Designing near Shannon limit LDPC codes using particle swarm optimization algorithm

This paper presents a new design methodology/process for low-density parity-check codes (LDPC). To minimize the gap to Shannon limit, the particle swarm optimizer is applied to optimize the variable and check node degree distribution lambda and p respectively in case of irregular LDPC codes. discret...

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Bibliographic Details
Main Authors: Newagy, F.A., Fahmy, Y.A., El-Soudani, M.M.S.
Format: Conference Proceeding
Language:English
Subjects:
(Fast) Density Evolution (FDE)
Algorithm design and analysis
Computational modeling
Computer simulation
Decoding
Design engineering
Design methodology
Error analysis
Low-Density Parity-Check Codes (LDPC)
Parity check codes
Particle swarm optimization
Particle Swarm Optimization (PSO) Algorithm
Polynomials
Shannon Limit
Threshold value
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Summary:This paper presents a new design methodology/process for low-density parity-check codes (LDPC). To minimize the gap to Shannon limit, the particle swarm optimizer is applied to optimize the variable and check node degree distribution lambda and p respectively in case of irregular LDPC codes. discrete fast density evolution (FDE) is used (as the analysis technique) to compute the threshold value of LDPC code and the Shannon limit is evaluated based on Butman and McEliece formula. The results conducted show that, our proposed distributions with low degrees of (lambda, p) outperform other comparable distributions.
DOI:10.1109/ICTMICC.2007.4448612