Abstract: Various aspects of the present disclosure relate to artificial intelligence/machine learning (AI/ML) in wireless communications. A user equipment (UE) can generate an indication associated with an AI/ML model, where the indication includes information of AI/ML model functionality available at the UE, and transmit the indication associated with the AI/ML model. In implementations, a UE can generate an indication associated with AI/ML model transfer, where the indication includes information of one or more AI/ML model transfer settings of the UE, and transmit the indication associated with the AI/ML model transfer.

Abstract: Various aspects of the present disclosure relate to reporting measurement information. A UE may receive, from a NE, configuration information for measurement and/or reporting. The configuration information indicates whether the UE is allowed to request an update for one or more parameters associated with the measurement and/or reporting, or initiate an update for one or more of the parameters. The UE may transmit, to the NE, an update request to change the one or more parameters associated with the measurement and/or reporting. The UE may transmit an update notification to change the one or more parameters associated with the measurement and/or reporting, or a selection of a pre-configured configuration from a set of pre-configured configurations. The UE may perform measurements based on the update and without notifying the NE of the update, and a measurement report is transmitted without notifying the NE of the update.

Abstract: Various aspects of the present disclosure relate to methods for artificial intelligence and machine learning model training. An apparatus, such as a UE, computes a readiness score for participation, by the UE, in tasks associated with learning model training, where the readiness score corresponds to one or more parameters associated with performance of the UE. The UE transmits, to a network equipment (NE), an indication of the readiness score. The tasks can include data collection, performing measurements, logging measured data, and reporting data, among other examples. The one or more parameters may include UE battery conditions, a hardware configuration, one or more buffer statuses, and statuses of existing tasks at the UE, among other examples. In response to the indication of the readiness score, the NE transmits a task configuration for the one or more tasks in accordance with the readiness score.

Abstract: Various aspects of the present disclosure relate to data collection for artificial intelligence (AI) functionalities. An apparatus, such as a UE, transmits first signaling that requests a configuration for collection of data for one or more AI functionalities. The UE receives, responsive to the first signaling, second signaling that indicates the configuration for the collection of the data. The UE then collects the data on the configuration. In some examples, a training entity transmits signaling that requests the data associated with one or more AI functionalities. The UE transmits, responsive to the signaling, signaling that approves collection of the data or rejects the collection of the data based on a configuration for the collection of the data.

Abstract: Various aspects of the present disclosure relate to enhanced, updated, and/or new user equipment (UE) capability framework that may introduce procedures for signaling dynamic and static capabilities to a requesting network node. The UE may store or otherwise maintain a variable that represents values (e.g., statuses) for the various dynamic and static capabilities of the UE. Further, the network node may request the UE to provide the UE capability information. Having knowledge of the dynamic and static capabilities of a UE, the RAN node may signal UE configurations that are based on a current status of the capabilities of the UE.

Abstract: Various aspects of the present disclosure relate to data reporting for artificial intelligence (AI) in wireless communications. An apparatus, such as a user equipment (UE), generates a report that indicates information associated with data collected in accordance with a first configuration. The information may include an identifier corresponding to the first configuration and a buffer size associated with an amount of data logged at the UE. The UE may transmit the report to a network equipment (NE). In some examples, the UE may receive control signaling (e.g., downlink control information (DCI)) from the NE indicating a request for at least some of the data associated with the information in the report, where the request includes one or more identifiers corresponding to the at least some of the data. The UE may transmit the requested data to the NE accordingly.

Abstract: Various aspects of the present disclosure relate to a User Equipment (UE) configured to or operable to generate a first message according to an Abstract Syntax Notation One (ASN.1) module and one or more ASN.1 sub-modules, wherein the ASN.1 module comprises information irrespective of features applicable to the UE, and wherein the one or more ASN.1 sub-modules comprises information respective to one or more features applicable to the UE, transmit, to a network entity, the first message, wherein the first message includes information respective to the one or more features applicable to the UE and excludes other information respective to one or more features inapplicable to the UE and receive, from the network entity, a second message based at least in part on the transmitted first message.

Abstract: Various aspects of the present disclosure relate to a UE for wireless communication with at least one memory and at least one processor coupled with the at least one memory and configured to cause the UE to receive a first message comprising a data collection configuration from a network entity, the data collection configuration comprising at least one measurement configuration, at least one logging configuration, and at least one reporting configuration, perform measurements according to a measurement configuration of the at least one measurement configuration, log measurement data associated with the measurements according to a logging configuration of the at least one logging configuration by storing the measurement data in the at least one memory, and transmit a second message to the network entity based on a reporting configuration of the at least one reporting configuration, the second message comprising the logged measurement data.

Abstract: Various aspects of the present disclosure relate to a user equipment (UE) for wireless communication with at least one memory and at least one processor coupled with the at least one memory and configured to cause the UE to transmit a first indication of a set of logging identifiers, wherein each logging identifier is associated with respective logged measurement data, receive a request message that identifies at least a subset of the set of logging identifiers and at least one criterion for reporting corresponding logged measurement data associated with the subset of the set of logging identifiers, and transmit a response message based at least in part on to the request message, wherein the response message comprises the corresponding logged measurement data associated with the subset of the set of logging identifiers and according to the at least one criterion.

