Distributed joint source-channel decoding for correlated Markov sources

Author

Chen, Qingyu ; Subbalakshmi, K.P.

Author_Institution

Dept. of ECE, Stevens Inst. of Technol., Hoboken, NJ, USA

fYear

2005

fDate

29-31 March 2005

Firstpage

453

Abstract

Summary form only given. Most current distributed joint source-channel coding (DJSCC) work focus on sources without memory, like i.i.d sources. We consider a general scenario where the sources are not only correlated with each other but also have memory. In particular, we design a constrained distributed joint source-channel decoder (C-DJSCD) for the optimal variable length multiple access source code (MASC) encoded sources for the symmetric distributed coding scenario. The proposed decoder is based on maximum a posteriori probability (MAP) estimation.

Keywords

Markov processes; combined source-channel coding; correlation theory; maximum likelihood decoding; maximum likelihood estimation; optimisation; probability; variable length codes; MAP estimation; constrained distributed joint source-channel decoder; correlated Markov sources; distributed joint source-channel coding; maximum a posteriori probability estimation; memory; multiple access source code; optimal variable length; symmetric distributed coding; Channel coding; Decoding; Dynamic programming; Hamming distance; State-space methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Data Compression Conference, 2005. Proceedings. DCC 2005

ISSN

1068-0314

Print_ISBN

0-7695-2309-9

Type

conf

DOI

10.1109/DCC.2005.32

Filename

1402210