ICL-SEC：迭代跨层语义错误校正

中文摘要 AI 辅助

迭代解码是现代信道编码成功的核心，其中可靠性信息会在解码组件间反复交换，以逼近基本性能极限。本文将同一原理应用于语义错误校正，提出迭代跨层语义错误校正（ICL-SEC）框架，该框架闭合了物理层软信道解码器与应用层语言模型增强型语义解码器之间的循环。在所提框架中，软输入软输出信道解码器首先生成比特级后验概率，从中推导单词级可靠性。被判定为可靠的单词会作为语义上下文暴露给掩码语言模型，而不可靠的单词则被掩码。语言模型随后生成上下文单词似然，这些似然被用于生成 extrinsic 比特级先验，并反馈给信道解码器以进行下一次迭代。这种迭代细化逐步扩大了置信恢复单词的集合。一项关键贡献是我们的确认先验更新规则：一旦某个单词被判定为可靠，其比特在后续迭代中会被分配概率为1的确定性先验，使该单词成为信道解码器和语言模型的完全解析辅助信息。这种连续确认机制防止了振荡性的掩码-非掩码行为，并产生了跨层一致的可靠性解释。文本传输仿真表明，ICL-SEC的性能显著优于传统信道解码和非迭代CL-SEC。具体而言，所提的确认方案相较于非迭代CL-SEC将误码率降低了两个数量级以上，同时还显著改善了其他五项性能指标。

英文摘要

Iterative decoding has been central to the success of modern channel coding, where reliability information is repeatedly exchanged across decoding components to approach fundamental performance limits. This paper brings the same principle to semantic error correction by proposing iterative cross-layer semantic error correction (ICL-SEC), a framework that closes the loop between physical-layer soft channel decoder and application-layer language-model-empowered semantic decoder. In the proposed framework, a soft-input soft-output channel decoder first produces bit-level posterior probabilities, from which word-level reliabilities are derived. Words deemed reliable are exposed to a masked language model as semantic context, while unreliable words are masked. The language model then produces contextual word likelihoods, which are leveraged to generate extrinsic bit-level priors and fed back to the channel decoder for the next iteration. This iterative refinement progressively expands the set of confidently recovered words. A key contribution is our Confirm prior-update rule: once a word is judged reliable, its bits are assigned deterministic priors with probability one in subsequent iterations, making the word fully resolved side information for both the channel decoder and the language model. This successive-confirmation mechanism prevents oscillatory unmask-mask behavior and yields a reliability interpretation consistent across layers. Simulations over text transmission demonstrates that ICL-SEC substantially outperforms both conventional channel decoding and non-iterative CL-SEC. In particular, the proposed Confirm scheme reduces the bit error rate by more than two orders of magnitude relative to non-iterative CL-SEC, while also significantly improving the other five performance metrics.

发表机构

• The Chinese University of Hong Kong（香港中文大学）

机构由 AI 辅助整理，请以论文原文为准。