On the sparsity-aware partial-update NLMS algorithms for UWB channel estimation

Solomon Nunoo, Razali Ngah, Uche A.K. Chude-Okonkwo, Olakunle Elijah, Igbafe Orikumhi, Chee Yen Leow

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

Abstract

Partial updating of filter coefficients is an effective method for reducing computational load and power consumption in adaptive filter implementation. In this paper, we present a class of MMax partial update NLMS algorithms suitable for estimating UWB channels, whose characteristics have shown to vary between highly sparse and dense depending on the channel environment under consideration and the measured bandwidth. Simulation results show improved performance of the proposed algorithms in terms of convergence speed, and computational complexity.

Original languageEnglish
Title of host publicationIEEE 2015 International Conference on Signal and Image Processing Applications, ICSIPA 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages326-331
Number of pages6
ISBN (Electronic)9781479989966
DOIs
Publication statusPublished - 17 Feb 2016
Externally publishedYes
Event4th IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2015 - Kuala Lumpur, Malaysia
Duration: 19 Oct 201521 Oct 2015

Publication series

NameIEEE 2015 International Conference on Signal and Image Processing Applications, ICSIPA 2015 - Proceedings

Conference

Conference4th IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2015
Country/TerritoryMalaysia
CityKuala Lumpur
Period19/10/1521/10/15

Keywords

  • compressive sensing
  • NLMS algorithm
  • sparse channel estimation
  • ultra wideband

ASJC Scopus subject areas

  • Computer Science Applications
  • Signal Processing

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