Channel estimation using gaussian approximation in a factor graph for QAM modulation

Yang Liu, Loïc Brunel, Joseph Boutros

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

Abstract

Joint channel estimation and decoding using belief propagation on factor graphs requires the quantization of probability densities since continuous parameters are involved. We propose to replace these densities by standard messages where the channel estimate is accurately modeled as a Gaussian mixture. Upward messages include symbol extrinsic information and downward messages carry a mean and a variance for the Gaussian modeled channel estimate. Such unquantized message propagation leads to a complexity reduction and a performance improvement. For QAM modulated symbols, the proposed belief propagation almost achieves the performance of Expectation- Maximization under good initialization and surpasses it under bad initialization.

Original languageEnglish
Title of host publication2008 IEEE Global Telecommunications Conference, GLOBECOM 2008
Pages4846-4850
Number of pages5
DOIs
Publication statusPublished - 1 Dec 2008
Event2008 IEEE Global Telecommunications Conference, GLOBECOM 2008 - New Orleans, LA, United States
Duration: 30 Nov 20084 Dec 2008

Other

Other2008 IEEE Global Telecommunications Conference, GLOBECOM 2008
CountryUnited States
CityNew Orleans, LA
Period30/11/084/12/08

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ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Liu, Y., Brunel, L., & Boutros, J. (2008). Channel estimation using gaussian approximation in a factor graph for QAM modulation. In 2008 IEEE Global Telecommunications Conference, GLOBECOM 2008 (pp. 4846-4850). [4698703] https://doi.org/10.1109/GLOCOM.2008.ECP.928