Energy Efficient Defense Against Cooperative Hostile Detection and Eavesdropping Attacks for AAV-Aided Short-Packet Transmissions

被引:1
作者
Mao, Haobin [1 ]
Liu, Yanming [1 ]
Xiao, Zhenyu [1 ]
Han, Zhu [2 ,3 ]
Xia, Xiang-Gen [4 ]
机构
[1] Beihang Univ, Sch Elect & Informat Engn, Beijing 100191, Peoples R China
[2] Univ Houston, Dept Elect & Comp Engn, Houston, TX 77004 USA
[3] Kyung Hee Univ, Dept Comp Sci & Engn, Seoul 446701, South Korea
[4] Univ Delaware, Dept Elect & Comp Engn, Newark, DE 19716 USA
基金
日本科学技术振兴机构; 中国国家自然科学基金;
关键词
Autonomous aerial vehicles; Trajectory; Three-dimensional displays; Optimization; Eavesdropping; Security; Power control; Relays; Convergence; Throughput; Autonomous aerial vehicle (AAV); covert communications; physical layer security; resource allocation; trajectory design; and short-packet communications; DATA-COLLECTION; COVERT; INFORMATION; COMMUNICATION; OPTIMIZATION; SECRECY; DESIGN;
D O I
10.1109/TVT.2024.3483256
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
Autonomous aerial vehicle (AAV)-aided short-packet transmissions have emerged as a promising paradigm for supporting mission-critical applications in future mobile communication networks. However, the security issues raised by the open nature of the wireless transmission deserve attention, especially when confronted with cooperative wardens and eavesdroppers. To this end, we consider a new framework for an energy-efficient design of AAV-aided short-packet transmission systems against cooperative hostile detection and eavesdropping attacks. Specifically, the false rate of the cooperative hostile detection is first derived by utilizing the likelihood ratio test and the bivariate Gaussian distribution property. Then, we formulate a problem to maximize the minimum covert secrecy energy efficiency (MCSEE) by jointly optimizing the user association, AAV power control, and AAV three-dimensional (3D) trajectory design. We propose a penalty-based dual-loop iterative optimization algorithm to tackle this complex problem suboptimally with the aid of auxiliary penalty variables, where the communication resource scheduling, the AAV trajectory planning, and the auxiliary penalty variables are optimized in the inner loop. In particular, the intractable joint AAV power control and 3D trajectory design sub-problem is suboptimally addressed by introducing slack variables and employing successive convex approximation (SCA) techniques. The penalty factor is updated in the outer loop. Finally, numerical results are provided to verify the effectiveness and superiority of our proposed solution to several benchmarks.
引用
收藏
页码:3082 / 3095
页数:14
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