Energy Efficiency Optimization for RIS-Assisted UAV-Enabled MEC Systems

The reconfigurable intelligent surface (RIS) can proactively modify the wireless communication environment and further improve the service quality of the wireless networks. Motivated by this vision, in this paper, we propose to introduce the RIS into the unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC) systems. Considering both the amount of completed task bits and the energy consumption, the energy efficiency of the RIS-assisted UAV-enabled MEC systems is maximized by jointly optimizing the bit allocation, phase shift, and UAV trajectory via an iterative algorithm with a double-loop structure. Simulation results show that: 1) the UAV tends to fly closer to the RIS rather than the IoT devices; 2) the energy efficiency first increases and then decreases with the increase of the total amount of task-input bits of IoT devices; 3) higher energy efficiency can be achieved by our proposed algorithm.