Gigabit DSL: A Deep-LMS approach

Avi Zanko, Itsik Bergel, Amir Leshem

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


In this paper we present the Deep-LMS, a novel algorithm for crosstalk cancellation in DSL. The Deep-LMS crosstalk canceler uses an adaptive non-diagonal preprocessing matrix prior to a conventional LMS crosstalk canceler. The role of the preprocessing matrix is to speed-up the convergence of the conventional LMS crosstalk canceler and hence speed-up the convergence of the overall system. The update of the preprocessing matrix is inspired by deep neural networks. However, since all the operations in the Deep-LMS algorithm are linear, we are capable of providing an exact convergence speed analysis. The Deep-LMS is important for crosstalk cancellation in the novel standard, where traditional LMS converges very slowly due to the large bandwidth. Simulation results support our analysis and show significant reduction in convergence time compared to existing LMS variants.

Original languageAmerican English
Title of host publication2016 24th European Signal Processing Conference, EUSIPCO 2016
PublisherEuropean Signal Processing Conference, EUSIPCO
Number of pages5
ISBN (Electronic)9780992862657
StatePublished - 28 Nov 2016
Externally publishedYes
Event24th European Signal Processing Conference, EUSIPCO 2016 - Budapest, Hungary
Duration: 28 Aug 20162 Sep 2016

Publication series

NameEuropean Signal Processing Conference
ISSN (Print)2219-5491


Conference24th European Signal Processing Conference, EUSIPCO 2016

Bibliographical note

Publisher Copyright:
© 2016 IEEE.


  • Crosstalk canceler
  • DSL
  • LMS


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