Uncrewed aerial vehicles (UAVs) are increasingly being employed for data collection tasks, thanks to their high mobility and easy deployment, acting as aerial platforms to collect data from ground devices (GDs). This study considers a secure underlay data collection system assisted by dual UAVs and focuses on the joint design of the UAVs' three-dimensional (3D) flight paths, the power of the jamming UAV, the power of GDs, and the scheduling of the underlay GDs in the context of an aerial eavesdropper. The highly coupled objective function and non-convex constraints make the formulated problem more complicated to solve. We first utilize an approximate lower bound on the expected spectral efficiency to streamline the solution process. The average secrecy spectral efficiency (ASSE) is maximized by jointly designing the 3D trajectory of the UAVs, the transmit power of GDs, and the user scheduling. The optimization problem is decomposed into four subproblems using block coordinate descent, with each of them into manageable convex optimization tasks by incorporating slack variables and employing successive convex approximation methods. The numerical results validate the effectiveness of our proposed approach, demonstrating that the design of UAV 3D trajectories remarkably improves the ASSE of the considered system.

翻译：无人机凭借其高机动性和易部署性，正越来越多地被用于数据采集任务，作为空中平台从地面设备收集数据。本研究考虑一个由双无人机辅助的安全底层数据采集系统，重点研究无人机三维飞行路径、干扰无人机功率、地面设备功率以及底层设备调度在存在空中窃听者场景下的联合设计。高度耦合的目标函数与非凸约束使得所构建的问题更加复杂。我们首先利用期望频谱效率的近似下界来简化求解过程。通过联合设计无人机三维轨迹、地面设备发射功率和用户调度，最大化平均保密频谱效率。采用块坐标下降法将优化问题分解为四个子问题，通过引入松弛变量并应用逐次凸近似方法，将每个子问题转化为可处理的凸优化任务。数值结果验证了所提方法的有效性，表明无人机三维轨迹设计能显著提升所考虑系统的平均保密频谱效率。