Linear detection via belief propagation

Danny Bickson, Danny Dolev, Ori Shenta, Paul H. Siegel, Jack K. Wolf

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

15 Scopus citations

Abstract

In this paper , the paradigm of linear detection is reformulated as a Gaussian belief propagation (GaBP) scheme , without resorting to direct matrix inversion. The derived Iterative framework allows for a distributed message-passing implementa-tion of this Important class of sub-optimal tractable estimators. The properties of GaBP-based linear detection are addressed , while its faster convergence , in comparison with conventional Iterative solution methods , Is demonstrated experimentally.

Original languageEnglish
Title of host publication45th Annual Allerton Conference on Communication, Control, and Computing 2007
PublisherUniversity of Illinois at Urbana-Champaign, Coordinated Science Laboratory and Department of Computer and Electrical Engineering
Pages1207-1213
Number of pages7
ISBN (Electronic)9781605600864
StatePublished - 2007
Event45th Annual Allerton Conference on Communication, Control, and Computing 2007 - Monticello, United States
Duration: 26 Sep 200728 Sep 2007

Publication series

Name45th Annual Allerton Conference on Communication, Control, and Computing 2007
Volume2

Conference

Conference45th Annual Allerton Conference on Communication, Control, and Computing 2007
Country/TerritoryUnited States
CityMonticello
Period26/09/0728/09/07

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