming, or Physical Random Access Channel (PRACH) extraction and filtering, etc. Each layer (which may also be referred to as a module) may be implemented using an interface configured to communicate signals with other layers (and modules) hosted by the DU 330 or with control functions hosted by the CU 310.

[0089] Each RU 340 can implement lower-layer functionality. In some deployments, the RU 340 controlled by the DU 330 can correspond to a logical node that hosts RF processing functions or low-PHY layer functions, such as performing FFT, performing iFFT, digital beamforming, or PRACH extraction and filtering, based on function splitting (e.g., function splitting defined by 3GPP) (such as lower-layer function splitting). In such architectures, each RU 340 can be operated to handle over-the-air (OTA) communications with one or more UE 120s. In some specific implementations, the real-time and non-real-time aspects of communication with the control plane and user plane of the RU 340 can be controlled by the corresponding DU 330. In some scenarios, this configuration allows each DU 330 and CU 310 to be implemented in a cloud-based RAN architecture, such as a vRAN architecture.

[0090] SMO framework 305 can be configured to support RAN deployment and provisioning of both non-virtualized and virtualized network elements. For non-virtualized network elements, SMO framework 305 can be configured to support the deployment of dedicated physical resources for RAN coverage requirements, which can be managed via operation and maintenance interfaces such as the O1 interface. For virtualized network elements, SMO framework 305 can be configured to interact with cloud computing platforms such as the Open Cloud (O-Cloud) platform 390 to perform network element lifecycle management (such as instantiating virtualized network elements) via cloud computing platform interfaces such as the O2 interface. Such virtualized network elements may include, but are not limited to, CU 310, DU 330, RU 340, non-RT RIC 315, and near-RT RIC 325. In some specific implementations, SMO framework 305 may communicate with the hardware aspects of the 4G RAN (such as the Open eNB (O-eNB) 311) via the O1 interface. Additionally, in some implementations, the SMO framework 305 can communicate directly with each of one or more RUs 340 via a corresponding O1 interface. The SMO framework 305 may also include a non-RT RIC 315 configured to support the functionality of the SMO framework 305.

[0091] The non-RT RIC 315 can be configured to include logical functions that enable non-real-time control and optimization of RAN elements and resources, including artificial intelligence / machine learning (AI / ML) workflows for model training and updates, or policy-based guidance for applications / features in the near-RT RIC 325. The non-RT RIC 315 can be coupled to or communicate with the near-RT RIC 325, such as via an A1 interface. The near-RT RIC 325 can be configured to include logical functions that enable near real-time control and optimization of RAN elements and resources via an interface, such as an E2 interface, through data collection and actions, connecting one or more CU 310s, one or more DU 330s, or both, and O-eNBs to the near-RT RIC 325.

[0092] In some implementations, to generate AI / ML models to be deployed in the near-RT RIC 325, the non-RT RIC 315 may receive parameters or external enrichment information from an external server. This information can be utilized by the near-RT RIC 325 and can be received from non-network data sources or network functions at the SMO framework 305 or the non-RT RIC 315. In some examples, the non-RT RIC 315 or the near-RT RIC 325 may be configured to tune RAN behavior or performance. For example, the non-RT RIC 315 may monitor long-term trends and patterns in performance and employ AI / ML models to perform corrective actions via the SMO framework 305 (such as reconfiguration via the O1 interface) or via the creation of RAN management policies (such as A1 interface policies).

[0093] As indicated above, Figure 3 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 3 The examples described are different.

[0094] Figure 4 This is a diagram illustrating example 400 of encoding and decoding CSI according to this disclosure.

[0095] CSI-RS can be configured to be sent from a network entity (e.g., a base station) to the UE. CSI-RS can be configured to be periodic (e.g., using RRC signaling), semi-persistent (e.g., using MAC control element (MAC CE) signaling), and / or aperiodic (e.g., using downlink control information (DCI)).

[0096] The UE can measure CSI-RS and send CSI reports indicating CSI, such as PMI. PMI is a matrix indicating how data is transmitted at the antenna port of a network entity. CSI reports may include codebooks, which are collections of one or more pre-decoders or one or more PMIs. The UE can use a sequence of bits to report PMIs. Type I codebooks may include predefined matrices. Type II codebooks may include more detailed CSI reports for multi-user MIMO. CSI acquisition can be enhanced by coherent joint transmission (CJT) for multiple TRPs (e.g., up to four TRPs). This may involve enhanced Type II codebooks (eType-II codebooks). Network entities can use RRC signaling (e.g., CSI-ReportConfig The RRC signaling is used to configure CSI reports, which includes carrier ID, report time type, channel measurement resources (CMR), interference measurement resources (IMR), report quantity, frequency configuration (subband), and / or codebook configuration.

[0097] In some examples, ML-based CSI feedback (including AI-based CSI feedback) can replace the codebook with an ML-based CSI encoder and decoder. In some examples, the encoder may resemble a PMI search algorithm, and the decoder may resemble a PMI codebook used to convert CSI report bits into PMI codewords. Using ML, CSI can be encoded (e.g., compressed) at the UE and decoded (e.g., reconstructed) at the network entity. In such cross-node ML, the neural network can be split into two parts, where the first part includes the encoder for the UE, and the second part includes the decoder for the network entity. The encoder output of the UE is sent to the network entity as input to the decoder.

[0098] For example, such as Figure 4 As shown in Example 400, encoder 402 at the UE may input a CSI (e.g., downlink channel estimation 404) and output a compressed CSI or another data signal (potential message 406), which is received as input at decoder 408 of the network entity. Potential message 406 may be a message between encoder 402 and decoder 408 with encoded or compressed CSI feedback, and may be unstructured or structured. An unstructured potential message may be a series of bits with a payload that is explicitly configured or derived based on the number of ports, the number of subbands, and / or the rank. Decoder 408 at the network entity may output a reconstructed CSI (e.g., reconstructed downlink channel estimation 410) or another data signal, such as a pre-decoded vector. Encoder input 412 may include a downlink channel matrix. H Downlink pre-decoder V Or interference covariance matrix R nnThe decoder output 414 may include the downlink channel matrix. H Transmit covariance matrix, downlink pre-decoder V Interference covariance matrix R nn The original channel or the whitened channel (e.g., whitened by a demodulation filter).

[0099] In multi-vendor training, each vendor (e.g., UE vendor, network entity vendor) can be associated with a corresponding server participating in offline training. The UE vendor server can communicate with the network entity vendor server (e.g., base station (BS) server) during training using a server-to-server connection. The UE vendor server can also be referred to as the network entity associated with the UE or the UE server.

[0100] In some examples, to evaluate ML-based CSI compression use cases, one or more different types of quantization or dequantization methods, such as vector quantization or scalar quantization, can be used. In CSI compression using two-sided model use cases, multiple ML models can be trained. In some instances, two-sided models can be jointly trained at a single side / entity (e.g., the UE side or the network side). In some instances, two-sided models can be jointly trained at the network side and the UE side separately. In some instances, models can be trained separately at the network side and the UE side, where the UE-side CSI generation part and the network-side CSI reconstruction part are trained by the UE side and the network side, respectively. "Joint training" can refer to training the generation model and the reconstruction model for forward and backward propagation in the same loop. Joint training can be done at a single node or across multiple nodes (e.g., through gradient exchange between nodes). Individual training can include sequential training starting from the UE side, or sequential training starting from the network side, or parallel training at the UE and the network.

[0101] As indicated above, Figure 4 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 4 The examples described are different.

[0102] Figure 5 This is an example diagram 500 illustrating the use of the ML model according to this disclosure.

[0103] In some examples, the ML model (e.g., ML model 502, ML model 504, ML model 506 in example 500) may be AI / ML functionality-based (Scheme 508) or AI / ML model-based (Scheme 510). For Scheme 508, which includes an AI / ML functionality identifier for a UE portion having a UE-side model and / or dual-side models, and functionality-based lifecycle management (LCM), functionality may refer to an AI / ML-enabled feature or feature group (FG) enabled by configuration, wherein the configuration is supported at least in part based on conditions indicated by UE capabilities. Correspondingly, the functionality-based LCM operates at least based on a configuration of an AI / ML-enabled feature / FG or a specific configuration of an AI / ML-enabled feature / FG. Network entities may send messages (e.g., DCI, MAC CE) to activate or deactivate the configuration or to activate or deactivate the AI / ML functionality-based ML model.

[0104] In some examples, for the AI / ML model identifier and model ID-based LCM of the UE portion of the UE-side model and / or dual-side model, the model ID-based LCM may operate at least partially based on the identified model, wherein the model may be associated with specific configurations or conditions related to the UE capabilities of the AI / ML-enabled feature / FG and additional conditions (e.g., scenario, site, and dataset) determined or identified between the UE side and the network side. Network entities may send messages (e.g., DCI, MAC CE) to activate or deactivate the configuration or the AI / ML-based ML model.

[0105] In some examples, multiple model pairs used for encoding and decoding can be identified during the model identification phase or offline at the network side. The functionality of these model pairs can be identified during the model identification phase (with model descriptions) or using UE capability signaling. Additional signaling can be used to indicate the scenarios or locations each model pair is designed for. Signaling can also indicate the dynamic conditions of each model pair (e.g., the model pair is designed for a certain condition, and once the condition changes, the model pair is no longer available or some functionality of the model is disabled). In some examples, ML models and ML model pairs can be explicitly indicated via RRC signaling.

[0106] As indicated above, Figure 5 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 5 The examples described are different.

