Sparsifying dictionary analysis for FIR MIMO channel-shortening equalizers

Abubakr O. Al-Abbasi, Ridha Hamila, Waheed U. Bajwa, Naofal Al-Dhahir

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In this paper, we propose a general framework that transforms the problems of designing sparse finite-impulse response channel-shortening equalizers and target impulse response filters for multiple antenna systems into the problems of sparsest-approximation of a vector in different dictionaries. Additionally, we compare several choices of the sparsifying dictionaries in terms of the worst-case coherence metric, which determines their sparsifying effectiveness. Furthermore, a reduced complexity design approach is proposed, which is realized by exploiting the asymptotic equivalence of Toeplitz and circulant matrices. Finally, the significance of our proposed approach is demonstrated through numerical experiments.

Original languageEnglish (US)
Title of host publicationSPAWC 2016 - 17th IEEE International Workshop on Signal Processing Advances in Wireless Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509017492
DOIs
StatePublished - Aug 9 2016
Event17th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2016 - Edinburgh, United Kingdom
Duration: Jul 3 2016Jul 6 2016

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
Volume2016-August

Other

Other17th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2016
Country/TerritoryUnited Kingdom
CityEdinburgh
Period7/3/167/6/16

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Information Systems

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