QLDPC码的多级重绕解码器
Multistage Rewinding Decoder for QLDPC Codes
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中文总结 AI 辅助
针对QLDPC码迭代解码的失效问题，提出多级重绕解码器，结合启发式度量与束搜索优化，逻辑错误率性能优于归一化最小和解码器，接近10阶有序统计解码增强的置信传播。
中文摘要 AI 辅助
本文提出一种利用底层消息传递解码器产生的内部信息的多级解码框架。该方法针对QLDPC码迭代解码的主要限制之一——经典陷阱集和对称稳定器支持的退化错误引发的失效动态。为识别不可靠变量节点，引入一种启发式度量，结合解码器的多个动态特征，包括变量节点对数似然可靠性、硬判决振荡、相邻不满足校验的数量，以及不满足校验贡献的软信息。基于该排序度量，解码器执行引导重绕，选择性强制最可疑变量节点的初始对数似然比值，并在对应强制配置下重启消息传递解码器。为控制候选配置的组合增长，该搜索在具有受控束宽的束搜索框架内进行。此外，引入基于伴随式残差权重与解码器输出后验可靠性组合的剪枝度量，仅保留最具前景的搜索路径。逻辑错误率结果表明，所提出的解码器显著优于归一化最小和解码器，且性能与经10阶有序统计解码增强的置信传播相当。
英文摘要
In this paper, we propose a multistage decoding framework that leverages internal information produced by an underlying message-passing decoder. The proposed method targets the failure dynamics caused by both classical trapping sets and degenerate errors supported on symmetric stabilizers, which are among the primary limitations of iterative decoding for QLDPC codes. To identify unreliable variable nodes, we introduce a heuristic metric that combines several dynamical features of the decoder, including variable-node log likelihood reliabilities, hard-decision oscillations, the number of adjacent unsatisfied checks, and the soft information contributed by unsatisfied checks. Based on this ranking metric, the decoder performs guided rewinds by selectively forcing the initial log likelihood ratio values of the most suspicious variable nodes and restarting the message-passing decoder under the corresponding forced configuration. To manage the combinatorial growth of candidate configurations, the search is formulated within a beam- search framework with controlled beam width. In addition, we introduce a pruning metric based on the combination of the residual syndrome weight and a posteriori reliability of the decoder output, thereby retaining only the most promising search paths. Logical error rate results demonstrate that the proposed decoder significantly outperforms the normalized min- sum decoder and achieves competitive performance with belief propagation enhanced by order-10 ordered statistics decoding.
