Neural Augmentation For Device Nonlinearity Mitigation In X-Node Machine Learning

    公开(公告)号:US20220070041A1

    公开(公告)日:2022-03-03

    申请号:US17394928

    申请日:2021-08-05

    Abstract: Various embodiments include methods for reducing peak to average power ratio of wireless transmission waveforms, performed in transmitter circuitry of a wireless communication. Various embodiments may include receiving frequency domain data tones, transforming the frequency domain data tones to time domain data signals, generating, using a set of peak reduction tone (PRT) neural networks, time domain PRTs using the time domain data signals in which the set of PRT neural networks have been trained in conjunction with an augmentation neural network, and a receiver neural network, generating an output of the augmentation neural network based on an input of final combined time domain signals including the time domain PRTs combined with previous combined time domain signals, and generating time domain wireless transmission waveforms that include the output of the augmentation neural network combined with the final combined time domain signals.

    TONE RESERVATION FOR PEAK TO AVERAGE POWER RATIO REDUCTION

    公开(公告)号:US20210344536A1

    公开(公告)日:2021-11-04

    申请号:US17306759

    申请日:2021-05-03

    Abstract: Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment may receive a resource allocation indicating a set of transmission tones comprising a set of data tones and a set of peak reduction tones (PRTs), wherein the resource allocation indicates locations for the set of data tones and locations for the set of PRTs within a particular bandwidth, wherein the locations for the set of PRTs are arranged relative to the locations for the set of data tones according to a PRT sequence, and wherein the PRT sequence comprises a plurality of contiguous PRTs arranged relative to a plurality of contiguous data tones or a pseudo-random pattern generated using a pseudo-random number generator; and transmit a data transmission using a waveform based at least in part on the resource allocation. Numerous other aspects are provided.

    NEURAL NETWORK CONFIGURATION FOR WIRELESS COMMUNICATION SYSTEM ASSISTANCE

    公开(公告)号:US20210185515A1

    公开(公告)日:2021-06-17

    申请号:US17122117

    申请日:2020-12-15

    Abstract: Methods, systems, and devices for wireless communications are described. Generally, the described techniques provide for communicating capability information (e.g., regarding neural network blocks supported by a user equipment (UE) and a base station). A base station may configure one or more neural network block parameters, and may transmit the neural network block parameters to the UE. The UE may configure or reconfigure a neural network block according to the neural network block parameters, and may process one or more signals, e.g., baseband signals, generated by the UE using the neural network block and the neural network block parameters.

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