Distributed compression of binary sources using conventional parallel and serial concatenated convolutional codes Conference Paper

abstract

• 2003 IEEE. It is shown how conventional parallel (turbo) and serial concatenated convolutional codes can be used to compress close to the Slepian-Wolf limit for the correlated binary sources. Conventional refers to codes already used in channel coding. Focusing on the asymmetric case of compression of an equipolarable memoryless binary source with side information at the decoder, the approach is based on modeling the correlation as a channel and using syndromes. The encoding and decoding procedures are explained in detail. The performance achieved is seen to be better than the recently published results using nonconventional turbo codes and close to the Slepian-Wolf limit.

name of conference

• Data Compression Conference, 2003. Proceedings. DCC 2003

authors

• Georghiades, Costas
• Xiong, Zixiang

published proceedings

• DCC 2003: DATA COMPRESSION CONFERENCE, PROCEEDINGS

author list (cited authors)

• Liveris, A. D., Xiong, Z. X., & Georghiades, C. N.

citation count

• 36

complete list of authors

• Liveris, AD||Xiong, ZX||Georghiades, CN

publication date

• January 2003

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• Data Compression Conference Proceedings  Journal

Digital Object Identifier (DOI)

• 10.1109/dcc.2003.1194010

International Standard Book Number (ISBN) 10

• 0-7695-1896-6

start page

• 193

end page

• 202

volume

• 2003-January

URL

• http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8491