Channel Estimation Using Gaussian Approximation in a Factor Graph for QAM Modulation Conference Paper

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. 2008 IEEE.

name of conference

• IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference

authors

• Boutros, Joseph

published proceedings

• GLOBECOM 2008 - 2008 IEEE GLOBAL TELECOMMUNICATIONS CONFERENCE

author list (cited authors)

• Liu, Y., Brunel, L., & Boutros, J. J.

citation count

• 0

complete list of authors

• Liu, Yang||Brunel, Loic||Boutros, Joseph J

publication date

• January 2008

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• n1930-529XISSN  Journal

keywords

• 40 Engineering
• 4006 Communications Engineering
• 46 Information And Computing Sciences
• 4603 Computer Vision And Multimedia Computation
• 4613 Theory Of Computation

Digital Object Identifier (DOI)

• 10.1109/GLOCOM.2008.ECP.928

International Standard Book Number (ISBN) 13

• 9781424423248

start page

• 1

end page

• 5

URL

• http://dx.doi.org/10.1109/glocom.2008.ecp.928