[0107] Figure 6A and Figure 6B This is a diagram illustrating example 600 of an identifier ML model according to this disclosure. For example... Figure 6AAs shown, network entity 610 (e.g., network node 110) and UE 620 (e.g., UE 120) can communicate with each other via a wireless network (e.g., wireless network 100).

[0108] According to the various aspects described herein, the UE may implicitly identify ML models and / or ML model pairs. The UE may identify the model ID of an ML model or the pair ID of an ML model pair at least in part based on the scenario, UE location, or dynamic conditions. The UE may identify the model ID or pair ID at least in part based on the SSB index and / or physical cell ID. By identifying the ML model at least in part based on the SSB index and / or physical cell ID, the UE can use an appropriate ML model to encode or compress UE information (e.g., CSI feedback), and network entities can use the paired ML models to reconstruct the CSI from the compressed information. In some aspects, by identifying the ML model at least in part based on the SSB index and / or physical cell ID, the UE can use an appropriate ML model to predict CSI or beams. Prediction may include predicting a narrow beam from a wider beam or predicting a beam for future time instances. Network entities can use accurate information to schedule and configure the UE for improved communication. By utilizing ML model selection to improve communication, latency is reduced and signaling resources are saved. Furthermore, network entities can save signaling resources by not explicitly sending model IDs or pairing IDs.

[0109] Figure 6A Example 600 illustrates that network entity 610 can transmit an SSB 602 associated with SSB index 604. SSB 602 may include PBCH 606, PSS 608, and SSS 610. SSB index 604 may be associated with a specific beam or area. SSBs can be anticipated within a 5-millisecond (ms) window, within which, for example, 4 SSBs (for frequencies equal to or less than 3 GHz), 8 SSBs (for frequencies less than 6 GHz), and up to 64 SSBs (for frequencies up to 52.6 GHz) may exist.

[0110] In some aspects, UE 620 may receive SSB 602 and detect PSS 608 and SSS 610. UE 620 may identify the SSB index 604 of SSB 602 based at least in part on scrambling 614 of PBCH 606. PBCH is a physical channel carrying MIB 612, which includes the content transmitted by MIB 612. UE 620 may also detect timing or frequency synchronization. MIB 612 may include information from the physical downlink control channel (PDCCH) from network entity 610, which schedules a physical downlink shared channel including Residual Minimum System Information (RMSI) 642 or other system information (OSI) 644. UE 620 may detect system information used by UE 620 to perform the Random Access Channel (RACH) procedure. RMSI 642 may include or indicate a System Information Block (SIB) that enables access to the cell. In some aspects, MIB 612 may indicate one or more model IDs 616 and / or a list of pairing IDs 618 (of one or more pairing IDs). In some aspects, UE 620 may receive explicit indication of model ID 630 or pairing ID 634 in RMSI 642 or OSI 644.

[0111] In some respects, UE 620 may identify physical cell ID 622 based at least in part on PSS 608 and SSS 610. More specifically, physical cell ID 1 is based at least in part on PSS, physical cell ID 2 is based at least in part on SSS, and physical cell ID 3 is equal to 3 * physical cell ID 1 + physical cell ID 2. In some respects, model ID or pairing ID may be based at least in part on physical cell ID. Physical cell ID 622 may be physical cell ID 1 based at least in part on PSS 608, physical cell ID 2 based at least in part on SSS 610, or a final ID (such as physical cell ID 3).

[0112] In some aspects, such as Figure 6BAs shown in the continuation of Example 600, UE 620 may identify Model ID 630 at least in part based on SSB index 604, Physical Cell ID 622, or a combination of SSB index 604 and Physical Cell ID 622. UE 620 may identify Model ID 630 at least in part based on mapping 628 between SSB index 604 and Model ID 630. Mapping 628 may be in stored configuration information (as defined in the standard) and / or received in RRC signaling. Model ID 630 may be associated with ML model 632. ML model 632 may be used for CSI prediction. ML model 632 may be used for beam prediction. UE 620 may use ML model 632 to predict beam 642, which may be a narrow beam from a wider beam or a beam for future time instances. In some respects, UE 620 may identify pair ID 634 at least in part based on SSB index 604, physical cell ID 622, or a combination of SSB index 604 and physical cell ID 622. UE 620 may identify pair ID 634 at least in part based on mapping 628 between SSB index 604 and pair ID 634. Pair ID 634 may be associated with ML model pair 636 (ML model 638 and ML model 640). ML model 638 can be used for encoding or compression, and ML model 640 can be used for decoding encoded content or reconstructing compressed content, such as CSI feedback.

[0113] As indicated above, Figure 6A and Figure 6B Examples are provided. Other examples can be found in relation to [the relevant information]. Figure 6A and Figure 6B The examples described are different.

[0114] Figure 7 This is an illustration of example 700 associated with the use of an ML model according to this disclosure.

[0115] Example 700 illustrates an example of signaling associated with the identifiers of the model ID and pairing ID described in conjunction with Example 600 of Figure 6. As indicated by reference numeral 705, network entity 610 may send an SSB 602 including PBCH 606, PSS 608, and SSS 610. In some aspects, as indicated by reference numeral 710, network entity 610 may send RMSI 642 and / or OSI 644.

[0116] As indicated by reference numeral 715, UE 620 may identify MIB 612 in PBCH 606 ​​at least in part based on PSS 608 and SSS 610. As indicated by reference numeral 720, UE 620 may identify Physical Cell ID 622 at least in part based on PSS 608 and / or SSS 610. As indicated by reference numeral 725, UE 620 may identify SSB index 604 at least in part based on scrambling 614 of PBCH 606. As indicated by reference numeral 730, UE 620 may identify Model ID 630 or Pair ID 634 at least in part based on SSB index 604 and / or Physical Cell ID 622.

[0117] As shown by reference numeral 735, UE 620 may encode CSI feedback 726 using ML model 632 associated with model ID 630 or ML model pair 636 associated with pairing ID 634 to obtain encoded CSI feedback 728. Although CSI feedback is encoded in Example 700, other information may be encoded or compressed. As shown by reference numeral 740, UE 620 may send encoded CSI feedback 728. As shown by reference numeral 745, network entity 610 may decode encoded CSI feedback 728 (using the ML model in ML model pair 636).

[0118] As indicated above, Figure 7 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 7 The examples described are different.

[0119] Figure 8 This is a diagram illustrating an example 800 associated with the use of an ML model according to this disclosure. For example... Figure 8 As shown, a first network entity 810 (e.g., network node 110) and a UE 820 (e.g., UE 120) can communicate with each other via a wireless network (e.g., wireless network 100). The first network entity 810 and / or UE 820 can communicate with a second network entity (e.g., network node 110) (such as location and management function (LMF) 830).

[0120] In some aspects, network entities may select pairing IDs for ML model pairs. Network entities may select pairing IDs based at least in part on the location information of the UE. Network entities may send the pairing IDs to the UE or another network entity. In some aspects, network entities may select pairing IDs based at least in part on a model pair description that describes the ML model pair associated with the pairing ID. This at least in part based on may include being associated with or related to... The model pair description may describe scene information and / or location information for each ML model pair.

[0121] Network entities may further select pair IDs based, at least in part, on meta-information associated with the model pair description. Meta-information may include the dataset on which the model was trained. Meta-information may include the CSI-RS index used by the UE for downlink measurements and to generate a baseline truth CSI. Meta-information may include timestamps, signal-to-noise ratio (SNR) of the downlink measurements, and / or channel statistics for the measurements in terms of delay spread or Doppler. The model pair description and meta-information may be provided during the model identification phase.

[0122] Example 800 illustrates an example of selecting a pairing ID. As indicated by reference numeral 835, LMF 830 may send a request for UE location information. As indicated by reference numeral 840, UE 820 may send location information 836 to LMF 830. As indicated by reference numeral 845, LMF 830 may send location information 836 to network entity 810. In some aspects, network entity 810 may request and receive location information 836 from UE 820.

[0123] As indicated by reference numeral 850, network entity 810 may select pair ID 852 based at least in part on location information 836. UE location information 836 may be mapped to pair ID 852. Network entity 810 may further select pair ID 852 based at least in part on model pair description 856 and / or meta-information 858.

[0124] As indicated by reference numeral 855, network entity 810 may send pairing ID 852. As indicated by reference numeral 860, UE 820 may use the ML model pair associated with pairing ID 852 to encode CSI feedback 862 to obtain encoded CSI feedback 864. Although CSI feedback is encoded in Example 800, other information may be encoded or compressed.

[0125] In some respects, UE 820 may send encoded CSI feedback 864. Network entity 810 may use an ML model pair to decode the encoded CSI feedback 864. In some respects, LMF 830 or other entities may indicate pairing ID 852 to first network entity 810 or UE 820.

[0126] As indicated above, Figure 8 This is provided as an example. Other examples are available with reference to [the relevant information]. Figure 8 The examples described are different.

[0127] Figure 9 This is a diagram illustrating an example process 900 performed, for example, at a UE or a device of a UE, according to this disclosure. Example process 900 is an example in which the device or the UE (e.g., UE 620) performs operations associated with identifying an ML model.

[0128] like Figure 9 As shown, in some aspects, process 900 may include receiving PSS and SSS (block 910). For example, the UE (e.g., using...) Figure 13 The communication manager 140 and / or receiving component 1302 depicted can receive PSS and SSS, as described above.

[0129] like Figure 9 As further shown, in some aspects, process 900 may include identifying the MIB carried by the PBCH based at least in part on the PSS and SSS, and identifying the Physical Cell ID based at least in part on one or more of the PSS or SSS (box 920). For example, the UE (e.g., using...) Figure 13 The described communication manager 140 and / or identification component 1308 may identify the MIB carried by the PBCH based at least in part on the PSS and SSS, and identify the physical cell ID based at least in part on one or more of the PSS or SSS, as described above.

