Home // International Journal On Advances in Telecommunications, volume 3, numbers 1 and 2, 2010 // View article

An Iterative Algorithm for Compression of Correlated Sources at Rates Approaching the Slepian-Wolf Bound: Theory and Analysis

Authors:
Fred Daneshgaran
Massimiliano Laddomada
Marina Mondin

Keywords: Correlated sources; compression; iterative decoding; low density parity check codes; Slepian-Wolf.

Abstract:
This paper proposes a novel iterative algorithm based on Low Density Parity Check codes for compression of correlated sources at rates approaching the Slepian-Wolf bound. The setup considered in the paper looks at the problem of compressing one source without employing the source correlation, and employing the other correlated source as side information at the decoder which decompresses the first source. We demonstrate that depending on the extent of the source correlation estimated through an iterative paradigm, significant compression can be obtained relative to the case the decoder does not use the implicit knowledge of the existence of correlation. Two stages of iterative decoding are employed. During global iterations updated estimates of the source correlation is obtained and passed on to the belief-propagation decoder that performs local iterations with a pre-defined stopping criterion and/or a maximum number of local decoding iterations. Detailed description of the iterative decoding algorithm with embedded cross-correlation estimation are provided in the paper, in addition to simulation results confirming the potential gains of the approach.

Pages: 39 to 48

Copyright: Copyright (c) to authors, 2010. Used with permission.

Publication date: September 5, 2010

Published in: journal

ISSN: 1942-2601