Mean field and mixed mean field iterative decoding of low-density parity-check codes
| Autor: | Juntan Zhang, M.P.C. Fossorier |
|---|---|
| Rok vydání: | 2006 |
| Předmět: |
Block code
Discrete mathematics Berlekamp–Welch algorithm Data_CODINGANDINFORMATIONTHEORY Sequential decoding Library and Information Sciences Belief propagation Linear code Computer Science Applications Probability distribution Low-density parity-check code Algorithm Decoding methods Computer Science::Information Theory Information Systems Mathematics |
| Zdroj: | IEEE Transactions on Information Theory. 52:3168-3185 |
| ISSN: | 0018-9448 |
| Popis: | In this paper, the mean field (MF) and mixed mean field (MMF) algorithms for decoding low-density parity-check (LDPC) codes are considered. The MF principle is well established in statistical physics and artificial intelligence. Instead of using a single completely factorized approximated distribution as in the MF approach, the mixed MF algorithm forms a weighted average of several MF distributions as an approximation of the true posterior probability distribution. The MF decoding algorithm for linear block codes is derived and shown to be an approximation of the a posteriori probability (APP) decoding algorithm. The MF approach is then developed in the context of iterative decoding and presented as an approximation of the popular belief propagation decoding method. These results are extended to iterative decoding with the MMF algorithm. Simulation results show that the MF and MMF decoding algorithms yield a good performance-complexity tradeoff, especially when employed for decoding LDPC codes based on finite geometries. |
| Databáze: | OpenAIRE |
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