Channel estimation by inference on Gaussian Markov random fields

Thomas J. Riedl, Jun Won Choi, Andrew C. Singer

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

Abstract

In this paper, we discuss a novel method for channel estimation. The approach is based on the idea of modeling the complex channel gains by a Markov random field. This graphical model is used to capture the statistical dependencies between consecutive taps in time and delay. The sum-product algorithm is finally employed to infer a MAP channel estimate from given observations.

Original languageEnglish (US)
Title of host publicationConference Record - 43rd Asilomar Conference on Signals, Systems and Computers
Pages1007-1011
Number of pages5
DOIs
StatePublished - 2009
Event43rd Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: Nov 1 2009Nov 4 2009

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other43rd Asilomar Conference on Signals, Systems and Computers
CountryUnited States
CityPacific Grove, CA
Period11/1/0911/4/09

Keywords

  • Channel estimation
  • Channel modeling
  • Gaussian message passing
  • Markov random field

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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