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Joint Optimization of a UAV's Trajectory and Transmit Power for Covert Communications

机译:秘密通信的无人机轨迹和发射功率的联合优化

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This paper considers covert communications in the context of unmanned aerial vehicle (UAV) networks, aiming to hide a UAV for transmitting critical information out of an area that is monitored and where communication is not allowed. Specifically, the UAV as a transmitter intends to transmit information to a legitimate receiver (Bob) covertly while avoiding being detected by a warden (Willie), where location uncertainty exists at Bob and/or Willie. In order to enhance the considered covert communication performance, we jointly optimize the UAV's trajectory and transmit power in terms of maximizing the average covert transmission rate from the UAV to Bob subject to transmission outage constraint and covertness constraint. The formulated optimization problem is difficult to tackle directly due to the intractable constraints. As such, we first employ conservative approximation to transform a constraint into a deterministic form and then apply the first-order restrictive approximation to transform the optimization problem into a convex form. By applying the successive convex approximation technique, an efficient iterative algorithm is developed to solve the optimization problem. Our examination shows that the developed joint trajectory and transmit power optimization scheme achieves significantly better covert communication performance as compared to a benchmark scheme.
机译:本文考虑了无人飞行器(UAV)网络环境中的秘密通信,旨在隐藏用于将关键信息传输到受监视区域和不允许通信区域的无人飞行器。具体地,作为发送器的UAV打算秘密地将信息发送到合法的接收器(Bob),同时避免被守望者(Willie)检测到,在其中鲍勃和/或威利存在位置不确定性。为了提高考虑到的隐蔽通信性能,我们在传输中断约束和隐蔽约束条件下,通过最大化从无人机到Bob的平均隐蔽传输速率,共同优化了无人机的轨迹和发射功率。由于难以克服的约束,提出的优化问题难以直接解决。这样,我们首先采用保守近似将约束转换为确定性形式,然后应用一阶限制性近似将优化问题转换为凸形式。通过应用逐次凸逼近技术,开发了一种有效的迭代算法来解决优化问题。我们的检查表明,与基准方案相比,已开发的联合轨迹和发射功率优化方案可实现明显更好的秘密通信性能。

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