MACHINE LEARNING BASED DYNAMIC DEMODULATOR SELECTION

    公开(公告)号:US20230035125A1

    公开(公告)日:2023-02-02

    申请号:US17388942

    申请日:2021-07-29

    Abstract: A user equipment may be configured to perform demodulator selection based on ML model coefficients trained by a base station. In some aspects, the user equipment may transmit a dynamic demodulator indication to a base station, transmit channel information to the base station, and receive, in response to the dynamic demodulator indication, updated coefficient information based on the channel information. Further, the user equipment may select a demodulator based on the updated coefficient information, and communicate with the base station via the demodulator in response to the selection of the demodulator.

    TECHNIQUES FOR CONFIGURING DEMODULATOR SEARCH SPACE IN WIRELESS COMMUNICATIONS

    公开(公告)号:US20220321257A1

    公开(公告)日:2022-10-06

    申请号:US17217701

    申请日:2021-03-30

    Abstract: Aspects described herein relate to configuring a search space size for a demodulator to use in generating log likelihood ratios (LLRs) in demodulating received signals. In an aspect, an indication of a search space size for a demodulator to use in generating LLRs can be received from a base station, and a demodulation of one or more signals received in wireless communication can be performed by a node using the demodulator and based on the search space size. In another aspect, a search space size for the demodulator of the node to use in generating log likelihood ratios (LLRs) can be determined based on one or more signals transmitted by the node, and an indication of a search space size can be transmitted to the node.

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