计算机科学
无线
拉格朗日乘数
信道状态信息
可扩展性
稳健性(进化)
频道(广播)
最优化问题
实时计算
预编码
发射机功率输出
迭代法
功率(物理)
通信系统
保密
乘数(经济学)
计算复杂性理论
正交频分复用
轨迹优化
马尔可夫决策过程
分布式计算
算法
干扰(通信)
稳健优化
计算机工程
安全通信
数学优化
弹道
基站
带宽(计算)
协方差矩阵
计算机网络
作者
Xiaojie Wang,Jiaxin Ren,Zhaolong Ning,Yihang Huang,Xiaoming Tao,Lei Guo,Yan Zhang
标识
DOI:10.1109/jsac.2026.3669466
摘要
Enabled by 6G wireless technologies, Simultaneously Transmitting And Reflecting Reconfigurable Intelligent Surfaces (STAR-RISs) create a new dimension for optimizing performance in Uncrewed Aerial Vehicle (UAV) communications through fullspace signal coverage. However, existing research on STAR-RIS-assisted UAV secure communications still faces critical challenges, including the reliance on ideal Channel State Information (CSI) assumptions, amplitude optimization complexity under mode switching protocols, and limited scalability to meet multi-user communication demands. To address these challenges, we propose a robust and secure STAR-RIS-assisted UAV communication approach for a multi-user and multi-eavesdropper scenario. By jointly optimizing user scheduling, transmitting and reflecting coefficients of STAR-RIS, transmit power and flight trajectory of UAV, we aim to maximize the average worst-case achievable secrecy rate. To tackle the non-convexity and coupled decision variables of the formulated problem, we propose an alternating optimization framework, with a Lagrange multiplier method for power allocation, a deterministic model reformulated via S-procedure for CSI uncertainty quantification and robust handling, and a penalty-based double-loop iterative algorithm forcing the phase-shift matrix toward a rank-one solution. Finally, theoretical analysis and simulation results validate the superior secrecy performance of the proposed algorithm over other representative algorithms.
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