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<p>Unmanned aerial vehicle (UAV) plays a vital role in modern networks due to its exceptional mobility and deployment flexibility. Reconfigurable intelligent surface (RIS), which can dynamically control electromagnetic wave propagation, provides an effective means to enhance UAV communication performance. This paper investigates a RIS-assisted secure UAV communication system to improve security performance. To maximize the average security rate (ASR) over the flight time, the beamforming vector of UAV, the phase shift matrix of RIS, and the UAV trajectory are jointly optimized. By addressing the complex coupling among the aforementioned variables through an alternating optimization framework, the original optimization problem is decomposed into three subproblems. First, the generalized Rayleigh quotient method is applied to optimize the UAV beamforming vector. Second, to obtain the phase shift matrix of RIS, a fractional programming approach is adopted. Finally, the successive convex approximation technique is employed to optimize the UAV trajectory. Extensive simulations demonstrate that the proposed scheme achieves better ASR performance than the benchmark schemes.</p>

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RIS-assisted secure UAV communication system: joint beamforming design and UAV trajectory optimization

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月11日

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  • Jin Li,
  • Chen Liu,
  • Mujun Qian,
  • Hong Wang,
  • Zhen Zhang

摘要

Unmanned aerial vehicle (UAV) plays a vital role in modern networks due to its exceptional mobility and deployment flexibility. Reconfigurable intelligent surface (RIS), which can dynamically control electromagnetic wave propagation, provides an effective means to enhance UAV communication performance. This paper investigates a RIS-assisted secure UAV communication system to improve security performance. To maximize the average security rate (ASR) over the flight time, the beamforming vector of UAV, the phase shift matrix of RIS, and the UAV trajectory are jointly optimized. By addressing the complex coupling among the aforementioned variables through an alternating optimization framework, the original optimization problem is decomposed into three subproblems. First, the generalized Rayleigh quotient method is applied to optimize the UAV beamforming vector. Second, to obtain the phase shift matrix of RIS, a fractional programming approach is adopted. Finally, the successive convex approximation technique is employed to optimize the UAV trajectory. Extensive simulations demonstrate that the proposed scheme achieves better ASR performance than the benchmark schemes.