Abstract: Various aspects of the present disclosure relate to data collection for artificial intelligence in wireless communications. An apparatus, such as a UE, receives control information comprising a first field indicating a trigger event for a data collection process, where the trigger event is based at least in part on one or more of a data sample novelty measure, a change in a configuration parameter of a node, a change in a condition of a node, a model performance metric, or model monitoring output. The apparatus triggers, based at least in part on an occurrence of the trigger event, a data collection process to generate a reporting set from a set of measured samples, and processes the reporting set based at least in part on the control information including to one or more of report the reporting set to a different node or log the reporting set to generate a logged reporting set.

Abstract: Various aspects of the present disclosure relate to model identification for artificial intelligence. An apparatus, such as a UE, transmits a set of test data and receives a first set of information associated with a first reference artificial intelligence model, where the first reference artificial intelligence model is associated with one or more of a decoder model of a two-sided artificial intelligence model or an encoder model of the two-sided artificial intelligence model. The apparatus performs a process to obtain the encoder model of the UE based at least in part on one or more of whether the first reference artificial intelligence model is associated with the encoder model of the two-sided artificial intelligence model or whether the first reference artificial intelligence model is associated with the decoder model of the two-sided artificial intelligence model.

Abstract: Various aspects of the present disclosure relate to artificial intelligence in wireless communications. An apparatus, such as a UE, receives an indication of one or more validity criterion for a portion of network context information, and stores the indication of the one or more validity criterion for the portion of the network context information as part of learning model data.

Abstract: Various aspects of the present disclosure relate to artificial intelligence in wireless communications. An apparatus, such as a user equipment (UE), receives one or more of: an indication, from a first network equipment (NE), of one or more validity criterion for a portion of network context information for a second network equipment, or identifiers for the portion of the network context information for the second network equipment.

Abstract: Various aspects of the present disclosure relate to an apparatus and method for signaling artificial intelligence (AI)/machine learning (ML) functionality. A first request message for capability information associated with AI can be received. A first response message comprising the capability information can be transmitted in response to the received first request message, where the capability information indicates one or more AI functionalities supported by a UE. A second request message can be received based at least in part on the transmitted first response message, where the second request message includes at least one configuration for AI. A second response message can be transmitted in response to the received second request message, where the second response message includes feedback that indicates whether the at least one AI functionality supported by the UE is applicable for the at least one configuration.

Abstract: Various aspects of the present disclosure relate to an apparatus and method for communicating artificial intelligence (AI)/machine learning (ML) information. A request message for information associated with AI can be received from a network entity. A response message including applicability-related information associated with at least one AI functionality supported by a UE can be transmitted to the network entity based at least in part on the received request message.

Abstract: Various aspects of the present disclosure relate to data collection procedures that reduce the number of samples reported to a network entity and/or logged by a user equipment (UE), without introducing degradation in performance and/or accuracy of a trained artificial intelligence/machine learning (AI/ML) model or a related monitoring scheme. For example, the UE may receive control information that indicates a reduced sample size mode of operation associated with data collection, determine whether to apply the reduced sample size mode of operation for a measured set of data, and incorporate the measured set of data into a reduced set of samples based on the determination.

Abstract: Various aspects of the present disclosure relate to transmitting a configuration for a serving cell associated with an irregular synchronization signal block (SSB) transmission pattern. Aspects of the present disclosure may relate to transmitting an indication for activation of SSB transmissions for the serving cell. Aspects of the present disclosure may relate to broadcasting at least one SSB transmission in the serving cell in accordance with the configuration.

Abstract: Various aspects of the present disclosure relate to scheduling data radio bearer (DRB) in network energy saving (NES) mode. An apparatus, such as a network equipment (NE), transmits, to a user equipment (UE), a mapping of NES flows to a DRB. The NE configures the DRB based at least in part on an NES class, and configures one or more bandwidth parts (BWPs) according to at least one NES configuration of the NES class. The NE configures scheduling restrictions on mapping uplink logical channels according to an NES DRB configuration, and associates the DRB to a BWP of the one or more BWPs. The NE transmits, to the UE, mapping information for the NES DRB configuration to the one or more BWPs. The UE receives, from the NE, the mapping of the NES flows to the DRB, and receives the mapping information for the NES DRB configuration to the BWPs.

Abstract: Various aspects of the present disclosure relate to jointly optimizing network and device power saving. An apparatus, such as a network equipment (NE), establishes an energy savings priority based on network energy savings and user equipment (UE) energy savings. The NE transmits a network energy saving (NES) configuration that is mapped to an NES class to a UE from which the UE establishes a (re) selection priority based at least in part on the network energy savings and the UE energy saving. The UE receives, from the NE as a cell, an indication of the NES configuration mapped to the NES class. The UE determines a remaining active time of the cell based on the NES configuration, and evaluates one or more cell-sleep conditions based on a UE cell-active threshold, a UE cell-sleep threshold, and a UE power saving state supported by the cell.

Abstract: Various aspects of the present disclosure relate to admission control considering network energy saving (NES). A network equipment (NE) configures the NE in an NES mode based on an NES class and NES configuration. The NES class and the NES configuration are obtained by the NES class and the NES configuration being determined at the NE, the NES class and the NES configuration are provisioned by a network management entity, the NES class is provisioned by the network management entity and the NES configuration is determined at the NE based on the NES class, and/or the NES class and the NES configuration are received from a network entity. A user equipment (UE) receives an indication of the NES class, where the NES class includes a QoS class identifier (QCI) supported by the NE, and configures the UE based on the NES configuration and/or the NES class.