Simulated Annealing Decoder for Linear Block Codes

Abstract

In this study, we introduce a novel soft decoder, the first of its kind, for linear block codes, based on Simulated Annealing algorithm (SA). The main enhancement in our contribution which let our decoder over performs with large gain (about 3 dB at 7×10-4) the classical SA approach, is to take the most reliable information set of the received codeword as a start solution and also according to this reliability generate neighbor's solutions. Besides, our algorithm performance is enhanced by reducing search space when we involve the code error correcting capability parameter. The performance of the designed algorithm is investigated through a parameter tuning process and then compared with other various decoding algorithms in terms of decoding performance and algorithmic complexity. Simulation results, show that our algorithm over performs its competitor decoders while keeping minimum computation cost. In fact, our algorithm has large gain over Chase-2 and GAMD, furthermore, it over performs the most efficient and up to date DDGA decoder by 2 dB at 10-5 for RS codes.

A new efficient decoder of linear block codes based on ensemble learning models: case of boosting

“…The corresponding results in terms of BER versus SNR are given in the Figures 2 to 4. From Figure 2, we deduced that the EL-BoostDec decoder used to decode the BCH (15,5,7) code reaches a BER equal to 10 -5 at the SNR 8.7 dB. We notice that the BCH (15,7,5) has relatively the same performances as BCH (15,5,7).…”

“…Knowing that, the training set contains all possible syndromes, therefore the performances in terms of BER correction of EL-BoostDec passes considerably those of LRDec decoder for the BCH(63, 51, 5) code. For the codes BCH (15,5,7) and BCH(31, 16, 7) they have the same performances. This comparison demonstrates clearly that when the code length increases, the EL-BoostDec remains powerful but the efficiency of LRDec decrease.…”

“…Aylaj and Belkasmi [17] introduces a novel variant of the SA method for error correction. To evaluate its efficacy, a performance comparison was conducted between EL-BoostDec and this SA decoder, specifically applied to the BCH(31, 16, 7) and BCH (15,7,5) codes. Remarkably, the comparison reveals that both decoders yield identical results for these codes, suggesting a comparable level of performance in error correction.…”

“…This approach offers a systematic way to decode the QR (17,9,5) code and retrieve the encoded information accurately. According to Niharmine et al [15], a novel soft decoding method based on the simulated annealing (SA) algorithm is presented. The decoder's key contribution is that it provides nearby solutions based on the received codeword's most accurate information as the starting solution.…”