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Joint Trajectory and User Scheduling Optimization for Dual-UAV Enabled Secure Communications

机译：支持双UAV的联合轨迹和用户调度优化支持的安全通信

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摘要

In this article, we address joint optimization of unmanned aerial vehicle (UAV) trajectories and user communication scheduling for a dual-UAV enabled secure communication system, where one UAV moves to serve multiple users on the ground in a time division multiple access (TDMA) mode while the other UAV in the area flies to jam the colluding eavesdroppers on the ground to protect communications of the desired users. Specifically, we maximize the minimum average secrecy rate among the users within each period by jointly optimizing UAV trajectories and user scheduling variables under the maximum UAV speed constraints, the UAV return constraints, and the discrete binary constraints on user scheduling variables. The resulting optimization problem is very challenging due to its highly nonconvex objective function and constraints. We then develop a novel algorithm based on the penalty concave-convex procedure (CCCP) technique to solve it. Based on our simulation results, the proposed joint optimization algorithm achieves significantly better performance than the conventional algorithms.
机译：在本文中，我们解决了无人驾驶飞行器（UAV）轨迹的联合优化和用户通信调度，支持双UAV的安全通信系统，其中一个无人机在时分多址（TDMA）中在地面上提供多个用户模式而区域中的其他UAV在地面上的勾结窃听器中飞行，以保护所需用户的通信。具体地，我们通过在最大UAV速度约束，UAV返回约束和用户调度变量上的离散二进制约束下共同优化UAV轨迹和用户调度变量，最大化每个时段内用户之间的最小平均保密率。由于其高度非凸起的目标函数和约束，所产生的优化问题非常具有挑战性。然后，我们开发一种基于惩罚凹凸过程（CCCP）技术的新颖算法来解决它。基于我们的仿真结果，所提出的联合优化算法比传统算法实现明显更好的性能。

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