Improving belief propagation on graphs with cycles

In this letter, we propose two modifications to belief propagation (BP) decoding algorithm. The modifications are based on reducing the reliability of messages throughout the iteration process, and are particularly effective for short low-density parity-check codes, where the existence of cycles mak...

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Bibliographic Details
Published in:IEEE communications letters Vol. 8; no. 1; pp. 57 - 59
Main Authors: Yazdani, M.R., Hemati, S., Banihashemi, A.H.
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.01.2004
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Additives
Algorithms
Applied sciences
Associate members
Back propagation
Belief propagation
Bipartite graph
Block codes
Coding, codes
Computer simulation
Decoding
Digital communication
Errors
Exact sciences and technology
Graphs
Information, signal and communications theory
Iterative algorithms
Iterative decoding
Maximum likelihood decoding
Messages
Parity check codes
Processor scheduling
Signal and communications theory
Telecommunications and information theory
Performance evaluation
iterative decoding
low-density parity-check (LDPC) codes
offset belief propagation
Signal processing
Iterative method
message-passing decoding algorithms
Decoding
Bipartite graph
Algorithm
normalized belief propagation
Belief propagation
ISSN:1089-7798, 1558-2558
Online Access:Get full text
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Summary:In this letter, we propose two modifications to belief propagation (BP) decoding algorithm. The modifications are based on reducing the reliability of messages throughout the iteration process, and are particularly effective for short low-density parity-check codes, where the existence of cycles makes the original BP algorithm perform suboptimal. The proposed algorithms, referred to as "normalized BP" and "offset BP," reduce the absolute value of the outgoing log-likelihood ratio messages at variable nodes by using a multiplicative factor and an additive factor, respectively. Simulation results show that both algorithms perform more or less the same, and both outperform BP in error performance.
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ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2003.822499