UAV-Assisted Task Offloading Strategy for Mobile Edge Computing

For the application scenario where the access points cannot access the mobile device due to ground signal blocking or shadow, we construct an unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system model based on simultaneous wireless information and power transfer. In this model, MEC services are provided for a group of mobile devices by correctly deploying and operating UAVs. Based on the model, a task offloading strategy for UAV assisted MEC is proposed. This strategy achieves the goal of minimizing the total energy consumption of UAV by jointly optimizing the horizontal position of UAV, communication and computing resources, and task division ratio. And then, we design a joint optimization algorithm based on the successive convex approximation (SCA) to address the non convex nature of the original optimization problem. The algorithm transform the original optimization problem into an approximate convex form, and the convex optimization toolbox in MATLAB is used for multiple iterations of solution. Simulation experiments verify the feasibility and effectiveness of the proposed UAV-assisted MEC task offloading strategy and the joint optimization algorithm based on SCA.