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    DATA GATHERING AND DATA SELECTION TO TRAIN A MACHINE LEARNING ALGORITHM
    71.
    发明申请
    DATA GATHERING AND DATA SELECTION TO TRAIN A MACHINE LEARNING ALGORITHM 有权

    公开(公告)号：US20230037704A1

    公开(公告)日：2023-02-09

    申请号：US17396417

    申请日：2021-08-06

    Applicant: QUALCOMM Incorporated

    Inventor： Mohammed HIRZALLAH ,  Srinivas YERRAMALLI ,  Taesang YOO ,  Rajat PRAKASH ,  Xiaoxia ZHANG

    IPC: H04W64/00 ,  H04W72/04 ,  G06K9/62

    Abstract: Disclosed are techniques for training a position estimation module. In an aspect, a first network entity obtains a plurality of positioning measurements, obtains a plurality of positions of one or more user equipments (UEs), the plurality of positions determined based on the plurality of positioning measurements, stores the plurality of positioning measurements as a plurality of features and the plurality of positions as a plurality of labels corresponding to the plurality of features, and trains the position estimation module with the plurality of features and the plurality of labels to determine a position of a UE from positioning measurements taken by the UE.

    SIGNALING FOR ADDITIONAL TRAINING OF NEURAL NETWORKS FOR MULTIPLE CHANNEL CONDITIONS
    72.
    发明申请
    SIGNALING FOR ADDITIONAL TRAINING OF NEURAL NETWORKS FOR MULTIPLE CHANNEL CONDITIONS 有权

    公开(公告)号：US20230021835A1

    公开(公告)日：2023-01-26

    申请号：US17385659

    申请日：2021-07-26

    Applicant: QUALCOMM Incorporated

    Inventor： Pavan Kumar VITTHALADEVUNI ,  Taesang YOO ,  Naga BHUSHAN

    IPC: H04L25/02 ,  H04B17/336 ,  G06N3/08 ,  G06N3/04

    Abstract: A method of wireless communication by a user equipment (UE) includes receiving, from a base station, a configuration to train a neural network for multiple different signal to noise ratios (SNRs) of a channel estimate for a wireless communication channel. The method also includes determining a current SNR of the channel estimate is above a first threshold value. The method further includes training the neural network based on the channel estimate, to obtain a first trained neural network. The method still further includes perturbing the channel estimate to obtain a perturbed channel estimate, and training the neural network based on the perturbed channel estimate, to obtain a second trained neural network. The method includes reporting, to the base station, parameters of the first trained neural network along with the channel estimate, and parameters of the second trained neural network.

    PREDICTIVE METHODS FOR SSB BEAM MEASUREMENTS
    74.
    发明申请
    PREDICTIVE METHODS FOR SSB BEAM MEASUREMENTS 有权

    公开(公告)号：US20220408381A1

    公开(公告)日：2022-12-22

    申请号：US17354767

    申请日：2021-06-22

    Applicant: QUALCOMM Incorporated

    Inventor： Hamed PEZESHKI ,  Tao LUO ,  Junyi LI ,  Taesang YOO ,  Sony AKKARAKARAN

    IPC: H04W56/00 ,  H04W24/08 ,  G06N3/02

    Abstract: A user equipment may be configured to perform predictive methods for SSB beam measurements. In some aspects, the user equipment may receive, from at least a base station, a first set of one or more synchronization signal block beam identifiers corresponding to a first set of one or more SSB beams belonging to a SSB burst, and receive, from at least the base station, the SSB burst including the first set of one or more SSB beams. Further, the user equipment may transmit, to at least the base station, one or more of: reporting information for a second set of one or more SSB beams or indications corresponding to the second set of one or more SSB beams, the second set of one or more SSB beams determined based on a prediction model and the first set of one or more SSB beams.

    USER EQUIPMENT (UE) CAPABILITY REPORT FOR MACHINE LEARNING APPLICATIONS
    78.
    发明申请
    USER EQUIPMENT (UE) CAPABILITY REPORT FOR MACHINE LEARNING APPLICATIONS 有权

    公开(公告)号：US20220116764A1

    公开(公告)日：2022-04-14

    申请号：US17496650

    申请日：2021-10-07

    Applicant: QUALCOMM Incorporated

    Inventor： Hamed PEZESHKI ,  Tao LUO ,  Taesang YOO

    IPC: H04W8/22 ,  G06N20/00 ,  H04W72/04 ,  H04W72/12

    Abstract: A method of wireless communication by a user equipment (UE) receives a machine learning model from a base station. The UE reports, to the base station, a machine learning processing capability. The UE also transmits, to the base station, gradient updates or weight updates to the machine learning model. A base station transmits a machine learning model to a number of UEs. The base station receives, from each of the number of UEs, a machine learning processing capability report. The base station groups a number of UEs in accordance with the machine learning processing capability reports, to receive gradient updates to the machine learning model.

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