Receiver for a communication system

    公开(公告)号:US12040857B2

    公开(公告)日:2024-07-16

    申请号:US17795620

    申请日:2020-01-29

    CPC classification number: H04B7/0456 H04L25/03006 H04L2025/03426

    Abstract: The present subject matter relates to a receiver including a detector for receiving a signal from a transmitter. The detector includes a set of one or more settable parameters, and circuitry configured for implementing an algorithm having trainable parameters. The algorithm is configured to receive as input information indicative of a status of a communication channel between the transmitter and the receiver and to output values of the set of settable parameters of the detector. The detector is configured to receive a signal corresponding to a message sent by the transmitter and to provide an output indicative of the message based on the received signal and the output values of the set of settable parameters of the detector.

    Learning in communication systems by updating of parameters in a receiving algorithm

    公开(公告)号:US11552731B2

    公开(公告)日:2023-01-10

    申请号:US17260441

    申请日:2018-07-20

    Abstract: An apparatus, method and computer program is described comprising receiving data at a receiver of a transmission system; using a receiver algorithm to convert data received at the receiver into an estimate of the first coded data, the receiver algorithm having one or more trainable parameters; generating an estimate of first data bits by decoding the estimate of the first coded data, said decoding making use of an error correction code of said encoding of the first data bits; generating a refined estimate of the first coded data by encoding the estimate of the first data bits; generating a loss function based on a function of the refined estimate of the first coded data and the estimate of the first coded data; updating the trainable parameters of the receiver algorithm in order to minimise the loss function; and controlling a repetition of updating the trainable parameters by generating, for each repetition, for the same received data, a further refined estimate of the first coded data, a further loss function and further updated trainable parameters.

    End-to-end learning in communication systems

    公开(公告)号:US12159228B2

    公开(公告)日:2024-12-03

    申请号:US17277105

    申请日:2018-09-25

    Abstract: An apparatus, method and computer program is described comprising: initialising parameters of a transmission system, wherein the transmission system comprises a transmitter, a channel and a receiver, wherein the transmitter includes a transmitter algorithm having at least some trainable weights and the receiver includes a receiver algorithm having at least some trainable weights; updating trainable parameters of the transmission system based on a loss function, wherein the trainable parameters include the trainable weights of the transmitter and the trainable weights of the receiver and wherein the loss function includes a penalty term; quantizing said trainable parameters, such that said weights can only take values within a codebook having a finite number of entries that is a subset of the possible values available during updating; and repeating the updating and quantizing until a first condition is reached.

    Iterative detection in a communication system

    公开(公告)号:US12107679B2

    公开(公告)日:2024-10-01

    申请号:US17594511

    申请日:2019-04-29

    CPC classification number: H04L1/005 G06N3/08 H04L1/1607

    Abstract: An apparatus, computer program and method is described including receiving data at a receiver of a communication system, generating an estimate of the data as transmitted by a transmitter of the transmission system (wherein generating the estimate includes a receiver algorithm having at least some trainable weights), generating a refined estimate of the transmitted data, based on said estimate and an error correction algorithm (wherein, in an operational mode, said estimate of the data as transmitted is generated based on the received data and said refined estimate); and generating, in the operational mode, a revised estimate of the transmitted data on each of a plurality of iterations of said generating an estimate of the transmitted data until a first condition is reached.

    Machine-learning-based detection and reconstruction from low-resolution samples

    公开(公告)号:US11139866B2

    公开(公告)日:2021-10-05

    申请号:US17135748

    申请日:2020-12-28

    Abstract: According to an aspect, there is provided an apparatus comprising a combiner for combining a received analog signal with an analog dithering signal to produce a combined analog signal, a one-bit analog-to-digital converter for converting the combined analog signal to a combined digital signal, means for performing joint downsampling and feature extraction for the combined digital signal, means for implementing a trained machine-learning algorithm for calculating one or more input parameters for waveform generation at least based on one or more features extracted from the combined digital signal and a parametric waveform generator for generating the analog dithering signal based on the one or more input parameters.

    Communication system having a configurable modulation order and an associated method and apparatus

    公开(公告)号:US11082149B2

    公开(公告)日:2021-08-03

    申请号:US16905569

    申请日:2020-06-18

    Abstract: A method, apparatus, receiver and system provide for configurability of the modulation order of a communications system, such as an autoencoder-based communication system. With respect to a system including a transmitter and a receiver, the transmitter encodes a message into a vector of channel symbols for transmission via a channel. The message is encoded pursuant to a modulation order m that is adjustable up to a maximum modulation order Mmax. The receiver receives a vector of samples generated by the channel and determines a first prediction vector for the message encoded by the transmitter. The receiver includes a slicing layer to eliminate one or more elements of the first prediction vector if the modulation order m is less than the maximum modulation order Mmax so as to generate a second prediction vector tailored to the modulation order from which a prediction of the message encoded by the transmitter is identified.

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