A New Fast Iterative Decoder of Product Codes Based on Hash and Syndromes and Optimized by Genetic Algorithms

A New Fast Iterative Decoder of Product Codes Based on Hash and Syndromes and Optimized by Genetic Algorithms

© 2022 by IJETT Journal
Volume-70 Issue-12
Year of Publication : 2022
Author : Hamza Faham, Seddiq El Kasmi Alaoui, Mohammed El Assad, Saïd Nouh, Idriss Chana, Mohamed Azzouazi
DOI : 10.14445/22315381/IJETT-V70I12P227

How to Cite?

Hamza Faham, Seddiq El Kasmi Alaoui, Mohammed El Assad, Saïd Nouh, Idriss Chana, Mohamed Azzouazi, "A New Fast Iterative Decoder of Product Codes Based on Hash and Syndromes and Optimized by Genetic Algorithms," International Journal of Engineering Trends and Technology, vol. 70, no. 12, pp. 289-295, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I12P227

Iterative decoding techniques have become very interesting, motivated by the encouraging results of the turbo codes. The Soft Decision Decoder based on Hash Techniques (SDHT) is a recent decoder of best performances and low temporal complexity. It is this second characteristic of the speed of SDHT which prompted us to use it here as a component decoder. In this paper, we adopt then SDHT as a soft input hard output (SIHO) decoding algorithm, about implement an iterative decoder for product codes at the base of Quadratic Residue (QR) and Bose Ray-Chaudhuri and Hocquenghem (BCH) codes. To compute the SDHT soft output, we exploit extrinsic information according to Soleymani et al. The iterative decoding is achieved via Pyndiah’s connection layout. The major aim of using the SDHT decoder is to benefit from its low computational complexity. We have also used a genetic algorithm to optimize the confidence value Ф that yields good performance in terms of Bit-Error-Rate. Simulation results and the study of complexities show that the proposed iterative decoder exceeds some competitors in terms of performance and complexity.

Error correcting codes, Genetic algorithms, Hash techniques, Product codes, Iterative decoder.

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