[0130] like Figure 9 As further shown, in some aspects, process 900 may include identifying the SSB index at least in part based on scrambling of the PBCH (box 930). For example, the UE (e.g., using...) Figure 13 The communication manager 140 and / or identification component 1308 depicted may identify the SSB index at least in part based on scrambling of the PBCH, as described above.

[0131] like Figure 9 As further shown, in some aspects, process 900 may include identifying a model ID associated with an ML model or a pair ID associated with an ML model pair based at least in part on an SSB index or physical cell ID (box 940). For example, a UE (e.g., using...) Figure 13 The described communication manager 140 and / or identification component 1308 may identify the model ID associated with the ML model or the pair ID associated with the ML model pair based at least in part on the SSB index or physical cell ID, as described above.

[0132] Process 900 may include additional aspects, such as any single aspect or any combination of aspects described below and / or in conjunction with one or more other processes described elsewhere herein.

[0133] In the first aspect, the ML model is associated with encoding or decoding CSI feedback, and the ML model is associated with both encoding and decoding CSI feedback.

[0134] In a second aspect, either alone or in combination with the first aspect, process 900 includes encoding CSI feedback using an ML model associated with a model ID or using an ML model in a pair of ML models associated with a pair ID, and sending the encoded CSI feedback.

[0135] In the third aspect, either alone or in combination with one or more of the first and second aspects, the MIB indicates one or more model IDs, and identifying a model ID includes identifying the model ID from one or more model IDs based at least in part on a mapping between the model ID and one or more of the SSB index or physical cell ID.

[0136] In the fourth aspect, either alone or in combination with one or more of the first to third aspects, the MIB indicates a list of one or more pairing IDs, and identifying a pairing ID includes identifying the pairing ID from the list of one or more pairing IDs based at least in part on a mapping between the pairing ID and one or more of the SSB index or physical cell ID.

[0137] In the fifth aspect, either alone or in combination with one or more of the first to fourth aspects, identifying the model ID includes further identifying the model ID based at least in part on RMSI or OSI.

[0138] In the sixth aspect, either alone or in combination with one or more of the first to fifth aspects, identifying the pair ID includes further identifying the pair ID based at least in part on RMSI or OSI.

[0139] although Figure 9 An example box of process 900 is shown, but in some respects, process 900 may include... Figure 9 The boxes depicted may be fewer, different, or arranged differently compared to additional boxes. Alternatively, two or more boxes in the process 900 may be executed in parallel.

[0140] Figure 10 This is a diagram illustrating an example process 1000 performed, for example, at a network entity or a device of a network entity, according to the present disclosure. Example process 1000 is an example in which the device or the network entity (e.g., network entity 610) performs operations associated with identifying an ML model.

[0141] like Figure 10 As shown, in some aspects, process 1000 may include sending one or more SSBs, each SSB including a PSS, an SSS, and a PBCH carrying a MIB, each SSB being associated with an SSB index and a physical cell ID (box 1010). For example, network entities (e.g., using...) Figure 16The described communication manager 1606 and / or transmitting component 1604 can transmit one or more SSBs, each SSB including a PSS, an SSS, and a PBCH carrying a MIB, each SSB being associated with an SSB index and a physical cell ID, as described above.

[0142] like Figure 10 Further shown, in some aspects, process 1000 may include sending one or more model IDs or one or more pair IDs in system information associated with the SSB index and physical cell ID, each of the one or more model IDs being associated with an ML model, and each of the one or more pair IDs being associated with an ML model pair (box 1020). For example, network entities (e.g., using...) Figure 16 The described communication manager 1606 and / or transmitting component 1604 may transmit one or more model IDs or one or more pair IDs in system information associated with the SSB index and physical cell ID, each of the one or more model IDs being associated with an ML model, and each of the one or more pair IDs being associated with an ML model pair, as described above.

[0143] like Figure 10 As further shown, in some aspects, process 1000 may include identifying a model ID from one or more model IDs or identifying a pair ID from one or more pair IDs, at least in part, based on one or more of the SSB index or physical cell ID (box 1030). For example, network entities (e.g., using...) Figure 16 The described communication manager 1606 and / or identification component 1608 can identify a model ID from one or more model IDs or a pair ID from one or more pair IDs, at least in part, based on one or more of the SSB index or physical cell ID, as described above.

[0144] Process 1000 may include additional aspects, such as any single aspect or any combination of aspects described below and / or in conjunction with one or more other processes described elsewhere herein.

[0145] In a first aspect, process 1000 includes receiving encoded CSI feedback and decoding the encoded CSI feedback using an ML model associated with decoding the CSI feedback associated with a model ID or pair ID.

[0146] In the second aspect, sending one or more model IDs, either alone or in combination with the first aspect, includes sending one or more model IDs in the MIB.

[0147] In a third aspect, either alone or in combination with one or more of the first and second aspects, process 1000 includes obtaining a mapping between the model ID and one or more of the SSB index or physical cell ID from the configuration information.

[0148] In the fourth aspect, either alone or in combination with one or more of the first to third aspects, one or more pairing IDs are sent, including a list of pairing IDs sent in the MIB.

[0149] In the fifth aspect, either alone or in combination with one or more of the first to fourth aspects, process 1000 includes obtaining a mapping between the pairing ID and one or more of the SSB index or physical cell ID from the configuration information.

[0150] In the sixth aspect, sending one or more model IDs, either alone or in combination with one or more of the first to fifth aspects, includes sending model IDs in RMSI or OSI.

[0151] In the seventh aspect, sending one or more pairing IDs, either alone or in combination with one or more of the first to sixth aspects, includes sending pairing IDs in RMSI or OSI.

[0152] although Figure 10 An example box of process 1000 is shown, but in some respects, process 1000 may include... Figure 10 The boxes depicted may be fewer, different, or arranged differently compared to additional boxes. Alternatively, two or more boxes in the process 1000 may be executed in parallel.

[0153] Figure 11 This is a diagram illustrating an example process 1100 performed, for example, at a first network entity or a device of the first network entity, according to this disclosure. Example process 1100 is an example in which the device or the first network entity (e.g., first network entity 810) performs an operation associated with selecting a model ID.

[0154] like Figure 11 As shown, in some aspects, process 1100 may include selecting a pairing ID (box 1110) associated with an ML model pair that encodes and decodes CSI feedback, at least in part, based on the UE's location information. For example, a first network entity (e.g., using...) Figure 16 The described communication manager 1606 and / or selection component 1612 can select a pairing ID associated with the ML model pair that encodes and decodes CSI feedback, as described above, based at least in part on the UE's location information.

[0155] like Figure 11As further shown, in some aspects, process 1100 may include sending a pairing ID to one or more of the UE or the second network entities (box 1120). For example, the first network entity (e.g., using...) Figure 16 The described communication manager 1606 and / or transmitting component 1604 can transmit a pairing ID to one or more of the UE or a second network entity, as described above.

[0156] Process 1100 may include additional aspects, such as any single aspect or any combination of aspects described below and / or in conjunction with one or more other processes described elsewhere herein.

[0157] In the first aspect, process 1100 includes receiving the location information of the UE.

[0158] In the second aspect, either alone or in combination with the first aspect, selecting a pair ID includes further selecting a pair ID based at least in part on a model pair description associated with one or more of the scene information or location information for the ML model pair.

[0159] In the third aspect, either alone or in combination with one or more of the first and second aspects, selecting the pair ID includes further selecting the pair ID based at least in part on meta-information describing the model pair.

[0160] In the fourth aspect, either alone or in combination with one or more of the first to third aspects, process 1100 includes receiving a model pair description.

[0161] In the fifth aspect, either alone or in combination with one or more of the first to fourth aspects, process 1100 includes receiving encoded CSI feedback from the UE and decoding the encoded CSI feedback using an ML model associated with decoding the CSI feedback associated with the pairing ID.

[0162] although Figure 11 An example box of process 1100 is shown, but in some respects, process 1100 may include... Figure 11 The boxes depicted may be fewer, different, or arranged differently compared to additional boxes. Alternatively, two or more boxes in process 1100 may be executed in parallel.

[0163] Figure 12 This is a diagram illustrating an example process 1200 performed, for example, at a UE or a device of a UE, according to this disclosure. Example process 1200 is an example in which the device or the UE (e.g., UE 120) performs operations associated with providing location information.

[0164] like Figure 12As shown, in some aspects, process 1200 may include receiving a request for location information of the UE (block 1210). For example, the UE (e.g., using...) Figure 13 The depicted communication manager 140 and / or receiving component 1302 can receive requests for the location information of the UE, as described above.

[0165] like Figure 12 As further shown, in some aspects, process 1200 may include sending the location information of the UE (box 1220). For example, the UE (e.g., using...) Figure 13 The depicted communication manager 140 and / or transmitting component 1304 can transmit the UE's location information as described above.

[0166] like Figure 12 As further shown, in some aspects, process 1200 may include receiving a pairing ID associated with the ML model pair (box 1230). For example, the UE (e.g., using...) Figure 13 The depicted communication manager 140 and / or receiving component 1302 can receive the pairing ID associated with the ML model pair, as described above.

[0167] Process 1200 may include additional aspects, such as any single aspect or any combination of aspects described below and / or in conjunction with one or more other processes described elsewhere herein.

[0168] In a first aspect, process 1200 includes encoding the CSI feedback using an ML model associated with encoding the CSI feedback related to the pairing ID, and sending the encoded CSI feedback.

