LEARNING IN COMMUNICATION SYSTEMS
    31.
    发明申请

    公开(公告)号:US20210099327A1

    公开(公告)日:2021-04-01

    申请号:US17044553

    申请日:2018-06-29

    Abstract: A method, apparatus and computer program are described includes obtaining or generating a transmitter-training sequence of messages for a first transmitter of a first module of a transmission system, wherein the transmission system includes the first module having the first transmitter and a first receiver, a second module having a second transmitter and a second receiver, and a channel, wherein the first transmitter includes a transmitter algorithm having at least some trainable weights; transmitting a perturbed version of the transmitter-training sequence of messages from the first transmitter to the second receiver over the channel of the transmission system; receiving a first loss function at the first receiver from the second transmitter, wherein the first loss function is based on the transmitted perturbed versions of the transmitter-training sequence of messages as received at the second receiver and knowledge of the transmitter-training sequence of messages for the first transmitter of the transmission system; and training at least some weights of the transmitter algorithm of the first transmitter based on the first loss function.

    CHANNEL MODELLING IN A DATA TRANSMISSION SYSTEM

    公开(公告)号:US20200334542A1

    公开(公告)日:2020-10-22

    申请号:US16959239

    申请日:2018-01-02

    Inventor: Jakob HOYDIS

    Abstract: Apparatuses, systems and methods are described including: converting generator inputs to a generator output vector using a generator, wherein the generator is a model of a channel of a data transmission system and wherein the generator comprises a generator neural network; selectively providing either the generator output vector or an output vector of the channel of the data transmission system to an input of a discriminator, wherein the discriminator comprises a discriminator neural network; using the discriminator to generate a probability indicative of whether the discriminator input is the channel output vector or the generator output vector; and training at least some weights of the discriminator neural network using a first loss function and training at least some weights of the generator neural network using a second loss function in order to improve the accuracy of the model of the channel.

    COMMUNICATION SYSTEM
    33.
    发明公开

    公开(公告)号:US20230188394A1

    公开(公告)日:2023-06-15

    申请号:US17926043

    申请日:2021-05-19

    CPC classification number: H04L27/2601 G06N20/00

    Abstract: A communications system and method is described comprising: handshaking between a transmitter and a receiver of the communication system to initiate a training procedure, wherein said handshaking comprises a training setup request message comprising parameters for the training procedure, wherein the transmitter comprises trainable parameters and/or the receiver comprises trainable parameters; receiving identified training data from the transmitter at the receiver, wherein the training data comprises transmitter training data and/or receiver training data; sending training information from the receiver to the transmitter, wherein the training information comprises information for controlling training at the transmitter and/or the receiver; and terminating the training procedure.

    SIGNAL DEMAPPING
    34.
    发明申请

    公开(公告)号:US20220286181A1

    公开(公告)日:2022-09-08

    申请号:US17628372

    申请日:2019-09-03

    Abstract: In one embodiment, a trainable logic includes determination logic configured to determine a plurality of available receiver configurations and associate each receiver configuration with a context matrix; codebook logic configured to select a quantisation codebook to be used by the trainable logic for the context matrices; and learning logic configured to learn from a training dataset including a plurality of received signal samples relevant to reconstruction of a transmitted message. The learning logic is configured to generate, from the training dataset, a set of superposed parameters and context matrices corresponding to the plurality of available receiver configurations and a set of contextual parameters for each context; quantize the context matrices according to the quantisation codebook; and repeat the generation of superposed parameters, context matrices and quantization of context matrices until a stop criterion is met.

    LEARNING IN COMMUNICATION SYSTEMS
    35.
    发明申请

    公开(公告)号:US20220247614A1

    公开(公告)日:2022-08-04

    申请号:US17613578

    申请日:2019-05-30

    Abstract: An apparatus, method and computer program is described comprising: initialising trainable parameters of a transmission system having a transmitter, a channel and a receiver; generating training symbols on the basis of a differentiable distribution function; transmitting modulated training symbols to the receiver over the channel in a training mode; generating a loss function based on the generated training symbols and the modulated training symbols as received at the receiver of the transmission system; and generating updated parameters of the transmission system in order to minimise the loss function.

    Training in Communication Systems
    36.
    发明申请

    公开(公告)号:US20220083870A1

    公开(公告)日:2022-03-17

    申请号:US17421462

    申请日:2019-01-18

    Abstract: An apparatus, method and computer program is described including evaluating some or all of a current population of algorithms according to a metric, each algorithm of the population implementing a transmission system; selecting a subset of the algorithms of the current population based on the metric; generating an updated population of algorithms from said subset; and repeating the evaluating, selecting and generating, based on the updated population, until a first condition is reached.

    END-TO-END LEARNING IN COMMUNICATION SYSTEMS

    公开(公告)号:US20210374529A1

    公开(公告)日:2021-12-02

    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.

    LEARNING IN COMMUNICATION SYSTEMS BY UPDATING OF PARAMETERS IN A RECEIVING ALGORITHM

    公开(公告)号:US20210306092A1

    公开(公告)日:2021-09-30

    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:US20210201135A1

    公开(公告)日:2021-07-01

    申请号:US17044607

    申请日:2018-04-03

    Abstract: An apparatus and method is described including obtaining or generating a transmitter-training sequence of messages for a transmission system, wherein the transmission system includes 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; transmitting perturbed versions of the transmitter-training sequence of messages over the transmission system; receiving first receiver loss function data at the transmitter, the first receiver loss function data being generated based on a received-training sequence as received at the receiver and knowledge of the transmitter training sequence of messages for the transmission system; and training at least some weights of the transmitter algorithm based on first receiver loss function data and knowledge of the transmitter-training sequence of messages and the perturbed versions of the transmitter-training sequence of messages.

    Method and Apparatus for Signal Detection in Wireless Communication System

    公开(公告)号:US20210099207A1

    公开(公告)日:2021-04-01

    申请号:US17046332

    申请日:2018-04-11

    Abstract: Embodiments of the present disclosure relate to methods, apparatuses and computer program products for signal detection in a wireless communication system. A method implemented at a receiver device includes obtaining a set of received signals; determining a channel matrix via which the set of received signals have been transported; and detecting the set of received signals in a staged manner, wherein in a stage, the method includes detecting the set of received signals, based on the channel matrix and a detection algorithm for the stage; fixing one or more of detected symbols output from the detecting algorithm for the stage; and updating the channel matrix and the set of received signals for usage by a next stage, based on the one or more of the detected symbols that are fixed in the stage.

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