Parallel vs. Sequential Belief Propagation Decoding of LDPC Codes over GF(q) and Markov Sources

Details Parallel vs. Sequential Belief Propagation Decoding of LDPC Codes over GF(q) and Markov Sources Parallel vs. Sequential Belief Propagation Decoding of LDPC Codes over GF(q) and Markov Sources

2006-05-16

arxiv.org/abs/cs/0605069v1

Computer Science

Information Theory

Scientific paper

10.1016/j.physa.2006.12.009

A sequential updating scheme (SUS) for belief propagation (BP) decoding of LDPC codes over Galois fields, $GF(q)$, and correlated Markov sources is proposed, and compared with the standard parallel updating scheme (PUS). A thorough experimental study of various transmission settings indicates that the convergence rate, in iterations, of the BP algorithm (and subsequently its complexity) for the SUS is about one half of that for the PUS, independent of the finite field size $q$. Moreover, this 1/2 factor appears regardless of the correlations of the source and the channel's noise model, while the error correction performance remains unchanged. These results may imply on the 'universality' of the one half convergence speed-up of SUS decoding.

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