%0 Journal Article
%A 黄铫
%A 李浩进
%A 李琳佩
%A 苏郁
%A 赵川
%T Energy-efficient computation offloading assisted by RIS-based UAV
%D 2024
%R 10.19682/j.cnki.1005-8885.2024.2004
%J 中国邮电高校学报（英文）
%P 37-48
%V 31
%N 1
%X The new applications surge with the rapid evolution of the mobile communications. The explosive growth of the data traffic aroused by the new applications has posed great computing pressure on the local side. It is essential to innovate the computation offloading methods to alleviate the local computing burden and improve the offloading efficiency. Mobile edge computing (MEC) assisted by reflecting intelligent surfaces (RIS)-based unmanned aerial vehicle (UAV) is a promising method to assist the users in executing the computation tasks in proximity at low cost. In this paper, we propose an energy-efficient MEC system assisted by RIS-based UAV, where the UAV with RIS mounted relays the computation tasks to the MEC server. The energy efficiency maximization problem is formulated by jointly optimizing the UAV's trajectory, the transmission power of all users, and the phase shifts of the reflecting elements placed on the UAV. Considering that the optimization problem is non-convex, we propose a deep deterministic policy gradient (DDPG)-based algorithm. By combining the DDPG algorithm with the energy efficiency maximization problem, the optimization problem can be resolved. Finally, the numerical results are illustrated to show the performance of the system and the superiority compared with the benchmark schemes.
%U https://jcupt.bupt.edu.cn/CN/10.19682/j.cnki.1005-8885.2024.2004