BCH码的有序可靠性比特Chase译码算法
An Ordered-Reliability-Bits Chase Decoding Algorithm for BCH Codes
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中文总结 AI 辅助
本文提出一种适用于BCH码的低复杂度ORB-Chase译码算法，通过逻辑权重生成TEP和整数早终止准则减少计算量，在接近ML性能的同时大幅降低BM译码调用次数。
中文摘要 AI 辅助
本文提出一种适用于BCH码的低复杂度有序可靠性比特Chase（ORB-Chase）译码算法。该算法与传统Chase算法有两个关键区别：一是采用逻辑权重作为度量来生成测试错误模式（TEP）；二是引入基于整数的早终止准则，若识别出最大似然码字，计算可在最早阶段停止，从而减少不必要的计算量。对（127,113,5）BCH码和（256,239,6）增强型BCH码（eBCH码）的仿真结果表明，ORB-Chase算法在测试模式数量远少于Chase算法的情况下，可达到接近最大似然（ML）的性能；此外，随着比特能量与噪声功率谱密度之比（$E_b/N_0$）的增加，Berlekamp-Massey（BM）译码调用的平均次数迅速减少，在相同误块率（BLER）性能下，与Chase算法相比最多可减少98.1%。
英文摘要
In this paper, we propose a low-complexity ordered-reliability-bits Chase (ORB-Chase) decoding algorithm for BCH codes. The proposed algorithm differs from the traditional Chase algorithm in two key aspects. First, it employs the logical weight as a metric to generate test error patterns (TEPs). Second, it introduces an integer-based early termination criterion that ensures computation can stop at the earliest possible stage if the maximum-likelihood codeword is identified, thereby minimizing unnecessary computational effort. Simulation results for (127, 113, 5) BCH codes and (256, 239, 6) eBCH codes demonstrate that the ORB-Chase algorithm achieves near-ML performance with significantly fewer test patterns compared to the Chase algorithm. Moreover, the average number of Berlekamp-Massey (BM) decoding calls decreases rapidly as $E_b / N_0$ increases, achieving a reduction of up to 98.1% compared to the Chase algorithm at the same BLER performance.