[0169] although Figure 12 An example box of process 1200 is shown, but in some respects, process 1200 may include... Figure 12 The boxes depicted may be fewer, different, or arranged differently compared to additional boxes. Alternatively, two or more boxes in process 1200 may be executed in parallel.

[0170] Figure 13This is a diagram of an example device 1300 for wireless communication according to the present disclosure. Device 1300 may be a UE (e.g., UE 120, UE 620, UE 820), or a UE may include device 1300. In some aspects, device 1300 includes a receiving component 1302 and a transmitting component 1304, which can communicate with each other (e.g., via one or more buses and / or one or more other components). As shown, device 1300 can use the receiving component 1302 and the transmitting component 1304 to communicate with another device 1306 (such as a UE, a base station, or another wireless communication device). As further shown, device 1300 may include a communication manager 140. Communication manager 140 may include an identification component 1308 and / or an encoder component 1310, etc.

[0171] In some respects, device 1300 can be configured to perform the functions described herein. Figures 1 to 8 One or more operations described herein. Additionally or alternatively, the apparatus 1300 may be configured to perform one or more processes described herein, such as Figure 9 The process 900 Figure 12 The process 1200 or a combination thereof. In some respects, Figure 13 The illustrated device 1300 and / or one or more components may include a combination Figure 2 One or more components of the described UE. Additionally or alternatively, Figure 13 One or more components shown can be combined Figure 2 Implementation within one or more of the described components. Alternatively or concurrently, one or more components in the set of components may be implemented at least partially as software stored in one or more memories. For example, a component (or a portion thereof) may be implemented as instructions or code stored in a non-transitory computer-readable medium and executable by one or more controllers or one or more processors to perform the function or operation of the component.

[0172] Receiver 1302 may receive communications from device 1306, such as reference signals, control information, data communications, or combinations thereof. Receiver 1302 may provide the received communications to one or more other components of device 1300. In some aspects, receiver 1302 may perform signal processing on the received communications (such as filtering, amplification, demodulation, analog-to-digital conversion, demultiplexing, deinterleaving, demapping, equalization, interference cancellation, or decoding, etc.) and may provide the processed signals to one or more other components of device 1300. In some aspects, receiver 1302 may include combinations of... Figure 2The described UE includes one or more antennas, one or more modems, one or more demodulators, one or more MIMO detectors, one or more receiver processors, one or more controllers / processors, one or more memories, or combinations thereof.

[0173] Transmitting component 1304 may transmit communications, such as reference signals, control information, data communications, or combinations thereof, to device 1306. In some aspects, one or more other components of device 1300 may generate communications and provide the generated communications to transmitting component 1304 for transmission to device 1306. In some aspects, transmitting component 1304 may perform signal processing (such as filtering, amplification, modulation, digital-to-analog conversion, multiplexing, interleaving, mapping, or encoding, etc.) on the generated communications and may transmit the processed signals to device 1306. In some aspects, transmitting component 1304 may include combinations of... Figure 2 The described UE may include one or more antennas, one or more modems, one or more modulators, one or more transmit MIMO processors, one or more transmit processors, one or more controllers / processors, one or more memories, or combinations thereof. In some aspects, the transmit component 1304 may co-located with the receive component 1302 in one or more transceivers.

[0174] In some aspects, receiving component 1302 may receive PSS and SSS. Identification component 1308 may identify the MIB carried by PBCH based at least in part on PSS and SSS, and identify the physical cell ID based at least in part on one or more of PSS or SSS. Identification component 1308 may identify the SSB index based at least in part on PBCH scrambling. Identification component 1308 may identify the model ID associated with the ML model or the pair ID associated with the ML model pair based at least in part on the SSB index or physical cell ID.

[0175] In some respects, receiving component 1302 can receive requests for the location information of the UE. Transmitting component 1304 can transmit the location information of the UE. Receiving component 1302 can receive an ID associated with an ML model pair.

[0176] Encoder component 1310 can encode the CSI feedback using an ML model associated with encoding the CSI feedback related to the pairing ID. Transmitter component 1304 can transmit the encoded CSI feedback.

[0177] Figure 13 The number and arrangement of components shown are provided as an example. In reality, they can exist in... Figure 13 The components shown are compared to additional components, fewer components, different components, or components arranged in a different manner. Furthermore, Figure 13The two or more components shown can be implemented within a single component, or Figure 13 The single component shown can be implemented as multiple distributed components. Additionally or alternatively, Figure 13 The collection of (one or more) components shown is executable and described as being composed of Figure 13 Another set of components shown performs one or more functions.

[0178] Figure 14 This is an illustration of an example 1400 of a hardware implementation of a device 1405 employing a processing system 1410 according to the present disclosure. The device 1405 may be a UE or may be located at a UE (e.g., included in a UE).

[0179] Processing system 1410 may be implemented using a bus architecture generally represented by bus 1415. Bus 1415 may include any number of interconnect buses and bridges, depending on the specific application of processing system 1410 and overall design constraints. Bus 1415 links together various circuits including one or more processors and / or hardware components represented by processor 1420, illustrated components, and computer-readable medium / memory 1425. Processor 1420 may include multiple processors, such as processor 1420a, memory 1420b, and memory 1420c. Memory 1425 may include multiple memories, such as memory 1425a, memory 1425b, and memory 1425c. Bus 1415 may also link various other circuits, such as timing sources, peripherals, voltage regulators, and / or power management circuits.

[0180] Processing system 1410 may be coupled to one or more transceivers 1430. Transceiver 1430 is coupled to one or more antennas 1435. Transceiver 1430 provides components for communicating with various other devices via a transmission medium. Transceiver 1430 receives signals from one or more antennas 1435, extracts information from the received signals, and provides the extracted information to processing system 1410 (specifically, receiving component 1302). Furthermore, transceiver 1430 receives information from processing system 1410 (specifically, transmitting component 1304) and generates signals to be applied to one or more antennas 1435 based at least in part on the received information.

[0181] Processing system 1410 includes one or more processors 1420 coupled to computer-readable medium / memory 1425. Processor 1420 is responsible for general processing, including executing software stored on computer-readable medium / memory 1425. When executed by processor 1420, the software causes processing system 1410 to perform the various functions described herein with respect to any particular device. Computer-readable medium / memory 1425 can also be used to store data manipulated by processor 1420 during software execution. The processing system also includes at least one of the illustrated components. A component may be: a software module running in processor 1420, residing in / stored in computer-readable medium / memory 1425, one or more hardware modules coupled to processor 1420, or some combination thereof.

[0182] In some aspects, the processing system 1410 may be a component of the UE 120 and may include one or more memories (such as memory 282) and / or may include one or more processors (such as at least one of TX MIMO processor 266, RX processor 258, and / or controller / processor 280). In some aspects, the apparatus 1405 for wireless communication includes: components for receiving PSS and SSS; components for identifying a MIB carried by the PBCH based at least in part on the PSS and SSS; components for identifying a physical cell ID based at least in part on one or more of the PSS or SSS; components for identifying an SSB index based at least in part on scrambling of the PBCH; and components for identifying a model ID associated with an ML model or a pair ID associated with an ML model pair based at least in part on the SSB index or physical cell ID. The aforementioned components may be one or more of the aforementioned components of the processing system 1410 of apparatus 1300 and / or apparatus 1405 configured to perform the functions stated by the aforementioned components. As described elsewhere herein, the processing system 1410 may include a TX MIMO processor 266, an RX processor 258, and / or a controller / processor 280. In one configuration, the aforementioned components may be the TX MIMO processor 266, the RX processor 258, and / or the controller / processor 280 configured to perform the functions and / or operations set forth herein.

[0183] In some aspects, processing system 1410 may be a component of UE 120 and may include one or more memories (such as memory 282) and / or may include one or more processors (such as at least one of TX MIMO processor 266, RX processor 258, and / or controller / processor 280). In some aspects, apparatus 1405 for wireless communication includes: components for receiving PSS and SSS; components for selecting a pairing ID associated with an ML model pair that encodes and decodes CSI feedback, at least in part based on the UE's location information; and components for transmitting the pairing ID to one or more of the UE or a second network entity. The aforementioned components may be one or more of the aforementioned components of processing system 1410 of apparatus 1300 and / or apparatus 1405 configured to perform the functions stated by the aforementioned components. As described elsewhere herein, processing system 1410 may include TX MIMO processor 266, RX processor 258, and / or controller / processor 280. In one configuration, the aforementioned components may be a TX MIMO processor 266, an RX processor 258, and / or a controller / processor 280 configured to perform the functions and / or operations set forth herein.

[0184] Figure 14 This is provided as an example. Other examples can be combined with it. Figure 14 The examples described are different.

[0185] Figure 15 This is an illustration of an example 1500 of a specific implementation of code and circuitry for device 1505 according to the present disclosure. The circuitry may include processing circuitry and memory circuitry. Device 1505 may be a UE, or a UE may include device 1505.

[0186] like Figure 15 As shown, device 1505 may include circuitry (circuit 1520) for receiving PSS and SSS. For example, circuitry 1520 may enable device 1505 to receive PSS and SSS.

[0187] like Figure 15 As shown, device 1505 may include code (code 1525) stored in computer-readable medium 1425 for receiving PSS and SSS. For example, when executed by processor 1420, code 1525 may cause processor 1420 to cause transceiver 1430 to receive PSS and SSS.

[0188] like Figure 15As shown, device 1505 may include circuitry (circuit 1530) for identifying a MIB carried by a PBCH based at least in part on the PSS and SSS. For example, circuitry 1530 may enable device 1505 to identify a MIB carried by a PBCH based at least in part on the PSS and SSS, and to identify a physical cell ID based at least in part on one or more of the PSS or SSS.

