Abstract
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 full-space 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.
Funding Information
  • National Natural Science Foundation of China (62272075)
  • National Natural Science Foundation of China (62025105)
  • National Natural Science Foundation of China (62221005)
  • National Natural Science Foundation of China (62272075)
  • National Natural Science Foundation of China (62025105)
  • National Natural Science Foundation of China (62221005)
  • Natural Science Foundation of Chongqing Municipality (CSTB2025NSCQ-LZX0050)
  • Natural Science Foundation of Chongqing Municipality (CSTB2024NSCQ-JQX0013)
  • Natural Science Foundation of Chongqing Municipality (CSTB2024NSCQ-QCXMX0058)

This publication has 29 references indexed in Scilit: