公开(公告)号：US10893495B2

公开(公告)日：2021-01-12

申请号：US16778116

申请日：2020-01-31

Applicant: Nokia Technologies Oy

Inventor： Faycal Ait Aoudia ,  Jakob Hoydis

IPC: H04W56/00 ,  G06N3/04 ,  G06N3/08 ,  H04W72/04

Abstract: A method, apparatus, receiver and system provide timing synchronization during data transmission over a channel. In the context of a method, the method receives, for individual ones of a plurality of sequences of samples generated by a channel in response to transmission of corresponding frames that are comprised of a plurality of symbols including a preamble and one or more data symbols: (i) a probability vector and (ii) an indication of the sample of the respective sequence that corresponds to the particular symbol of the corresponding frame. The method determines one or more updated parameters of a frame detector of a receiver that receives the sequence of samples from the channel. The method determines one or more updated parameters of a preamble generator of a transmitter that provides the preamble for transmission over the channel.

公开(公告)号：US20200177418A1

公开(公告)日：2020-06-04

申请号：US16623072

申请日：2018-05-15

Applicant: Nokia Technologies Oy

Inventor： Jakob Hoydis ,  Sebastian Cammerer ,  Sebastian Dörner

IPC: H04L25/03 ,  G06N3/04 ,  G06N3/08 ,  H04L27/26 ,  H04L25/02

Abstract: A method and devices for configuring a data transmission network are disclosed. The method is for configuring a data transmission network, executed by a configuration device, wherein the data transmission network comprises at least one transmitter, at least one receiver with a communication channel between the transmitter and the receiver, the method comprising: training a machine learning model of the data transmission network, wherein the machine learning model comprises at least a transmitter model including a transmitter neural network, a channel model, and a receiver model including a receiver neural network by providing a message within a sequence of messages; generating a group of transmission symbols for each message in the sequence of messages using the transmitter neural network; concatenating the groups of transmission symbols together as a sequence of transmission symbols; simulating transmission of the sequence of transmission symbols over the communication channel using the channel model to the receiver; analysing a sequence of received symbols using the reception neural network to generate a decoded message; and updating the machine learning model based on an output of said reception neural network. In this way, the machine learning model can be trained using representative sequences of message, which improves performance when deployed in a real network.

公开(公告)号：US11949484B2

公开(公告)日：2024-04-02

申请号：US17628372

申请日：2019-09-03

Applicant: Nokia Technologies OY

Inventor： Faycal Ait Aoudia ,  Jakob Hoydis

IPC: H04B7/06 ,  G06N3/08

CPC classification number: H04B7/0639 ,  G06N3/08 ,  H04B7/0663

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.

公开(公告)号：US11895613B2

公开(公告)日：2024-02-06

申请号：US17286625

申请日：2018-10-19

Applicant: NOKIA TECHNOLOGIES OY

Inventor： Joerg Schaepperle ,  Luca Rose ,  Jakob Hoydis

IPC: H04W64/00

CPC classification number: H04W64/00

Abstract: A central node receives, from each of a plurality of access points providing access for user equipments to a communication network, a result of a measurement related to a position of a user equipment, receives additional information comprising at least one of an evaluation of the result of the measurement and a reference towards which the measurement was done, and calculates the position of the user equipment by combining the results of the measurements received from the plurality of access points using at least one of the evaluation and the reference.

公开(公告)号：US11848735B2

公开(公告)日：2023-12-19

申请号：US17316906

申请日：2021-05-11

Applicant: Nokia Technologies Oy

Inventor： Mathieu Goutay ,  Jakob Hoydis ,  Faycal Ait Aoudia

IPC: H04L5/04 ,  H04B7/06 ,  G06N20/00 ,  H04B7/0452

CPC classification number: H04B7/0634 ,  G06N20/00 ,  H04B7/0452

Abstract: An apparatus for optimization of signal shaping for a multi user multiple input multiple output, MU-MIMO, communication system, including circuitry configured for receiving a bit vector; and for determining a constellation vector, wherein the circuitry for determining the constellation vector includes a Geometric Shaping and Labeling Block, GSLB, for modulating the bit vector, wherein the GSLB is configured to implement an algorithm with one or more trainable parameters.