[0189] like Figure 15 As shown, apparatus 1505 may include code (code 1535) stored in computer-readable medium 1425 for identifying a MIB carried by PBCH based at least in part on PSS and SSS. For example, when executed by processor 1420, code 1535 may enable processor 1420 to identify a MIB carried by PBCH based at least in part on PSS and SSS, and to identify a physical cell ID based at least in part on one or more of PSS or SSS.

[0190] like Figure 15 As shown, device 1505 may include circuitry (circuit 1530) for identifying SSB indices at least in part based on scrambling of the PBCH. For example, circuitry 1530 may enable device 1505 to identify SSB indices at least in part based on scrambling of the PBCH.

[0191] like Figure 15 As shown, apparatus 1505 may include code (code 1535) stored in computer-readable medium 1425 for identifying an SSB index based at least in part on scrambling of the PBCH. For example, when executed by processor 1420, code 1535 may cause processor 1420 to identify the SSB index based at least in part on scrambling of the PBCH.

[0192] like Figure 15 As shown, apparatus 1505 may include circuitry (circuit 1530) for identifying a model ID associated with an ML model or a pair ID associated with an ML model pair, based at least in part on an SSB index or a physical cell ID. For example, circuitry 1530 may enable apparatus 1505 to identify a model ID associated with an ML model or a pair ID associated with an ML model pair, based at least in part on an SSB index or a physical cell ID.

[0193] like Figure 15As shown, apparatus 1505 may include code (code 1535) stored in computer-readable medium 1425 for identifying a model ID associated with an ML model or a pair ID associated with an ML model pair, based at least in part on an SSB index or a physical cell ID. For example, when executed by processor 1420, code 1535 may cause processor 1420 to identify a model ID associated with an ML model or a pair ID associated with an ML model pair, based at least in part on an SSB index or a physical cell ID.

[0194] In some aspects, device 1505 may include circuitry (circuitry 1540) for receiving a request for location information of the UE. For example, circuitry 1540 may enable device 1505 to receive a request for location information of the UE.

[0195] like Figure 15 As shown, device 1505 may include code (code 1545) stored in computer-readable medium 1425 for receiving a request for location information of the UE. For example, when executed by processor 1420, code 1545 may cause processor 1420 to cause transceiver 1430 to receive a request for location information of the UE.

[0196] like Figure 15 As shown, device 1505 may include circuitry (circuit 1550) for transmitting location information of the UE. For example, circuitry 1550 may enable device 1505 to transmit the location information of the UE.

[0197] like Figure 15 As shown, device 1505 may include code (code 1555) stored in computer-readable medium 1425 for transmitting location information of the UE. For example, when executed by processor 1420, code 1555 may cause processor 1420 to cause transceiver 1430 to transmit the location information of the UE.

[0198] like Figure 15 As shown, device 1505 may include circuitry (circuit 1560) for receiving a pairing ID associated with an ML model pair. For example, circuitry 1560 may enable device 1505 to receive a pairing ID associated with an ML model pair.

[0199] like Figure 15 As shown, apparatus 1505 may include code (code 1565) stored in computer-readable medium 1425 for receiving a pairing ID associated with an ML model pair. For example, when executed by processor 1420, code 1565 may cause processor 1420 to cause transceiver 1430 to receive a pairing ID associated with an ML model pair.

[0200] Figure 15 This is provided as an example. Other examples can be combined with it. Figure 15 The examples described are different.

[0201] Figure 16 This is a diagram of an example device 1600 for wireless communication according to the present disclosure. Device 1600 may be a network entity, or a network entity may include device 1600. In some aspects, device 1600 includes a receiving component 1602 and a transmitting component 1604, which can communicate with each other (e.g., via one or more buses and / or one or more other components). As shown, device 1600 can use the receiving component 1602 and the transmitting component 1604 to communicate with another device 1606 (such as a UE, a base station, or another wireless communication device). As further shown, device 1600 may include a communication manager 150. Communication manager 150 may include one or more of an identification component 1608, a decoder component 1610, or a selection component 1612, etc.

[0202] In some respects, device 1600 can be configured to perform the functions described herein. Figures 1 to 8 One or more operations described herein. Additionally or alternatively, the apparatus 1600 may be configured to perform one or more processes described herein, such as Figure 10 Process 1000 Figure 11 The process 1100 or a combination thereof. In some respects, Figure 16 The illustrated device 1600 and / or one or more components may include a combination Figure 2 One or more components of the described network entity. Additionally or alternatively, Figure 16 One or more components shown can be combined Figure 2 Implementation within one or more of the described components. Alternatively or concurrently, one or more components in the set of components may be implemented at least partially as software stored in one or more memories. For example, a component (or a portion thereof) may be implemented as instructions or code stored in a non-transitory computer-readable medium and executable by one or more controllers or one or more processors to perform the function or operation of the component.

[0203] Receiver 1602 may receive communications from device 1606, such as reference signals, control information, data communications, or combinations thereof. Receiver 1602 may provide the received communications to one or more other components of device 1600. In some aspects, receiver 1602 may perform signal processing on the received communications (such as filtering, amplification, demodulation, analog-to-digital conversion, demultiplexing, deinterleaving, demapping, equalization, interference cancellation, or decoding, etc.) and may provide the processed signals to one or more other components of device 1600. In some aspects, receiver 1602 may include combinations of... Figure 2The described network entity includes one or more antennas, one or more modems, one or more demodulators, one or more MIMO detectors, one or more receiver processors, one or more controllers / processors, one or more memories, or combinations thereof.

[0204] Transmitting component 1604 may transmit communications, such as reference signals, control information, data communications, or combinations thereof, to device 1606. In some aspects, one or more other components of device 1600 may generate communications and provide the generated communications to transmitting component 1604 for transmission to device 1606. In some aspects, transmitting component 1604 may perform signal processing (such as filtering, amplification, modulation, digital-to-analog conversion, multiplexing, interleaving, mapping, or encoding, etc.) on the generated communications and may transmit the processed signals to device 1606. In some aspects, transmitting component 1604 may include combinations of... Figure 2 The described network entity includes one or more antennas, one or more modems, one or more modulators, one or more transmit MIMO processors, one or more transmit processors, one or more controllers / processors, one or more memories, or combinations thereof. In some aspects, the transmit component 1604 may co-located with the receive component 1602 in one or more transceivers.

[0205] In some aspects, transmitting component 1604 may transmit one or more Synchronization Signal Blocks (SSBs), each SSB including a PSS, an SSS, and a PBCH carrying a MIB, each SSB being associated with an SSB index and a physical cell ID. Transmitting component 1604 may transmit one or more model IDs or one or more pair IDs in system information associated with the SSB index and physical cell ID, each of the one or more model IDs being associated with an ML model, and each of the one or more pair IDs being associated with an ML model pair. Identification component 1608 may identify a model ID from one or more model IDs or a pair ID from one or more pair IDs, at least in part, based on one or more of the SSB index or the physical cell ID.

[0206] The receiving component 1602 can receive encoded CSI feedback. The decoder component 1610 can decode the encoded CSI feedback using an ML model associated with decoding the CSI feedback related to a model ID or pair ID.

[0207] The identification component 1608 can obtain a mapping between the model ID and one or more of the SSB index or physical cell ID from the configuration information. The identification component 1608 can also obtain a mapping between the pairing ID and one or more of the SSB index or physical cell ID from the configuration information.

[0208] In some respects, selection component 1612 may select, at least in part, a component associated with a pairing ID linked to the ML model pair that encodes and decodes CSI feedback, based on the UE's location information. Transmission component 1604 may transmit the pairing ID to one or more of the UE or a second network entity.

[0209] The receiving component 1602 can receive the UE's location information. The receiving component 1602 can receive a model pair description. The receiving component 1602 can receive encoded CSI reports from the UE. The decoder component 1610 can decode the encoded CSI feedback using an ML model associated with decoding the CSI feedback related to the pairing ID.

[0210] Figure 16 The number and arrangement of components shown are provided as an example. In reality, they can exist in... Figure 16 The components shown are compared to additional components, fewer components, different components, or components arranged in a different manner. Furthermore, Figure 16 The two or more components shown can be implemented within a single component, or Figure 16 The single component shown can be implemented as multiple distributed components. Additionally or alternatively, Figure 16 The collection of (one or more) components shown is executable and described as being composed of Figure 16 Another set of components shown performs one or more functions.

[0211] Figure 17 This is an illustration of an example 1700 of a hardware implementation of a device 1705 for employing a processing system 1710 according to the present disclosure. The device 1705 may be a network entity or may be located at a network entity (e.g., included in a network entity).

[0212] Processing system 1710 can be implemented using a bus architecture generally represented by bus 1715. Bus 1715 may include any number of interconnect buses and bridges, depending on the specific application of processing system 1710 and overall design constraints. Bus 1715 links together various circuits including one or more processors and / or hardware components represented by processor 1720, illustrated components, and computer-readable medium / memory 1725. Processor 1720 may include multiple processors, such as processor 1720a, memory 1720b, and memory 1720c. Memory 1725 may include multiple memories, such as memory 1725a, memory 1725b, and memory 1725c. Bus 1715 may also link various other circuits, such as timing sources, peripheral devices, voltage regulators, and / or power management circuits.

[0213] Processing system 1710 may be coupled to one or more transceivers 1730. Transceiver 1730 is coupled to one or more antennas 1735. Transceiver 1730 provides components for communicating with various other devices via a transmission medium. Transceiver 1730 receives signals from one or more antennas 1735, extracts information from the received signals, and provides the extracted information to processing system 1710 (specifically, receiving component 1602). Furthermore, transceiver 1730 receives information from processing system 1710 (specifically, transmitting component 1604) and generates signals to be applied to one or more antennas 1735 based at least in part on the received information.

