MODEL-BASED CHANNEL STATE INFORMATION
    139.
    发明公开

    公开(公告)号:US20230291518A1

    公开(公告)日:2023-09-14

    申请号:US17654381

    申请日:2022-03-10

    CPC classification number: H04L5/0048 H04W64/006

    Abstract: This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for tracking channel variations via a model-based representation of the channel. A first network entity may receive from a second network entity or transmit to the second network entity, a model configuration indicative of a model condition of a channel between the first network entity and the second network entity. The model configuration may be associated with one or more initial parameters. The first network entity may receive a reference signal from the second network entity to measure a condition of the channel between the first network entity and the second network entity, and transmit, to the second network entity, one or more updated parameters for the model configuration based on a measurement of the condition of the channel in comparison to the model condition of the channel based on the model configuration.

    MULTI-HEAD MACHINE LEARNING MODEL FOR ESTIMATING A PLURALITY OF PARAMETER VALUES

    公开(公告)号:US20230276480A1

    公开(公告)日:2023-08-31

    申请号:US17652854

    申请日:2022-02-28

    CPC classification number: H04W72/08 G06N3/08

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a first network node may receive a signal associated with a set of resources. The first network node may determine, using a multi-head machine learning model having a body module and a plurality of head modules, a plurality of estimated parameter values of a plurality of parameters corresponding to the set of resources, wherein the body module extracts a set of common features based at least in part on a set of model inputs corresponding to the set of resources, and wherein the plurality of head modules generate the plurality of estimated parameter values based at least in part on the set of common features. The first network node may perform a wireless communication operation based at least in part on the plurality of estimated parameter values. Numerous other aspects are described.

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