Efficient iterative decoding of LDPC in the presence of strong phase noise

Shachar Shayovitz, Dan Raphaeli

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

Abstract

In this paper we propose a new efficient message passing algorithm for decoding LDPC transmitted over a channel with strong phase noise. The algorithm performs approximate bayesian inference on a factor graph representation of the channel and code joint posterior. The approximate inference is based on an improved canonical model for the messages of the Sum & Product Algorithm, and a method for clustering the messages using the directional statistics framework. The proposed canonical model includes treatment for phase slips which can limit the performance of tracking algorithms. We show simulation results and complexity analysis for the proposed algorithm demonstrating its superiority over some of the current state of the art algorithms.

Original languageEnglish
Title of host publication2012 7th International Symposium on Turbo Codes and Iterative Information Processing, ISTC 2012
Pages1-5
Number of pages5
DOIs
StatePublished - 2012
Event2012 7th International Symposium on Turbo Codes and Iterative Information Processing, ISTC 2012 - Gothenburg, Sweden
Duration: 27 Aug 201231 Aug 2012

Publication series

NameInternational Symposium on Turbo Codes and Iterative Information Processing, ISTC
ISSN (Print)2165-4700
ISSN (Electronic)2165-4719

Conference

Conference2012 7th International Symposium on Turbo Codes and Iterative Information Processing, ISTC 2012
Country/TerritorySweden
CityGothenburg
Period27/08/1231/08/12

Keywords

  • Tikhonov
  • directional statistics
  • factor graph
  • moment matching
  • phase noise
  • phase slip

Fingerprint

Dive into the research topics of 'Efficient iterative decoding of LDPC in the presence of strong phase noise'. Together they form a unique fingerprint.

Cite this