[0214] Processing system 1710 includes one or more processors 1720 coupled to computer-readable medium / memory 1725. Processor 1720 is responsible for general processing, including executing software stored on computer-readable medium / memory 1725. When executed by processor 1720, the software causes processing system 1710 to perform the various functions described herein with respect to any particular device. Computer-readable medium / memory 1725 can also be used to store data manipulated by processor 1720 during software execution. The processing system also includes at least one of the illustrated components. A component may be: a software module running in processor 1720, residing in / stored on computer-readable medium / memory 1725, one or more hardware modules coupled to processor 1720, or some combination thereof.

[0215] In some aspects, the processing system 1710 may be a component of the UE 120 and may include one or more memories (such as memory 282) and / or may include one or more processors (such as at least one of TX MIMO processor 266, RX processor 258, and / or controller / processor 280). In some aspects, the apparatus 1705 for wireless communication includes: components for transmitting one or more synchronization signal blocks (SSBs), each SSB including a PSS, an SSS, and a PBCH carrying a MIB, each SSB being associated with an SSB index and a physical cell ID; components for transmitting one or more model IDs or one or more pairing IDs in system information associated with the SSB index and the physical cell ID, each of the one or more model IDs being associated with an ML model, and each of the one or more pairing IDs being associated with an ML model pair; and components for identifying a model ID from one or more model IDs or a pairing ID from one or more pairing IDs, at least in part based on one or more of the SSB index or the physical cell ID. In some aspects, the apparatus 1705 for wireless communication includes: components for selecting a pairing ID associated with an ML model pair that encodes and decodes CSI feedback, at least in part based on the location information of the UE; and components for transmitting the pairing ID to one or more of the UE or a second network entity. The aforementioned components may be one or more of the aforementioned components of the processing system 1710 of apparatus 1700 and / or apparatus 1705, configured to perform the functions stated by the aforementioned components. As described elsewhere herein, the processing system 1710 may include a TX MIMO processor 266, an RX processor 258, and / or a controller / processor 280. In one configuration, the aforementioned components may be the TX MIMO processor 266, the RX processor 258, and / or the controller / processor 280, configured to perform the functions and / or operations stated herein.

[0216] Figure 17 This is provided as an example. Other examples can be combined with it. Figure 17 The examples described are different.

[0217] Figure 18 This is an illustration of example 1800 of a specific implementation of code and circuitry for device 1805 according to this disclosure. The circuitry may include processing circuitry and memory circuitry. Device 1805 may be a network entity, or a network entity may include device 1805.

[0218] like Figure 18As shown, device 1805 may include circuitry for transmitting one or more SSBs, each SSB including a PSS, an SSS, and a PBCH carrying a MIB, each SSB being associated with an SSB index and a physical cell ID (circuitry 1820). For example, circuitry 1820 may enable device 1805 to transmit one or more SSBs, each SSB including a PSS, an SSS, and a PBCH carrying a MIB, each SSB being associated with an SSB index and a physical cell ID.

[0219] like Figure 18 As shown, apparatus 1805 may include code stored in computer-readable medium 1725 for transmitting one or more SSBs, each SSB including a PSS, an SSS, and a PBCH carrying a MIB, each SSB being associated with an SSB index and a physical cell ID (code 1825). For example, when executed by processor 1720, code 1825 may cause processor 1720 to cause transceiver 1730 to transmit one or more SSBs, each SSB including a PSS, an SSS, and a PBCH carrying a MIB, each SSB being associated with an SSB index and a physical cell ID.

[0220] like Figure 18 As shown, apparatus 1805 may include circuitry for transmitting one or more model IDs or one or more pair IDs in system information associated with an SSB index and a physical cell ID, each of the one or more model IDs being associated with an ML model, and each of the one or more pair IDs being associated with an ML model pair (circuitry 1830). For example, circuitry 1830 may enable apparatus 1805 to transmit one or more model IDs or one or more pair IDs in system information associated with an SSB index and a physical cell ID, each of the one or more model IDs being associated with an ML model, and each of the one or more pair IDs being associated with an ML model pair.

[0221] like Figure 18As shown, apparatus 1805 may include code stored in computer-readable medium 1725 for transmitting one or more model IDs or one or more pair IDs in system information associated with an SSB index and a physical cell ID, each of the one or more model IDs being associated with an ML model, and each of the one or more pair IDs being associated with an ML model pair (code 1835). For example, when executed by processor 1720, code 1835 may cause processor 1720 to cause transceiver 1730 to transmit one or more model IDs or one or more pair IDs in system information associated with an SSB index and a physical cell ID, each of the one or more model IDs being associated with an ML model, and each of the one or more pair IDs being associated with an ML model pair.

[0222] like Figure 18 As shown, device 1805 may include circuitry (circuit 1840) for identifying a model ID from one or more model IDs or a pair ID from one or more pair IDs, based at least in part on one or more of the SSB index or physical cell ID. For example, circuitry 1840 may enable device 1805 to identify a model ID from one or more model IDs or a pair ID from one or more pair IDs, based at least in part on one or more of the SSB index or physical cell ID.

[0223] like Figure 18 As shown, apparatus 1805 may include code (code 1845) stored in computer-readable medium 1725 for identifying a model ID from one or more model IDs or a pair ID from one or more pair IDs, based at least in part on one or more of the SSB index or physical cell ID. For example, when executed by processor 1720, code 1845 may cause processor 1720 to identify a model ID from one or more model IDs or a pair ID from one or more pair IDs, based at least in part on one or more of the SSB index or physical cell ID.

[0224] like Figure 18 As shown, device 1805 may include circuitry (circuit 1850) for selecting a pairing ID associated with an ML model pair that encodes and decodes CSI feedback, based at least in part on the UE's location information. For example, circuitry 1850 may enable device 1805 to select a pairing ID associated with an ML model pair that encodes and decodes CSI feedback, based at least in part on the UE's location information.

[0225] like Figure 18As shown, apparatus 1805 may include code (code 1855) stored in computer-readable medium 1725 for selecting a pairing ID associated with a pair of ML models that encode and decode CSI feedback, based at least in part on the UE's location information. For example, when executed by processor 1720, code 1855 may cause processor 1720 to select a pairing ID associated with a pair of ML models that encode and decode CSI feedback, based at least in part on the UE's location information.

[0226] like Figure 18 As shown, device 1805 may include circuitry (circuit 1860) for sending a pairing ID to one or more of the UE or the second network entity. For example, circuitry 1860 may enable device 1805 to send a pairing ID to one or more of the UE or the second network entity.

[0227] like Figure 18 As shown, apparatus 1805 may include code (code 1865) stored in computer-readable medium 1725 for sending a pairing ID to one or more of the UE or a second network entity. For example, when executed by processor 1720, code 1865 may cause processor 1720 to cause transceiver 1730 to send the pairing ID to one or more of the UE or a second network entity.

[0228] Figure 18 This is provided as an example. Other examples can be combined with it. Figure 18 The examples described are different.

[0229] The following provides an overview of some aspects of this disclosure.

[0230] Aspect 1: A method for wireless communication performed by a user equipment (UE), the method comprising: receiving a primary synchronization signal (PSS) and a secondary synchronization signal (SSS); identifying a primary information block (MIB) carried by a physical broadcast channel (PBCH) based at least in part on the PSS and the SSS; identifying a physical cell identifier (ID) based at least in part on one or more of the PSS or the SSS; identifying a synchronization signal block (SSB) index based at least in part on scrambling of the PBCH; and identifying a model ID associated with a machine learning (ML) model or a pair ID associated with an ML model pair based at least in part on the SSB index or the physical cell ID.

[0231] Aspect 2: According to the method of aspect 1, wherein the ML model is associated with encoding or decoding channel state information (CSI) feedback, and wherein the ML model is associated with encoding and decoding CSI feedback.

[0232] Aspect 3: The method according to any one of Aspects 1 to 2, the method further comprising: encoding channel state information (CSI) feedback using the ML model associated with the model ID or using the ML model in the ML model pair associated with the pairing ID; and transmitting the encoded CSI feedback.

[0233] Aspect 4: The method according to any one of Aspects 1 to 3, wherein the MIB indicates one or more model IDs, and wherein identifying the model ID includes identifying the model ID from the one or more model IDs based at least in part on a mapping between the model ID and one or more of the SSB index or the physical cell ID.

[0234] Aspect 5: The method according to any one of Aspects 1 to 4, wherein the MIB indicates a list of one or more pairing IDs, and wherein identifying the pairing ID includes identifying the pairing ID from the list of one or more pairing IDs based at least in part on a mapping between the pairing ID and one or more of the SSB index or the physical cell ID.

[0235] Aspect 6: The method according to any one of Aspects 1 to 5, wherein identifying the model ID includes further identifying the model ID based at least in part on Residual Minimal System Information (RMSI) or other System Information (OSI).

[0236] Aspect 7: The method according to any one of Aspects 1 to 6, wherein identifying the pairing ID includes further identifying the pairing ID based at least in part on Residual Minimal System Information (RMSI) or other System Information (OSI).

[0237] Aspect 8: A method of wireless communication performed by a network entity, the method comprising: transmitting one or more synchronization signal blocks (SSBs), each SSB including a primary synchronization signal (PSS), a secondary synchronization signal (SSS), and a physical broadcast channel (PBCH) carrying a primary information block (MIB), each SSB being associated with an SSB index and a physical cell identifier (ID); transmitting one or more model IDs or one or more pair IDs in system information associated with the SSB index and the physical cell ID, each of the one or more model IDs being associated with a machine learning (ML) model, and each of the one or more pair IDs being associated with an ML model pair; and identifying a model ID from the one or more model IDs or identifying a pair ID from the one or more pair IDs based at least in part on one or more of the SSB index or the physical cell ID.

