@article {Azougaghe202211, title = {Turbo decoding of concatenated codes based on RS codes using adapted scaling factors}, journal = {Infocommunications Journal}, volume = {14}, number = {1}, year = {2022}, note = {cited By 0}, pages = {11-16}, abstract = {Iteratively decoded block turbo codes are product codes that exhibit excellent performance with reasonable com-plexity. In this paper, a generalization of parallel concatenated block codes (GPCBs) based on RS codes is presented. We propose an efficient decoding algorithm with modifications of the Chase- Pyndiah algorithm is written by using Weighting factor α and Reliability factor β. In this work, we studied the effect of diverse parametres such as the effect of various component codes, interleaver size (number of sub-blocks) and number of iterations. The simulation results shows the relevance of the adapted parameters to decode generalized parallel concatenated block codes based on RS codes. The proposed algorithm (MCP) using the adapted parameters performs better than the one using with empirical parameters (CP). {\textcopyright} 2022 Scientific Association for Infocommunications. All rights reserved.}, keywords = {Block codes, Block Turbo codes, Chase decoding, Concatenated codes, Generalized parallel con-catenated code, Iterative decoding, Iterative decodings, Modified chase- pyndiah algorithm, Performance, Product code, RS codes, Scaling factors, Turbo codes, Turbo decoding}, doi = {10.36244/ICJ.2022.1.2}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129965517\&doi=10.36244\%2fICJ.2022.1.2\&partnerID=40\&md5=b8b9da3f379cbf44233c273bb8f4108f}, author = {Azougaghe, E.-S. and Farchane, A. and Safi, S. and Belkasmi, M.} } @article {Yatribi2020, title = {Gradient-descent decoding of one-step majority-logic decodable codes}, journal = {Physical Communication}, volume = {39}, year = {2020}, note = {cited By 1}, abstract = {In this paper, a new low-complexity gradient-descent based iterative majority-logic decoder (GD-MLGD) is proposed for decoding One-Step Majority-Logic Decodable (OSMLD) codes. We give a formulation of the decoding problem of binary OSMLD codes, as a maximization problem of a derivable objective function. The optimization problem is solved using a pseudo gradient-descent algorithm, which performs iteratively an update towards the optimal estimated codeword been transmitted, based on the first-order partial derivatives of each variable calculated in the previous iteration. The proposed decoding scheme achieves a fast convergence to an optimum codeword compared to other decoding techniques reviewed in this paper, at the cost of lower computational complexity. The quantized version (QGD-MLGD) is also proposed in order to further reduce the computational complexity. Simulation results show that the proposed decoding algorithms outperform all the existing majority-logic decoding schemes, and also various gradient-descent based bit-flipping algorithms, and performs nearly close to the belief propagation sum{\textendash}product (BP-SP) decoding algorithm of LDPC codes, especially for high code lengths, providing an efficient trade-off between performance and decoding complexity. Moreover, the proposed quantized algorithm has shown to perform better than all the existing decoding techniques. The proposed decoding algorithms have shown to be suitable for ultra reliable, low latency and energy-constrained communication systems where both high performances and low-complexity are required. {\textcopyright} 2020 Elsevier B.V.}, keywords = {AWGN channel, Backpropagation, Computational complexity, Computer circuits, Decoding complexity, Difference sets, Economic and social effects, Electronic trading, Gradient descent, Gradient methods, Iterative decoding, LDPC codes, Majority logic, Majority logic decoding, Maximum likelihood, Maximum likelihood decoding, Optimization, OSMLD codes}, doi = {10.1016/j.phycom.2019.100999}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077749482\&doi=10.1016\%2fj.phycom.2019.100999\&partnerID=40\&md5=830156cfb12a8ec3dbff2e002b3ade63}, author = {Yatribi, A. and Belkasmi, M. and Ayoub, F.} } @article {Azougaghe2020103, title = {Iterative Decoding of GSCB Codes Based on RS Codes Using Adapted Scaling Factors}, journal = {Communications in Computer and Information Science}, volume = {1264}, year = {2020}, note = {cited By 0}, pages = {103-114}, abstract = {In this work, we have extended two algorithms to decode generalized serially concatenated block codes based on RS codes (GSCB-RS). The first is the modified Chase-Pyndiah algorithm (MCPA) proposed by Farchane and Belkasmi[1]. The second is the Chase-Pyndiah algorithm (CPA) that is developed initially for decoding turbo product codes[2]. We also investigated the effect of different parameters, namely component codes, the size and structure of the interleaver and the number of iterations, using computer simulations. The simulations result shows that the performance of the GSCB-RS codes using the MCPA decoder out performs the CPA decoder that uses predetermined weighting factor (α) and reliability factor (β) parameters. {\textcopyright} 2020, Springer Nature Switzerland AG.}, keywords = {Block codes, Component codes, Concatenated codes, Data communication systems, Interleavers, Iterative decoding, Number of iterations, Reliability factor, RS codes, Scaling factors, Security of data, Turbo product codes, Weighting factors}, doi = {10.1007/978-3-030-61143-9_9}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097364331\&doi=10.1007\%2f978-3-030-61143-9_9\&partnerID=40\&md5=5a3be47852101aec7c21c1ee8c52200c}, author = {Azougaghe, E.-S. and Farchane, A. and Safi, S. and Belkasmi, M.} } @article {8699111820120101, title = {Reduced Complexity Iterative Decoding of 3D-Product Block Codes Based on Genetic Algorithms.}, journal = {Journal of Electrical \& Computer Engineering}, year = {2012}, pages = {1 - 8}, abstract = {Two iterative decoding algorithms of 3D-product block codes (3D-PBC) based on genetic algorithms (GAs) are presented. The first algorithm uses the Chase-Pyndiah SISO, and the second one uses the list-based SISO decoding algorithm (LBDA) based on order-i reprocessing. We applied these algorithms over AWGN channel to symmetric 3D-PBC constructed from BCH codes. The simulation results show that the first algorithm outperforms the Chase-Pyndiah one and is only 1.38 dB away from the Shannon capacity limit at BER of 10-5 for BCH (31, 21, 5){\textthreesuperior} and 1.4 dB for BCH (16, 11, 4){\textthreesuperior}. The simulations of the LBDA-based GA on the BCH (16, 11, 4){\textthreesuperior} show that its performances outperform the first algorithm and is about 1.33 dB from the Shannon limit. Furthermore, these algorithms can be applied to any arbitrary 3D binary product block codes, without the need of a hard-in hardout decoder. We show also that the two proposed decoders are less complex than both Chase-Pyndiah algorithm for codes with large corr}, keywords = {Computational complexity, Computer simulation, Genetic algorithms, Iterative decoding, Performance evaluation, Three-dimensional imaging}, issn = {20900147}, url = {http://search.ebscohost.com/login.aspx?direct=true\&db=iih\&AN=86991118\&site=ehost-live}, author = {Ahmadi, Abdeslam and Bouanani, Faissal El and Ben-Azza, Hussain and Benghabrit, Youssef} }