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<p>Intelligent reconfigurable surface (IRS) is an emerging technology for enhancing physical layer security (PLS). This paper investigates an IRS-assisted uncrewed aerial vehicle (UAV) secure communication system with a flying UAV eavesdropper (UAE) and mobile ground users, addressing a research gap where few studies consider both user and eavesdropper mobility. We formulate a sum secrecy rate maximization problem by jointly optimizing the UAV trajectory, user transmit power, and IRS phase shifts while ensuring users’ quality of service (QoS) requirements, including secrecy and data rate constraints. Due to the coupled and non-convex nature of the optimization problem, we propose a hybrid approach that combines the soft actor-critic (SAC) algorithm and block coordinate descent (BCD). SAC is employed to optimize the UAV trajectory and user power allocation, while BCD is used to optimize the IRS reflection coefficients. Simulation results demonstrate that the proposed SAC-BCD algorithm achieves superior convergence and outperforms several benchmark methods in terms of secrecy rate. Furthermore, IRS deployment significantly enhances system security compared to scenarios without IRS assistance, confirming the effectiveness of our proposed approach.</p>

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Maximizing secrecy rate for IRS-assisted UAV network with an aerial eavesdropper

  • 期刊论文

  • 发表日期：

    2025年12月5日

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  • Tingting Li,
  • Yanjun Li,
  • Yuzhe Chen,
  • Jianji Shao,
  • Zhibo Wang

摘要

Intelligent reconfigurable surface (IRS) is an emerging technology for enhancing physical layer security (PLS). This paper investigates an IRS-assisted uncrewed aerial vehicle (UAV) secure communication system with a flying UAV eavesdropper (UAE) and mobile ground users, addressing a research gap where few studies consider both user and eavesdropper mobility. We formulate a sum secrecy rate maximization problem by jointly optimizing the UAV trajectory, user transmit power, and IRS phase shifts while ensuring users’ quality of service (QoS) requirements, including secrecy and data rate constraints. Due to the coupled and non-convex nature of the optimization problem, we propose a hybrid approach that combines the soft actor-critic (SAC) algorithm and block coordinate descent (BCD). SAC is employed to optimize the UAV trajectory and user power allocation, while BCD is used to optimize the IRS reflection coefficients. Simulation results demonstrate that the proposed SAC-BCD algorithm achieves superior convergence and outperforms several benchmark methods in terms of secrecy rate. Furthermore, IRS deployment significantly enhances system security compared to scenarios without IRS assistance, confirming the effectiveness of our proposed approach.