标题： 数字语义通信中的不等错误保护信道编码 显示英文标题

标题： Channel Coding for Unequal Error Protection in Digital Semantic Communication

摘要： 语义通信是一种新兴范式，它优先传输与任务相关的信息，而不是准确地传递原始数据位。 在本文中，我们解决数字语义通信中的不等错误保护（UEP）问题，其中语义重要性较高的位需要更强的保护。 为了量化比特级别的重要性，我们利用语义比特的翻转概率作为目标错误保护级别，这些级别与语义编码器和解码器一起学习。 我们提出了两种新颖的信道编码框架，旨在最小化总块长度同时满足UEP约束。 首先，我们开发了一个基于重复编码的比特级UEP框架，其中每个比特的重复次数被优化以精确满足其目标比特翻转概率。 其次，我们引入了一个利用现代信道码的块级UEP框架，其中具有相似目标比特翻转概率的语义比特被分组以利用编码增益。 在此框架内，我们提出了一种由有限块长度容量分析引导的比特分组算法。 在图像传输任务上的仿真结果证实，所提出的框架显著优于传统方法，在任务性能和传输效率方面均取得了显著提升。 显示英文摘要

摘要： Semantic communication is an emerging paradigm that prioritizes transmitting task-relevant information over accurately delivering raw data bits. In this paper, we address an unequal error protection (UEP) problem in digital semantic communication, where bits of higher semantic importance require stronger protection. To quantify bit-level importance, we leverage bit-flip probabilities of semantic bits as target error protection levels, which are jointly learned with semantic encoder and decoder. We propose two novel channel coding frameworks aimed at minimizing the total blocklength while satisfying UEP constraints. First, we develop a bit-level UEP framework based on repetition coding, in which the repetition number for each bit is optimized to precisely meet its target bit-flip probability. Second, we introduce a block-level UEP framework utilizing modern channel codes, where semantic bits with similar target bit-flip probabilities are grouped to exploit coding gains. Within this framework, we propose a bit-grouping algorithm guided by finite blocklength capacity analysis. Simulation results conducted on image transmission tasks confirm that the proposed frameworks significantly outperform conventional approaches, yielding substantial improvements in both task performance and transmission efficiency.