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    MACHINE LEARNING-BASED LINK ADAPTATION
    1.
    发明申请
    MACHINE LEARNING-BASED LINK ADAPTATION 有权

    公开(公告)号：US20210218483A1

    公开(公告)日：2021-07-15

    申请号：US17252976

    申请日：2018-09-28

    Applicant: Intel Corporation

    Inventor： Xiaoran Fang ,  Matthew Hayes ,  John P. Hogan ,  Shoujiang Ma ,  Mehrzad Malmirchegini ,  Rongzhen Yang ,  Hujun Yin

    IPC: H04B17/336 ,  H04W24/08 ,  H04L1/00

    Abstract: Aspects for machine learning-based link adaptation are described. For example, an apparatus can determine k-nearest neighbors (K-NNs) based on training data associated with the sub-band and on the signal to interference and noise ratio (SINR) of the sub-band. In aspects, the apparatus can identify a channel quality indicator (CQI) associated with the lowest error rate for the k-NNs and provide the identified CQI to a base station. In aspects, a neural network (NN) can provide labels for CQIs that indicate probability of choosing a CQI, and the CQI having highest probability will be provided to a base station. In aspects, a covariance matrix based on samples of a communication channel can be provided to a NN to determine a rank indicator (RI) corresponding to the channel, and channel state information associated with the (RI) can be sent to the base station. Other aspects are described.

    IMAGE COMPRESSION USING AUTOENCODER INFORMATION
    5.
    发明申请
    IMAGE COMPRESSION USING AUTOENCODER INFORMATION 有权

    公开(公告)号：US20210120255A1

    公开(公告)日：2021-04-22

    申请号：US17133192

    申请日：2020-12-23

    Applicant: Intel Corporation

    Inventor： Xiaoran Fang ,  Zheng Gao ,  Hujun Yin ,  Rongzhen Yang

    IPC: H04N19/29 ,  H04N19/146 ,  G06T3/40

    Abstract: Methods, apparatus, systems, and articles of manufacture for image compression using autoencoder information are disclosed. An example apparatus disclosed herein includes a pre-compressor to compress an input scaled image to generate a fundamental bitstream and a reconstructed scaled image. The disclosed example apparatus also includes an autoencoder to encode a residual of a reconstructed image to generate a side information bitstream, the reconstructed image based on the reconstructed scaled image. The disclosed example apparatus further includes a bitstream merger to combine the fundamental bitstream and the side information bitstream to generate an output compressed bitstream.

    Machine learning-based link adaptation
    6.
    发明授权
    Machine learning-based link adaptation 有权

    公开(公告)号：US11637643B2

    公开(公告)日：2023-04-25

    申请号：US17252976

    申请日：2018-09-28

    Applicant: Intel Corporation

    Inventor： Xiaoran Fang ,  Matthew Hayes ,  John P. Hogan ,  Shoujiang Ma ,  Mehrzad Malmirchegini ,  Rongzhen Yang ,  Hujun Yin

    IPC: H04B17/336 ,  H04L1/00 ,  H04W24/08

    Abstract: Aspects for machine learning-based link adaptation are described. For example, an apparatus can determine k-nearest neighbors (K-NNs) based on training data associated with the sub-band and on the signal to interference and noise ratio (SINR) of the sub-band. In aspects, the apparatus can identify a channel quality indicator (CQI) associated with the lowest error rate for the k-NNs and provide the identified CQI to a base station. In aspects, a neural network (NN) can provide labels for CQIs that indicate probability of choosing a CQI, and the CQI having highest probability will be provided to a base station. In aspects, a covariance matrix based on samples of a communication channel can be provided to a NN to determine a rank indicator (RI) corresponding to the channel, and channel state information associated with the (RI) can be sent to the base station. Other aspects are described.

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