Toward Reliable Semantic Communication: Beyond Average Performance

2026-05-31

AI Summary

This study addresses the insufficient reliability of existing semantic communication systems in dynamically uncertain environments, particularly their poor tail performance under harsh channel conditions. For the first time, it introduces a reliability-oriented perspective into semantic communication design and proposes a sample-level reliability enhancement framework that integrates channel-aware adaptation, robust semantic encoding and decoding, and HARQ retransmission mechanisms. To cope with imperfect channel state information, the work further develops a robust adaptive transmission scheme and a joint source-channel-check coding method. The paper systematically categorizes three design paradigms for reliable semantic communication and their limitations, then presents two novel solutions, offering both theoretical foundations and optimization frameworks for building high-reliability semantic communication systems compatible with existing wireless networks.

Abstract

Semantic communication has emerged as a promising paradigm for improving transmission efficiency by conveying task-relevant semantics rather than raw data. Although recent studies have achieved notable gains in communication efficiency and average task performance, reliability remains a fundamental bottleneck in dynamic and uncertain environments. In particular, most existing designs are still optimized mainly for average-case behavior, while lower-tail performance under adverse transmission conditions remains insufficiently understood and inadequately protected. In this article, we present a unified perspective on reliable semantic communication beyond average performance. We first review three reliability-oriented design categories: channel-aware adaptation, robustness-oriented codec design, and hybrid automatic repeat request (HARQ)-based retransmission. We show that these approaches address reliability from complementary perspectives, but each still has inherent limitations. Motivated by these observations, we discuss two solution directions: robust adaptive semantic communication under imperfect CSI, and joint source-channel-check coding with adaptive retransmission for sample-level reliability enhancement. Finally, we outline several future research directions, including the joint design of robustness and retransmission, reliability metrics beyond averages, and compatibility with existing digital wireless networks.

Problem

• semantic communication
• reliability
• tail performance
• dynamic environments
• transmission uncertainty

Innovation

• reliable semantic communication
• robust adaptive coding
• HARQ-based retransmission
• sample-level reliability
• imperfect CSI