移动通信2026，Vol.50Issue(1)：35-43,9.DOI:10.3969/j.issn.1006-1010.20250920-0001
基于信道容量约束的物理层安全语义通信
Physical Layer Secure Semantic Communication Based on Channel Capacity Constraints
摘要
Abstract
With advancements in artificial intelligence,semantic communication has emerged as a key research direction for 6G networks.However,the broadcast nature of wireless channels introduces privacy risks,necessitating secure solutions.Existing methods often rely on network-layer encryption,which suffers from operational complexity and potential key leakage.Physical layer security,leveraging the channel's time-variation and randomness,can circumvent complex cryptographic mechanisms.In response,this paper proposes a physical layer secure semantic communication framework based on channel capacity constraints.The core design goal is to maximize the legitimate channel's capacity while restricting the overall security capacity to a predefined threshold.A differentiable mutual information estimator is introduced to construct a dual-channel capacity estimation model that includes both legitimate users and eavesdroppers,which can be jointly optimized with the semantic communication system.Additionally,an innovative security sentence similarity metric is proposed to quantify the security performance of semantic communication.Simulation results demonstrate that the proposed scheme significantly enhances communication security at the cost of a slight decrease in transmission accuracy.关键词
语义通信/物理层安全/信道容量/互信息估计Key words
semantic communication/physical layer security/channel capacity/mutual information estimation分类
信息技术与安全科学引用本文复制引用
刘宇翔,王旭,施政,王金涛,杨光华,马少丹..基于信道容量约束的物理层安全语义通信[J].移动通信,2026,50(1):35-43,9.基金项目
国家自然科学基金面上项目"面向超可靠低延时通信的叉包HARQ传输理论与方法""智能反射面辅助的安全通信理论与关键技术研究"(62171200,62171201) （62171200,62171201）
国家自然科学基金国际(地区)合作与交流项目"AI驱动的6G无线智能空口传输理论与关键技术"(62261160650) （地区）
广东省自然科学基金面上项目"叉包HARQ辅助太赫兹通信的传输理论和方法研究"(2023A1515010900) （2023A1515010900）
中央高校基本科研业务费项目"基于深度学习的端到端语义通信可靠性研究"(21625361) （21625361）
高校青年教师科研创新能力支持项目(SRICSPYF-BS2025134) （SRICSPYF-BS2025134）
暨南大学研究生拔尖创新人才项目资助(2025CXY358) （2025CXY358）
