Unequal Error Protection for Digital Semantic Communication with Channel Coding

TL;DR

This paper introduces novel unequal error protection frameworks for digital semantic communication, linking semantic importance to bit reliability, and demonstrates significant improvements in transmission efficiency and task performance over traditional methods.

Contribution

The paper presents two UEP frameworks tailored for semantic communication, utilizing learned bit-flip probabilities and finite blocklength analysis for optimized protection levels.

Findings

Short-block coding outperforms long-block designs for heterogeneous protection.

Proposed frameworks achieve better task performance and transmission efficiency.

Simulation results validate substantial gains over equal-protection schemes.

Abstract

This paper investigates unequal error protection (UEP) in digital semantic communication, where semantically important bits require substantially higher reliability than less critical ones. To characterize this heterogeneity, we introduce a novel perspective that treats learned bit-flip probabilities of semantic bits as target error protection levels, thereby directly linking semantic importance to bit-level reliability. This formulation reveals that the required protection levels of the semantic bits may differ by several orders of magnitude, making short-block coding more advantageous than conventional long-block designs. Motivated by this, we develop two UEP frameworks that minimize total blocklength under heterogeneous reliability constraints. First, we propose a bit-level UEP framework based on repetition coding, providing an analytically tractable solution that precisely meets per-bit protection requirements. Second, to improve energy and blocklength efficiency, we design a block-level UEP framework in which the semantic bits are partitioned into short blocks with similar protection levels. Guided by finite blocklength capacity analysis, we derive a closed-form threshold condition for beneficial partitioning and develop a systematic algorithm for integrating modern channel codes. Simulation results on image transmission tasks demonstrate substantial gains in both task performance and transmission efficiency compared with conventional equal-protection schemes.