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    ML MODEL TRAINING PROCEDURE
    1.
    发明申请
    ML MODEL TRAINING PROCEDURE 审中-公开

    公开(公告)号：WO2022245459A1

    公开(公告)日：2022-11-24

    申请号：PCT/US2022/025384

    申请日：2022-04-19

    Applicant: QUALCOMM INCORPORATED

    Inventor： KUMAR, Rajeev ,  BALEVI, Eren ,  YOO, Taesang ,  ZHU, Xipeng ,  HORN, Gavin Bernard ,  KRISHNAN, Shankar ,  GHOLMIEH, Aziz

    IPC: H04L41/16

    Abstract: This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for an ML model training procedure. A network entity may receive a trigger to activate an ML model training procedure based on at least one of an indication from an ML model repository or a protocol of the network entity. The network entity may transmit an ML model training request to activate the ML model training at one or more nodes. The one or more nodes may be associated with a RAN that may transmit, based on receiving the ML model training request, ML model training results indicative of a trained ML model. In aspects, an apparatus, such as a UE, may train the ML model based on an ML model training configuration received from the RAN, and transmit an ML model training report indicative of the trained ML model.

    OVER-THE-AIR (OTA) DATA AGGREGATION
    5.
    发明申请
    OVER-THE-AIR (OTA) DATA AGGREGATION 审中-公开

    公开(公告)号：WO2023091834A1

    公开(公告)日：2023-05-25

    申请号：PCT/US2022/078333

    申请日：2022-10-19

    Applicant: QUALCOMM INCORPORATED

    Inventor： PEZESHKI, Hamed ,  LUO, Tao ,  YOO, Taesang ,  BALEVI, Eren ,  YERRAMALLI, Srinivas ,  LI, Junyi

    IPC: H04B7/0452

    Abstract: Certain aspects of the present disclosure provide techniques for over-the-air (OTA) aggregation of data. Certain techniques include transmitting, to a plurality of user equipments (UEs), a first reference signal (RS) via a first transmit beam of a base station (BS), wherein the plurality of UEs and the BS share a global federated learning model; receiving, in response to the first RS, a first set of signals each carrying corresponding local gradient information of a first set of local gradient information for the global federated learning model, the first set of local gradient information comprising local gradient information calculated by each UE of multiple UEs of the plurality of UEs, the first set of local gradient information received via a first receive beam of the BS; and aggregating, in an analog domain, the first set of signals to aggregate the first set of local gradient information received from the multiple UEs.

    USER EQUIPMENT PARTICIPATION INDICATIONS ASSOCIATED WITH FEDERATED LEARNING
    7.
    发明申请
    USER EQUIPMENT PARTICIPATION INDICATIONS ASSOCIATED WITH FEDERATED LEARNING 审中-公开

    公开(公告)号：WO2023044192A1

    公开(公告)日：2023-03-23

    申请号：PCT/US2022/074338

    申请日：2022-07-29

    Applicant: QUALCOMM INCORPORATED

    Inventor： PEZESHKI, Hamed ,  YOO, Taesang ,  LUO, Tao ,  BALEVI, Eren

    IPC: H04W24/04

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a base station, a federated learning configuration that configures a participation indication to be used by the UE to indicate a participation status of the UE associated with at least one federated learning round corresponding to a machine learning component. The UE may transmit the participation indication to the base station based at least in part on the federated learning configuration. Numerous other aspects are described.

    UE CAPABILITY FOR AI/ML
    8.
    发明申请
    UE CAPABILITY FOR AI/ML 审中-公开

    公开(公告)号：WO2022235363A1

    公开(公告)日：2022-11-10

    申请号：PCT/US2022/023448

    申请日：2022-04-05

    Applicant: QUALCOMM INCORPORATED

    Inventor： ZHU, Xipeng ,  HORN, Gavin Bernard ,  YOO, Taesang ,  JI, Tingfang ,  KUMAR, Rajeev ,  KRISHNAN, Shankar ,  BALEVI, Eren ,  GHOLMIEH, Aziz

    IPC: H04W8/24 ,  H04W24/02

    Abstract: This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for a UE capability for AI/ML. A UE may receive a request from a network to report a UE capability for at least one of an AI procedure or an ML procedure. The UE may transmit to the network, based on the request to report the UE capability, an indication of one or more of an AI capability, an ML capability, a radio capability associated with the at least one of the AI procedure or the ML procedure, or a core network capability associated with the at least one of the AI procedure or the ML procedure.

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