MACHINE LEARNING BASED CHANNEL ESTIMATION FOR AN ANTENNA ARRAY

    公开(公告)号:US20240396767A1

    公开(公告)日:2024-11-28

    申请号:US18696159

    申请日:2021-10-07

    Abstract: A method of channel estimation for a receiver side antenna array includes receiving a first signal associated with a pilot tone transmitted by a transmitter side antenna array, obtaining a first group of neural network models trained for channel estimation based on the pilot tone, inputting a representation of the received first signal into each neural network model of the first group, performing one-dimensional interpolation for second signals associated with data tones in at least one of time domain and frequency domain, obtaining a second group of neural network models trained for channel estimation in presence of interpolation errors based on the data tones, and for each one-dimensional interpolation, inputting an interpolated channel estimate of the generated interpolated channel estimates into each neural network model of the second group and generating a corrected interpolated channel estimate for a second signal.

    SELECTING MODULATION AND CODING SCHEME

    公开(公告)号:US20230094649A1

    公开(公告)日:2023-03-30

    申请号:US17953828

    申请日:2022-09-27

    Abstract: A modulation and coding scheme for a transmission to an apparatus may be selected by at least sampling a posteriori probability distribution that has been calculated using a first probability distribution and a second probability distribution. The first probability distribution is calculated using at least a newest first feedback and a plurality of older first feedbacks, a first feedback indicating channel quality. The second probability distribution is calculated using at least a newest second feedback and a plurality of older second feedbacks, a second feedback indicating a success or failure of an earlier transmission transmitted from the apparatus.

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