Joint Trajectory-Task-Cache Optimization With Phase-Shift Design of RIS-Assisted UAV for MEC

Abstract

Unmanned aerial vehicle (UAV) can work as mobile edge computing (MEC) server in the sky to provide communication and computation services to ground terminals (GTs), due to its high mobility. However, UAV might work in complicated environment, where UAV-GT links being frequently blocked by ground obstacles, then leading to a poor quality of service (QoS) on task latency. To this problem, reconfigurable intelligent surface (RIS) can assist UAV and improve the wireless environment by reflecting the transmitted signals between the UAV and GTs. RIS-assisted UAV thus can have a greatly improved performance on mobile computing. Under this deployment, to maximize the energy-efficiency of the RIS-assisted UAV, this letter tries to study the joint optimization of UAV trajectory, task offloading and cache with the phase-shift design of the RIS. We intent to ultilize the successive convex approximation (SCA) method to solve the joint problem, which is non-convex in its original form. Numerical results show that the joint optimization can improve the performance of the RIS-assisted UAV, compared with the benchmark solutions.