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<p>Ensuring robust data integrity in modern communication systems necessitates advanced error correction techniques for handling noisy channel environments. This study proposes a hybrid decoding framework that integrates Chaos-Based Optimization with the Berlekamp-Massey (CBO-BM) algorithm to improve the decoding of Bose–Chaudhuri–Hocquenghem (BCH) codes. Three chaotic maps—logistic, sine, and tent—are employed to refine soft decision vectors prior to hard decoding. A Chaos-Enhanced Belief Propagation (CBP) approach is introduced to optimize decoding performance further. Simulation results across an Additive White Gaussian Noise (AWGN) channel demonstrate significant improvements. At 4 dB signal-to-noise ratio (SNR), the proposed hybrid method with logistic map achieves a Bit Error Rate (BER) of 0.0034 compared to 0.012 for conventional BM decoding, yielding over 70% reduction. The CBP method improves decoding accuracy, achieving a bit error rate (BER) of 0.003 at the same signal-to-noise ratio (SNR). These findings confirm the effectiveness and adaptability of chaotic dynamics in enhancing error correction reliability, particularly under low signal-to-noise ratio (SNR) conditions.</p>

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Chaos-based optimization and Berlekamp-Massey algorithm for Bose–Chaudhuri–Hocquenghem (BCH) code decoding

  • 期刊论文

  • 发表日期：

    2025年10月25日

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  • Augustus Ehiremen Ibhaze,
  • Ofeoritse Sarah Temiatse,
  • Agbotiname Lucky Imoize

摘要

Ensuring robust data integrity in modern communication systems necessitates advanced error correction techniques for handling noisy channel environments. This study proposes a hybrid decoding framework that integrates Chaos-Based Optimization with the Berlekamp-Massey (CBO-BM) algorithm to improve the decoding of Bose–Chaudhuri–Hocquenghem (BCH) codes. Three chaotic maps—logistic, sine, and tent—are employed to refine soft decision vectors prior to hard decoding. A Chaos-Enhanced Belief Propagation (CBP) approach is introduced to optimize decoding performance further. Simulation results across an Additive White Gaussian Noise (AWGN) channel demonstrate significant improvements. At 4 dB signal-to-noise ratio (SNR), the proposed hybrid method with logistic map achieves a Bit Error Rate (BER) of 0.0034 compared to 0.012 for conventional BM decoding, yielding over 70% reduction. The CBP method improves decoding accuracy, achieving a bit error rate (BER) of 0.003 at the same signal-to-noise ratio (SNR). These findings confirm the effectiveness and adaptability of chaotic dynamics in enhancing error correction reliability, particularly under low signal-to-noise ratio (SNR) conditions.