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.