Density Evolution for the Design of Non-Binary Low Density Parity Check Codes for Slepian-Wolf Coding

In this paper, we investigate the problem of designing good non-binary LDPC codes for Slepian-Wolf coding. The design method is based on Density Evolution which gives the asymptotic error probability of the decoder for given code degree distributions. Density Evolution was originally introduced for...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on communications Vol. 63; no. 1; pp. 25 - 36
Main Authors: Dupraz, Elsa, Savin, Valentin, Kieffer, Michel
Format: Journal Article
Language:English
Published: New York IEEE 01.01.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Subjects:
Asymptotic properties
Channel coding
Channels
Coding
Computer Science
Decoding
Degree distribution optimization
Density
Density Evolution
Error correcting codes
Evolution
Gain
Information Theory
LDPC codes
Mathematics
Optimization
Parity check codes
Random variables
Recursion
Signal and Image Processing
Source coding with side information
Transforms
Vectors
Source coding with side information
degree distribution optimization
LDPC codes
density evolution
ISSN:0090-6778, 1558-0857
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, we investigate the problem of designing good non-binary LDPC codes for Slepian-Wolf coding. The design method is based on Density Evolution which gives the asymptotic error probability of the decoder for given code degree distributions. Density Evolution was originally introduced for channel coding under the assumption that the channel is symmetric. In Slepian-Wolf coding, the correlation channel is not necessarily symmetric and the source distribution has to be taken into account. In this paper, we express the non-binary Density Evolution recursion for Slepian-Wolf coding. From Density Evolution, we then perform code degree distribution optimization using an optimization algorithm called differential evolution. Both asymptotic performance evaluation and finite-length simulations show the gain at considering optimized degree distributions for SW coding.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2014.2382126