公开(公告)号：US12143166B2

公开(公告)日：2024-11-12

申请号：US17874715

申请日：2022-07-27

Applicant: Nokia Solutions and Networks Oy

Inventor： Axel Van Damme ,  Nicolas Dupuis ,  Philippe Dierickx

IPC: H04B17/391

Abstract: An apparatus, method and computer program is described comprising: combining first features extracted from an echo signal using a convolutional encoder of a convolutional encoder-decoder having first weights, wherein the echo signal is obtained in response to a transmission over a channel or a simulation thereof; and using a convolutional decoder of the convolutional encoder-decoder to generate an estimate of a frequency response of the channel based on the echo signal, wherein the convolutional decoder has second weights.

公开(公告)号：US11996907B2

公开(公告)日：2024-05-28

申请号：US17858882

申请日：2022-07-06

Applicant: Nokia Solutions and Networks Oy

Inventor： Olivier Delaby ,  Nicolas Dupuis ,  Axel Van Damme

IPC: H04B3/48 ,  H04B3/487 ,  H04B17/10

CPC classification number: H04B3/48 ,  H04B3/487 ,  H04B17/101

Abstract: Embodiments of the present disclosure relate to an apparatus including means configured to perform: obtaining a measured channel frequency response, and a measured noise power spectral density for a line of a wired network susceptible to an impairment; deriving, in case of an indication of an impairment present on the line, from the measured channel frequency response and the measured noise power spectral density, a first theoretical noise representation for the line with the impairment and a second theoretical noise representation for the line without the impairment; and determining information indicative of a location of the impairment in the line, by processing the measured noise power spectral density, the first theoretical noise representation, and the second theoretical noise representation with a neural network.

公开(公告)号：US11909908B2

公开(公告)日：2024-02-20

申请号：US17142377

申请日：2021-01-06

Applicant: Nokia Solutions and Networks Oy

Inventor： Nicolas Dupuis ,  Gert-Jan Stockman ,  Philippe Dierickx ,  Paschalis Tsiaflakis

IPC: H04M3/30 ,  H04M1/24 ,  H04B3/493 ,  H04M3/22 ,  H04B3/23 ,  G06N3/008 ,  H04B3/20

CPC classification number: H04M3/306 ,  H04B3/23 ,  H04B3/493 ,  H04M1/24 ,  H04M3/22 ,  G06N3/008 ,  H04B3/20

Abstract: Embodiments relate to an apparatus comprising means configured for:



obtaining echo response data representative of the echo response of a communication line, wherein the echo response data specifies the echo response based on two dimensions and includes first dimension data and second dimension data,
determining at least one property of the communication line based on processing the echo response data with a neural network, wherein the neural network comprises at least:

a first convolutional branch for processing the first dimension data,
a second convolutional branch for processing the second dimension data,
a dense part for processing the outputs of the first and second convolutional branches.

公开(公告)号：US10812206B2

公开(公告)日：2020-10-20

申请号：US16734645

申请日：2020-01-06

Applicant: Nokia Solutions and Networks Oy

Inventor： Nicolas Dupuis ,  Philippe Dierickx

IPC: H04B17/30 ,  H04B17/373 ,  G06N20/00 ,  H04B3/46

Abstract: Embodiments relate to a method and an apparatus for predicting the bitrate of a repaired communication channel. The method may include, generating a dataset specifying, for a plurality of communication channels, a channel frequency response of a communication channel affected by an impairment, and a channel frequency response of the communication channel non-affected by the impairment, training, based on the dataset, a machine learning model configured to predict a channel frequency response of the repaired communication channel based on the channel frequency response of the communication channel affected by an impairment.

公开(公告)号：US11929790B2

公开(公告)日：2024-03-12

申请号：US17222180

申请日：2021-04-05

Applicant: Nokia Solutions and Networks Oy

Inventor： Nicolas Dupuis ,  Axel Van Damme

IPC: H04B3/32 ,  H04B3/487 ,  H04B17/345

CPC classification number: H04B3/32 ,  H04B3/487 ,  H04B17/345

Abstract: A system for diagnosing noise impacting impairments affecting a Digital Subscriber Line includes at least one processor and at least one memory storing instructions. The at least one memory and the instructions configured to, with the at least one processor, cause the system at least to, receive noise sequences for said Digital Subscriber Line; detect noise symptoms in said noise sequences and identify noise impacting impairments associated with said noise symptoms using a trained machine learning model; and determine an impact on said Digital Subscriber Line of a plurality of noise impacting impairments.

公开(公告)号：US11146344B2

公开(公告)日：2021-10-12

申请号：US16259069

申请日：2019-01-28

Applicant: Nokia Solutions and Networks OY

Inventor： Nicolas Dupuis ,  Axel Van Damme

IPC: H04B17/309 ,  G06N3/08 ,  H04L12/24 ,  H04L12/26 ,  H04B3/54 ,  H04M3/30

Abstract: Embodiments relate to an apparatus for monitoring a telecommunication network including one or more telecommunication channels. The apparatus includes a processor configured after executing computer code to design a convolutional neural network configured for determining an impairment type of a telecommunication channel as a function of a channel frequency response of the telecommunication channel, by selecting at least one of a number of convolutional layers, a number of filters for respective convolutional layers, and/or a size of filters for respective convolutional layers; and train the convolutional neural network based on training data specifying, for respective telecommunication channels, a channel frequency response and an associated impairment type.

公开(公告)号：US10938981B2

公开(公告)日：2021-03-02

申请号：US16857485

申请日：2020-04-24

Applicant: Nokia Solutions and Networks Oy

Inventor： Nicolas Dupuis ,  Axel Van Damme

IPC: H04M3/22 ,  G06N20/00 ,  H04M3/26 ,  G06N3/08

Abstract: The apparatus includes a memory configured to store executable code; and a processor configured to execute the executable code and cause the apparatus to perform the operations of generating and training. The generating generates a dataset specifying, for a plurality of communication lines, i) a channel frequency response of a communication line having one or two bridged taps, and ii) a set of M lengths of bridged taps associated with the communication line, with M greater than one. The training trains, based on the dataset, a machine learning model, the machine learning model configured for determining, based on the channel frequency response of a communication line, a set of M lengths of bridged taps associated with the communication line.