[0238] Aspect 9: According to the method of aspect 8, the method further includes: receiving encoded CSI feedback; and decoding the encoded CSI feedback using an ML model associated with decoding the CSI feedback associated with the model ID or the pairing ID.

[0239] Aspect 10: The method according to any one of Aspects 8 to 9, wherein sending the one or more model IDs includes sending the one or more model IDs in a Master Information Block (MIB).

[0240] Aspect 11: According to the method of aspect 10, the method further includes obtaining a mapping between the model ID and one or more of the SSB index or the physical cell ID from the configuration information.

[0241] Aspect 12: The method according to any one of Aspects 8 to 11, wherein sending the one or more pairing IDs includes sending a list of pairing IDs in the Master Information Block (MIB).

[0242] Aspect 13: According to the method of aspect 12, the method further includes obtaining a mapping between the pairing ID and one or more of the SSB index or the physical cell ID from configuration information.

[0243] Aspect 14: The method according to any one of Aspects 8 to 13, wherein sending the one or more model IDs includes sending the model ID in Residual Minimal System Information (RMSI) or other System Information (OSI).

[0244] Aspect 15: The method according to any one of Aspects 8 to 14, wherein sending the one or more pairing IDs includes sending the pairing ID in Residual Minimal System Information (RMSI) or other System Information (OSI).

[0245] Aspect 16: A method of wireless communication performed by a first network entity, the method comprising: selecting a pairing identifier (ID) associated with a machine learning (ML) model pair that encodes and decodes channel state information (CSI) feedback, based at least in part on location information of a user equipment (UE); and transmitting the pairing ID to one or more of the UE or a second network entity.

[0246] Aspect 17: The method according to aspect 16 further includes receiving the location information of the UE.

[0247] Aspect 18: The method according to any one of Aspects 16 to 17, wherein selecting the pair ID includes further selecting the pair ID based at least in part on a model pair description associated with one or more of the scene information or location information for the ML model pair.

[0248] Aspect 19: The method according to aspect 18, wherein selecting the pair ID includes further selecting the pair ID based at least in part on meta-information describing the model pair.

[0249] Aspect 20: According to the method of aspect 18, the method further includes receiving the model pair description.

[0250] Aspect 21: The method according to any one of Aspects 16 to 20, the method further comprising: receiving encoded CSI feedback from the UE; and decoding the encoded CSI feedback using an ML model associated with decoding the CSI feedback associated with the pairing ID.

[0251] Aspect 22: A method of wireless communication performed by a user equipment (UE), the method comprising: receiving a request for location information of the UE; transmitting the location information of the UE; and receiving a pairing identifier (ID) associated with a machine learning (ML) model pair.

[0252] Aspect 23: According to the method of aspect 22, the method further includes: encoding the CSI feedback using an ML model associated with encoding the CSI feedback associated with the pairing ID; and sending the encoded CSI feedback.

[0253] Aspect 24: An apparatus for wireless communication at a device, the apparatus comprising one or more processors; one or more memories coupled to the one or more processors; and instructions stored in the one or more memories and executable by the one or more processors to cause the apparatus to perform the method according to one or more of aspects 1 to 23.

[0254] Aspect 25: An apparatus for wireless communication at a device, the apparatus comprising one or more memories and one or more processors coupled to the one or more memories, the one or more processors being configured to cause the device to perform the method according to one or more of aspects 1 to 23.

[0255] Aspect 26: An apparatus for wireless communication, the apparatus comprising at least one component for performing the method according to one or more of aspects 1 to 23.

[0256] Aspect 27: A non-transitory computer-readable medium storing code for wireless communication, the code including instructions executable by one or more processors to perform the method according to one or more of aspects 1 to 23.

[0257] Aspect 28: A non-transitory computer-readable medium storing a set of instructions for wireless communication, the set of instructions comprising one or more instructions that, when executed by one or more processors of a device, cause the device to perform the method according to one or more of aspects 1 to 23.

[0258] Aspect 29: A device for wireless communication, the device including a processing system comprising one or more processors and one or more memories coupled to the one or more processors, the processing system being configured to cause the device to perform the method according to one or more of aspects 1 to 23.

[0259] Aspect 30: An apparatus for wireless communication at a device, the apparatus comprising one or more memories and one or more processors coupled to the one or more memories, the one or more processors being individually or collectively configured to cause the device to perform one or more of the methods according to aspects 1 to 23.

[0260] Aspect 31: An apparatus for wireless communication at a user equipment (UE), the apparatus comprising: a processing system including processor circuitry and memory circuitry storing code and coupled to the processor circuitry, the processing system being configured to cause the UE to perform one or more of the methods according to aspects 1 to 23.

[0261] Aspect 32: An apparatus for wireless communication at a user equipment (UE), the apparatus comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors being configured to cause the UE to: receive a primary synchronization signal (PSS) and a secondary synchronization signal (SSS); identify a primary information block (MIB) carried by a physical broadcast channel (PBCH) based at least in part on the PSS and the SSS; identify a physical cell identifier (ID) based at least in part on one or more of the PSS or the SSS; identify a synchronization signal block (SSB) index based at least in part on scrambling of the PBCH; and identify a model ID associated with a machine learning (ML) model or a pair ID associated with an ML model pair based at least in part on the SSB index or the physical cell ID.

[0262] Aspect 33: The apparatus according to aspect 32, wherein the one or more processors are individually or jointly configured to cause the UE to: receive a primary synchronization signal (PSS) and a secondary synchronization signal (SSS); identify a primary information block (MIB) carried by a physical broadcast channel (PBCH) based at least in part on the PSS and the SSS; identify a physical cell identifier (ID) based at least in part on one or more of the PSS or the SSS; identify a synchronization signal block (SSB) index based at least in part on scrambling of the PBCH; and identify a model ID associated with a machine learning (ML) model or a pair ID associated with an ML model pair based at least in part on the SSB index or the physical cell ID.

[0263] Aspect 34: An apparatus for wireless communication at a network entity, the apparatus comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors being configured to cause the network entity to: transmit one or more synchronization signal blocks (SSBs), each SSB including a primary synchronization signal (PSS), a secondary synchronization signal (SSS), and a physical broadcast channel (PBCH) carrying a primary information block (MIB), each SSB being associated with an SSB index and a physical cell identifier (ID); transmit one or more model IDs or one or more pair IDs in system information associated with the SSB index and the physical cell ID, each of the one or more model IDs being associated with a machine learning (ML) model, and each of the one or more pair IDs being associated with an ML model pair; and identify a model ID from the one or more model IDs or identify a pair ID from the one or more pair IDs based at least in part on one or more of the SSB index or the physical cell ID.

[0264] Aspect 35: The apparatus according to aspect 34, wherein the one or more processors are individually or jointly configured to cause the UE to: transmit one or more synchronization signal blocks (SSBs), each SSB including a primary synchronization signal (PSS), a secondary synchronization signal (SSS), and a physical broadcast channel (PBCH) carrying a primary information block (MIB), each SSB being associated with an SSB index and a physical cell identifier (ID); transmit one or more model IDs or one or more pair IDs in system information associated with the SSB index and the physical cell ID, each of the one or more model IDs being associated with a machine learning (ML) model, and each of the one or more pair IDs being associated with an ML model pair; and identify a model ID from the one or more model IDs or a pair ID from the one or more pair IDs at least in part based on one or more of the SSB index or the physical cell ID.

[0265] Aspect 36: An apparatus for wireless communication at a user equipment (UE), the apparatus comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors being configured to cause the UE to: select, at least in part, based on location information of the user equipment (UE), a pairing identifier (ID) associated with a machine learning (ML) model that encodes and decodes channel state information (CSI) feedback; and transmit the pairing ID to one or more of the UE or a second network entity.

[0266] Aspect 37: The apparatus according to aspect 36, wherein the one or more processors are individually or jointly configured to cause the UE to: select, at least in part, based on the location information of the user equipment (UE), a pairing identifier (ID) associated with a machine learning (ML) model pair that encodes and decodes channel state information (CSI) feedback; and transmit the pairing ID to one or more of the UE or a second network entity.

[0267] Aspect 38: An apparatus for wireless communication at a user equipment (UE), the apparatus comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors being configured to cause the UE to: receive a request for location information of the UE; transmit the location information of the UE; and receive a pairing identifier (ID) associated with a machine learning (ML) model pair.

[0268] Aspect 39: The apparatus according to aspect 38, wherein the one or more processors are individually or jointly configured to cause the UE to: receive a request for location information of the UE; transmit the location information of the UE; and receive a pairing identifier (ID) associated with a machine learning (ML) model pair.

[0269] Aspect 40: An apparatus for wireless communication at a user equipment (UE), the apparatus comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors being configured to cause the UE to perform the method according to any one of claims 1 to 7 and 22 to 23.

[0270] Aspect 40: An apparatus for wireless communication at a network entity, the apparatus comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors being configured to cause the UE to perform the method according to any one of claims 8 to 21.

[0271] While the foregoing disclosure provides examples and descriptions, it is not intended to be exhaustive or to limit aspects to the precise form disclosed. Modifications and variations can be made based on the foregoing disclosure, or from various aspects of practice.