公开(公告)号：US11804860B2

公开(公告)日：2023-10-31

申请号：US17291477

申请日：2018-11-23

Applicant: NOKIA TECHNOLOGIES OY

Inventor： Jakob Hoydis ,  Faycal Ait Aoudia

IPC: H04B1/00 ,  G06N3/08 ,  H04B1/40 ,  G06N3/045

CPC classification number: H04B1/0003 ,  G06N3/045 ,  G06N3/08 ,  H04B1/40

Abstract: An apparatus, method and computer program performs initializing parameters of a transmission system. The transmission system comprises a transmitter, a first channel, a relay, a second channel and a receiver. The transmitter includes a transmitter algorithm having trainable weights, the relay includes a relay algorithm having trainable weights and the receiver includes a receiver algorithm having trainable weights. A first training sequence of messages is received, and the first training sequence of messages is sent from the transmitter to the relay using the first channel and is sent from the relay to the receiver using the second channel. A loss function is obtained or generated, and trainable parameters of the transmission system are updated based on the loss function. The trainable parameters include some of the trainable weights of the transmitter, some of the trainable weights of the relay, and some of the trainable weights of the receiver.

公开(公告)号：US11722240B2

公开(公告)日：2023-08-08

申请号：US17482610

申请日：2021-09-23

Applicant: NOKIA TECHNOLOGIES OY

Inventor： Faycal Ait Aoudia ,  Jakob Hoydis

IPC: H04L1/00 ,  H04L1/20 ,  H04W72/542

CPC classification number: H04L1/0003 ,  H04L1/206 ,  H04W72/542

Abstract: This specification describes an apparatus relating to rate adaptation. The apparatus may comprise a processor and a memory including instructions, the instructions, when executed by the processor, cause the apparatus to provide first data representing an estimate of a communications link based on a signal received over said communications link from a transmitter. The apparatus may determine an estimated achievable data rate over said communications link for each of a plurality of link configurations which have respective combinations of modulation scheme and pilot symbol pattern which correspond to one or more transmitter link configurations, the estimated achievable data rate for a particular link configuration being determined based on the first data, and the modulation scheme and the pilot pattern of the particular reference link configuration. The apparatus may select a transmitter link configuration based on the estimated achievable data rates.

公开(公告)号：US11651190B2

公开(公告)日：2023-05-16

申请号：US16757560

申请日：2017-10-23

Applicant: NOKIA TECHNOLOGIES OY

Inventor： Jakob Hoydis

IPC: G06N3/04 ,  G06N3/045 ,  G06N3/063 ,  H04L5/00 ,  H04L25/03 ,  H04L25/497 ,  G06F18/21 ,  G06N3/047

CPC classification number: G06N3/045 ,  G06F18/217 ,  G06N3/047 ,  G06N3/063 ,  H04L5/001 ,  H04L25/03165 ,  H04L25/497

Abstract: This specification relates to end-to-end learning in communication systems and describes: organising a plurality of transmitter neutral networks and a plurality of receiver neural networks into a plurality of transmitter-receiver neural network pairs, wherein a transmitter-receiver neural network pair is defined for each of a plurality of subcarrier frequency bands of a multi-carrier transmission system; arranging a plurality of symbols of the multi-carrier transmission system into a plurality of transmit blocks; mapping each of said transmit blocks to one of the transmitter-receiver neural network pairs; transmitting each symbol using the mapped transmitter-receiver neural network pair; and training at least some weights of the transmit and receive neural networks using a loss function for each transmitter-receiver neural network pair.

公开(公告)号：US11617183B2

公开(公告)日：2023-03-28

申请号：US17539661

申请日：2021-12-01

Applicant: NOKIA TECHNOLOGIES OY

Inventor： Mathieu Goutay ,  Faycal Ait Aoudia ,  Jakob Hoydis

IPC: H04W72/08 ,  H04B7/0452 ,  H04L25/02

Abstract: To provide demapping at a receiving side, a trained model for a demapper is used to output log-likelihood ratios of received signals representing data in a multi-user transmission. Inputs for the trained model for the demapper comprise a resource grid of equalized received signals.

公开(公告)号：US11556799B2

公开(公告)日：2023-01-17

申请号：US16959239

申请日：2018-01-02

Applicant: NOKIA TECHNOLOGIES OY

Inventor： Jakob Hoydis

IPC: G06N3/08 ,  G06F17/18 ,  G06N3/04 ,  H04L25/03

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.