MACHINE LEARNING FOR ADDRESSING TRANSMIT (Tx) NON-LINEARITY

    公开(公告)号:US20210266875A1

    公开(公告)日:2021-08-26

    申请号:US17181927

    申请日:2021-02-22

    Abstract: A method of wireless communication by a transmitting device transforms a transmit waveform by an encoder neural network to control power amplifier (PA) operation with respect to non-linearities. The method also transmits the transformed transmit waveform across a propagation channel. A method of wireless communication by a receiving device receives a waveform transformed by an encoder neural network. The method also recovers, with a decoder neural network, the encoder input symbols from the received waveform. A transmitting device for wireless communication calculates distortion error based on a non-distorted digital transmit waveform and a distorted digital transmit waveform. The transmitting device also compresses the distortion error with an encoder neural network of an auto-encoder. The transmitting device transmits to a receiving device the compressed distortion error to compensate for power amplifier (PA) non-linearity.

    Method To Convey The TX Waveform Distortion To The Receiver

    公开(公告)号:US20210266203A1

    公开(公告)日:2021-08-26

    申请号:US16914011

    申请日:2020-06-26

    Abstract: Various embodiments may employ neural networks at transmitting devices to compress transmit (TX) waveform distortion. In various embodiments, compressed TX waveform distortion information may be conveyed to a receiving device. In various embodiments, the signaling of TX waveform distortion information from a transmitting device to a receiving device may enable a receiving device to mitigate waveform distortion in a transmit waveform received from the transmitting device. Various embodiments include systems and methods of wireless communication by transmitting a waveform to a receiving device performed by a processor of a transmitting device. Various embodiments include systems and methods of wireless communication by receiving a waveform from a transmitting device performed by a processor of a receiving device.

    GRADIENT FEEDBACK FRAMEWORK FOR JOINT TRANSCEIVER NEURAL NETWORK TRAINING

    公开(公告)号:US20210264255A1

    公开(公告)日:2021-08-26

    申请号:US16918782

    申请日:2020-07-01

    Abstract: A method of wireless communication performed by a receiving device includes determining a transmission reference point value and determining a transmission reference point gradient of a loss based on the transmission reference point value. The receiving device also transmits a message comprising the transmission reference point gradient to a transmitting device. A method of wireless communication by a transmitting device includes receiving a transmission reference point gradient of a loss from a receiving device. The transmitting device determines a transmission point-payload gradient of a transmission reference point value with respect to an encoded value generated by a transmitter neural network. The transmitting device also determines a payload gradient of the loss based on a product of the transmission reference point gradient and the transmission point-payload gradient. The transmitting device further updates weights of the transmitter neural network based on the payload gradient.

    UE-BASED POSITIONING
    228.
    发明申请

    公开(公告)号:US20210160812A1

    公开(公告)日:2021-05-27

    申请号:US16846301

    申请日:2020-04-11

    Abstract: A method of determining a location of a user equipment includes: obtaining, at the user equipment, a position-determination model associated with a coarse location of the user equipment; determining one or more first positioning measurements at the user equipment; and determining, at the user equipment, the location of the user equipment based on the one or more first positioning measurements and the position-determination model.

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