Iterative Estimation and Decoding for Gaussian Channels with Abruptly Changing Statistics

Author

Wufei Zhang ; Costello, D.J. ; Fuja, T.E. ; Shamir, G.I. ; Eckford, Andrew W.

Author_Institution

Dept. of Electr. Eng., Notre Dame Univ., IN

fYear

2006

fDate

9-14 July 2006

Firstpage

2466

Lastpage

2470

Abstract

An iterative estimation and decoding technique for memoryless additive white Gaussian noise (AWGN) channels with several abrupt changes in noise variance during transmission of a codeword is introduced. A technique developed for source coding of piecewise-stationary memoryless sources is adapted to estimate the unknown channel transition points. Then, maximum-likelihood (ML) estimation is used to estimate the unknown noise variance in each segment This process is carried out on an estimated noise sequence of the currently hypothesized codeword. Simulations using turbo codes show performance almost as good as that of a receiver with perfect knowledge of the channel

Keywords

AWGN channels; channel estimation; combined source-channel coding; iterative decoding; maximum likelihood estimation; turbo codes; AWGN channels; Gaussian channels; abruptly changing statistics; codeword; iterative decoding; iterative estimation; maximum-likelihood estimation; memoryless additive white Gaussian noise channels; piecewise-stationary memoryless sources; source coding; turbo codes; AWGN; Additive white noise; Gaussian channels; Gaussian noise; Iterative decoding; Maximum likelihood decoding; Maximum likelihood estimation; Source coding; Statistics; Turbo codes;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Theory, 2006 IEEE International Symposium on

Conference_Location

Seattle, WA

Print_ISBN

1-4244-0505-X

Type

conf

DOI

10.1109/ISIT.2006.262053

Filename

4036414