公开(公告)号：US12261720B2

公开(公告)日：2025-03-25

申请号：US18300539

申请日：2023-04-14

Applicant: Nokia Solutions and Networks Oy

Inventor： Axel Van Damme ,  Nicolas Dupuis ,  Philippe Dierickx ,  Olivier Delaby

IPC: H04L25/02

Abstract: In one embodiment, the method includes obtaining channel response data including a first channel frequency response of a channel over a first frequency spectrum, where the first channel frequency response is generated in response to a transmission over the channel or a simulation thereof; and generating an estimate of a second channel frequency response of the channel over a second frequency spectrum in response to applying the channel response data to a machine-learning model, where the second frequency spectrum is different to the first frequency spectrum.

公开(公告)号：US11089150B2

公开(公告)日：2021-08-10

申请号：US16639197

申请日：2018-08-28

Applicant: Nokia Solutions and Networks Oy

Inventor： Philippe Dierickx ,  Benoit Drooghaag

IPC: H04M3/30 ,  H04M3/08 ,  H04M3/22

Abstract: The method includes obtaining a loop length of a terminal section of the communication line; determining whether there is an impairment in the communication line; if no impairment, classifying the communication line into the first group; if impairment is determined, perform obtaining a location of the impairment in the communication line; determining whether the impairment is located in the terminal section of the communication line based on the loop length; if so, classifying the communication line into a second group; else, classifying the communication line into the first group; wherein, in the first group, it is qualified for an new broadband communication service, and if in the second group, it is not qualified, and wherein, the new broadband communication service is to be deployed over the terminal section of the communication line.

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：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.