[0272] As used herein, the term "component" is intended to be interpreted broadly as hardware and / or a combination of hardware and software. Whether referred to as software, firmware, middleware, microcode, hardware description language, or other names, "software" should be interpreted broadly as meaning instructions, instruction sets, code, code segments, program code, programs, subroutines, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, and / or functions, etc. As used herein, a "processor" is implemented in hardware and / or a combination of hardware and software. It will be apparent to those skilled in the art that the systems and / or methods described herein can be implemented in various forms of hardware and / or combinations of hardware and software. The actual dedicated control hardware or software code used to implement these systems and / or methods is not limiting in any way. Therefore, no specific software code is referenced in this document to describe the operation and behavior of the systems and / or methods, as those skilled in the art will understand that the software and hardware can be designed, at least in part, based on the descriptions herein, to implement the systems and / or methods.

[0273] Hardware and data processing means for implementing the various exemplary logic, logic blocks, modules, and circuits described herein can be implemented or executed using general-purpose single-chip or multi-chip processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic components, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor can be a microprocessor, or any conventional processor, controller, microcontroller, or state machine. A processor can also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors combined with a DSP core, or any other such configuration. In some aspects, specific processes and methods can be performed by circuitry dedicated to a given function.

[0274] As used in this article, depending on the context, "meeting the threshold" can mean a value greater than the threshold, greater than or equal to the threshold, less than the threshold, less than or equal to the threshold, equal to the threshold, not equal to the threshold, etc.

[0275] Although specific combinations of features are set forth in the claims and / or disclosed in the specification, these combinations are not intended to limit the disclosure of various aspects. Many of these features may be combined in ways not specifically set forth in the claims and / or not disclosed in the specification. The disclosure of various aspects includes each dependent claim in combination with each other claim in the set of claims. As used herein, the phrase referring to “at least one of” the list of items means any combination of these items, including a single member. As an example, “at least one of a, b, or c” is intended to cover: a, b, c, a+b, a+c, b+c, and a+b+c, as well as any combination having multiple identical elements (e.g., a+a, a+a+a, a+a+b, a+a+c, a+b+b, a+c+c, b+b, b+b+b, b+b+c, c+c, and c+c+c, or any other ordering of a, b, and c).

[0276] No element, action, or instruction used herein should be construed as essential or necessary unless explicitly stated otherwise. Furthermore, as used herein, the articles “a” and “an” are intended to include one or more items and are used interchangeably with “one or more.” Furthermore, as used herein, the article “described” is intended to include one or more items mentioned in connection with the article “described” and is used interchangeably with “one or more.” Furthermore, as used herein, the terms “group” and “cluster” are intended to include one or more items and are used interchangeably with “one or more.” If only one item is desired, the phrase “only one” or similar terminology will be used. Furthermore, as used herein, the terms “have,” “possess,” “have,” etc., are intended to be open-ended terms that do not limit the elements they modify (e.g., an element “having” A may also have B). Furthermore, the phrase “based on” is intended to mean “at least partially based on” unless otherwise explicitly stated. Furthermore, as used herein, the term “or” is intended to be inclusive when used in a series and is interchangeable with “and / or” unless otherwise explicitly stated (e.g., in the case of its use in conjunction with “any” or “only one”).

Claims

1. An apparatus for wireless communication at a user equipment (UE), the apparatus comprising: one or more memories; and one or more processors coupled to the one or more memories and configured to cause the UE to: receive a primary synchronization signal (PSS) and a secondary synchronization signal (SSS); identify, based at least in part on the PSS and the SSS, a master information block (MIB) carried by a physical broadcast channel (PBCH), identify a physical cell identifier (ID) based at least in part on one or more of the PSS or the SSS; identify a synchronization signal block (SSB) index based at least in part on a scrambling of the PBCH; and identify, based at least in part on the SSB index or the physical cell ID, a model ID associated with a machine learning (ML) model or a pairing ID associated with a pair of ML models.

2. The apparatus of claim 1, wherein the ML model is associated with encoding or decoding channel state information (CSI) feedback, and wherein the pair of ML models is associated with encoding and decoding CSI feedback.

3. The apparatus of claim 1, wherein the one or more processors are further configured to cause the UE to: encode channel state information (CSI) feedback using the ML model associated with the model ID or using an ML model of the pair of ML models associated with the pairing ID; and transmit the encoded CSI feedback.

4. The apparatus of claim 1, wherein the MIB indicates one or more model IDs, and wherein to identify the model ID, the one or more processors are configured to cause the UE to identify the model ID from the one or more model IDs based at least in part on a mapping between the model ID and one or more of the SSB index or the physical cell ID.

5. The apparatus of claim 1, wherein the MIB indicates a list of one or more pairing IDs, and wherein to identify the pairing ID, the one or more processors are configured to identify the pairing ID from the list of one or more pairing IDs based at least in part on a mapping between the pairing ID and one or more of the SSB index or the physical cell ID.

6. The apparatus of claim 1, wherein to cause the UE to identify the model ID, the one or more processors are configured to cause the UE to further identify the model ID based at least in part on remaining minimum system information (RMSI) or other system information (OSI).

7. The apparatus of claim 1, wherein to cause the UE to identify the pairing ID, the one or more processors are configured to cause the UE to further identify the pairing ID based at least in part on remaining minimum system information (RMSI) or other system information (OSI).

8. An apparatus for wireless communication at a network entity, the apparatus comprising: one or more memories; and one or more processors coupled to the one or more memories and configured to cause the network entity to: transmit a primary synchronization signal (PSS) and a secondary synchronization signal (SSS); transmit a master information block (MIB) carried by a physical broadcast channel (PBCH) based at least in part on the PSS and the SSS, transmit a physical cell identifier (ID) based at least in part on one or more of the PSS or the SSS; transmit a synchronization signal block (SSB) based at least in part on a scrambling of the PBCH; and transmit, based at least in part on the SSB or the physical cell ID, a model ID associated with a machine learning (ML) model or a pairing ID associated with a pair of ML models. one or more processors coupled to the one or more memories and configured to cause the network entity to: transmit one or more synchronization signal blocks (SSBs), each SSB including a primary synchronization signal (PSS), a secondary synchronization signal (SSS), and a physical broadcast channel (PBCH) carrying a master information block (MIB), each SSB being associated with a SSB index and a physical cell identifier (ID); transmit, in system information associated with the SSB index and the physical cell ID, one or more model IDs or one or more pairing IDs, each model ID of the one or more model IDs being associated with a machine learning (ML) model and each pairing ID of the one or more pairing IDs being associated with a pair of ML models; and identify, based at least in part on one or more of the SSB index or the physical cell ID, a model ID from the one or more model IDs or a pairing ID from the one or more pairing IDs.

9. The apparatus of claim 8, wherein the one or more processors are further configured to cause the network entity to: receive encoded CSI feedback; and decode the encoded CSI feedback using a ML model associated with decoding CSI feedback associated with the model ID or the pairing ID.

10. The apparatus of claim 8, wherein to cause the network entity to transmit the one or more model IDs, the one or more processors are configured to cause the network entity to transmit the one or more model IDs in a master information block (MIB).

11. The apparatus of claim 10, wherein the one or more processors are configured to cause the network entity to obtain a mapping between the model ID and one or more of the SSB index or the physical cell ID from configuration information.

12. The apparatus of claim 8, wherein to cause the network entity to transmit the one or more pairing IDs, the one or more processors are configured to cause the network entity to transmit a list of pairing IDs in a master information block (MIB).

13. The apparatus of claim 12, wherein the one or more processors are configured to cause the network entity to obtain a mapping between the pairing ID and one or more of the SSB index or the physical cell ID from configuration information.

14. The apparatus of claim 8, wherein to cause the network entity to transmit the one or more model IDs, the one or more processors are configured to cause the network entity to transmit a model ID in remaining minimum system information (RMSI) or other system information (OSI).

15. The apparatus of claim 8, wherein to cause the network entity to transmit the one or more pairing IDs, the one or more processors are configured to cause the network entity to transmit a pairing ID in remaining minimum system information (RMSI) or other system information (OSI).

16. An apparatus for wireless communication at a first network entity, the apparatus comprising: one or more memories; and one or more processors coupled to the one or more memories and configured to cause the first network entity to: select, based at least in part on location information of a user equipment (UE), a pairing identifier (ID) associated with a pair of machine learning (ML) models associated with encoding and decoding channel state information (CSI) feedback; and transmit, to one or more of the UE or a second network entity, the pairing ID.

17. The apparatus of claim 16, wherein the one or more processors are configured to cause the first network entity to receive the location information of the UE.

18. The apparatus of claim 16, wherein to select the pairing ID, the one or more processors are configured to cause the first network entity to further select the pairing ID based at least in part on a model pair description associated with one or more of scenario information or location information for the pair of ML models.

19. The apparatus of claim 18, wherein to select the pairing ID, the one or more processors are configured to cause the first network entity to further select the pairing ID based at least in part on meta information for the model pair description.

20. The apparatus of claim 18, wherein the one or more processors are further configured to cause the first network entity to receive the model pair description.

21. The apparatus of claim 16, wherein the one or more processors are further configured to cause the first network entity to: receive, from the UE, encoded CSI feedback; and decode the encoded CSI feedback using a ML model associated with decoding CSI feedback associated with the pairing ID.

22. An apparatus for wireless communication at a user equipment (UE), the apparatus comprising: one or more memories; and one or more processors coupled to the one or more memories and configured to cause the UE to: receive a request for location information of the UE; transmit the location information of the UE; and receive a pairing identifier (ID) associated with a pair of machine learning (ML) models.

23. The apparatus of claim 22, wherein the one or more processors are further configured to cause the UE to: encode CSI feedback using a ML model associated with encoding CSI feedback associated with the pairing ID; and transmit encoded CSI feedback. ​

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