CENTRALIZED MACHINE LEARNING MODEL CONFIGURATIONS

    公开(公告)号:US20250126444A1

    公开(公告)日:2025-04-17

    申请号:US18832054

    申请日:2022-03-31

    Abstract: Methods, systems, and devices for wireless communications are described. A UE may be configured with a machine learning model by a core network to perform analytics, training, or inferences. The UE may indicate capability information to a core network entity, including a list of machine learning models supported at the UE. A centralized core network entity may manage different machine learning models and may send information for a machine learning model to the UE, such as through another core network entity. The UE or the core network may initiate the configuration. For example, the UE may request to be configured with a machine learning model. The core network may send control signaling that indicates a configuration for the machine learning model to the UE. The UE may perform analytics based on the machine learning model.

    SIGNALING ASSOCIATED WITH BEAM ACTIVATION AND DEACTIVATION

    公开(公告)号:US20250055655A1

    公开(公告)日:2025-02-13

    申请号:US18772842

    申请日:2024-07-15

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive first system information indicative of a first synchronization signal block (SSB) configuration, the first SSB configuration indicating a plurality of SSBs comprising at least one deactivated SSB. The UE may receive, based on a reactivation of the at least one deactivated SSB, second system information, the second system information omitting a second SSB configuration. Numerous other aspects are described.

    INTEGRATED ACCESS AND BACKHAUL DATA COLLECTION

    公开(公告)号:US20240276246A1

    公开(公告)日:2024-08-15

    申请号:US18568390

    申请日:2022-06-28

    CPC classification number: H04W24/02 H04L41/12 H04W24/04 H04W28/0236

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, an apparatus of a central or management entity of an integrated access and backhaul (IAB) network may receive a report indicating one or more of a failure associated with a communication link associated with an IAB node included in the IAB network or a quality of service (QoS) associated with the communication link. The apparatus may modify a topography of the IAB network or routing within the IAB network when the report indicates the failure associated with the communication link. The apparatus may verify a QoS associated with the IAB network when the report indicates the QoS associated with the communication link. Numerous other aspects are described.

    PROVIDING SYSTEM INFORMATION ASSOCIATED WITH NON-ANCHOR CELLS

    公开(公告)号:US20240155472A1

    公开(公告)日:2024-05-09

    申请号:US18465637

    申请日:2023-09-12

    CPC classification number: H04W48/16

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a first network node associated with an anchor cell, first system information (SI) associated with the anchor cell and proxy information associated with obtaining second SI. The UE may obtain the second SI based on the proxy information. The UE may communicate with the non-anchor cell based on the second SI. Numerous other aspects are provided.

    FEDERATED LEARNING IN A DISAGGREGATED RADIO ACCESS NETWORK

    公开(公告)号:US20230297875A1

    公开(公告)日:2023-09-21

    申请号:US17696712

    申请日:2022-03-16

    CPC classification number: G06N20/00 G06K9/6256 H04W8/18 H04W88/085

    Abstract: Disclosed are systems and techniques for wireless communications. For instance, a network entity can determine a first data heterogeneity level associated with input data for training a machine learning model. In some cases, the network entity can determine, based on the first data heterogeneity level, a first data aggregation period for training the machine learning model. In some aspects, the network entity may obtain a first set of updated model parameters from a first client device and a second set of updated model parameters from a second client device, wherein the first set of updated model parameters and the second set of updated model parameters are based on the first data aggregation period. In some examples, the network entity can combine the first set of updated model parameters and the second set of updated model parameters to yield a first combined set of updated model parameters.

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