Energy-Efficient Trajectory Planning for UAV-Aided Secure Communication

Wireless communication with unmanned aerial vehicles(UAVs) has aroused great research interest recently. This paper is concerned with the UAV's trajectory planning problem for secrecy energy efficiency maximization(SEEM) in the UAV communication system. Specifically, we jointly consider the secrecy throughput and UAV's energy consumption in a three-node(fixed-wing UAV-aided source, destination, and eavesdropper) wiretap channel. By ignoring the energy consumption on radiation and signal processing, the system's secrecy energy efficiency is defined as the total secrecy rate normalized by the UAV's propulsion energy consumption within a given time horizon. Nonetheless, the SEEM problem is nonconvex and thus is intractable to solve. As a compromise, we propose an iterative algorithm based on sequential convex programming(SCP) and Dinkelbach's method to seek a suboptimal solution for SEEM. The algorithm only needs to solve convex problems, and thus is computationally efficient to implement. Additionally, we prove that the proposed algorithm has Karush-KuhnTucker(KKT) point convergence guarantee. Lastly, simulation results demonstrate the efficacy of our proposed algorithm in improving the secrecy energy efficiency for the UAV communication system.

Energy-Efficient and Secure Power Allocation and Trajectory Optimization for UAV-Enabled Data Collection in Wireless Sensor Networks

Using unmanned aerial vehicles(UAVs)to collect data in wireless sensor networks(WSNs)has advantages of controllable mobility and flexible deployment.However,there are potential challenges of energy limitation and data security which may limit such applications.To cope with these challenges,a complicated and intractable optimization problem is formulated,which maximizes the performance metric of secrecy energy efficiency(EE)subject to the constraints of secrecy rate,maximum power,and trajectory.Then,an energy-efficient and secure solution is developed to improve the secrecy EE of the UAV-enabled data collection in the WSNs by joint optimizing the UAV’s trajectory and velocity along with the sensors’power.The proposed solution is an iterative algorithm based on the optimization approaches of alternating optimization,successive convex approximation,and fractional programming.Simulation results demonstrate that the proposed solution scheme is effective for improving the secrecy EE while guaranteeing the data security.