Joint Physical Layer Security and Information Freshness of RIS-Assisted SPC System: Analysis and Optimization

被引:0
作者
Zhao, Wei [1 ]
Ni, Jianxin [1 ]
Hao, Shuai [1 ]
Li, Baogang [1 ]
Zhang, Tiantian [1 ]
机构
[1] North China Elect Power Univ, Dept Elect & Commun Engn, Baoding 071003, Peoples R China
基金
中国国家自然科学基金;
关键词
Ultra reliable low latency communication; Optimization; Reconfigurable intelligent surfaces; Wireless communication; Security; Eavesdropping; Communication system security; Upper bound; Simulation; Protocols; Reconfigurable intelligent surface; URLLC; physical layer security; information freshness; stochastic successive convex approximation; SHORT-PACKET COMMUNICATIONS; DRIVEN STATISTICAL DELAY; WIRELESS COMMUNICATION; PERFORMANCE ANALYSIS; MOBILE NETWORKS; AGE; MURLLC; URLLC;
D O I
10.1109/TVT.2025.3545884
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In order to maintain information freshness in passive eavesdropping scenarios of reconfigurable intelligent surface (RIS) assisted short packet communications (SPC), this paper proposes a physical layer security communication scheme that considers information freshness. Specifically, with the moment generating function in stochastic network calculus (SNC), the approximate closed-form expression for the upper bound of secrecy age outage probability (SAOP) under statistical channel state information (CSI) is derived. Besides, the effects of blocklength and decoding error probability on SAOP are analyzed. The average blocklength and decoding error probability satisfying minimum SAOP are derived. Furthermore, a SAOP minimization problem is proposed by considering reliability, security and RIS unit modulus constraints. For the non-convex problem with coupling variables, we decompose it into blocklength and RIS phase shift optimization subproblem through the alternating optimization algorithm. In particular, for the stochastic RIS phase shift optimization, a momentum stochastic successive convex approximation (M-SSCA) algorithm is proposed to obtain the optimal solution, which introduces a momentum disturbance factor to accelerate convergence. In simulation results, the effects of main system parameters on SAOP are given. Compared with the traditional convex optimization schemes, the algorithm proposed in this paper reduces SAOP more effectively and has better convergence performance according to simulation results.
引用
收藏
页码:10748 / 10760
页数:13
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