The Journal of China Universities of Posts and Telecommunications ›› 2024, Vol. 31 ›› Issue (1): 37-48.doi: 10.19682/j.cnki.1005-8885.2024.2004

• Wireless • Previous Articles     Next Articles

Energy-efficient computation offloading assisted by RIS-based UAV

Li Linpei, Zhao Chuan, Su Yu, Huo Jiahao, Huang Yao, Li Haojin   

  1. 1. School of Intelligence Science and Technology, University of Science and Technology Beijing, Beijing 100083, China 2. Institute of Artificial Intelligence, University of Science and Technology Beijing, Beijing 100083, China 3. Shunde Innovation School, University of Science and Technology Beijing, Foshan 528399, China 4. School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China 5. Research Department of 5G and Drone, China Mobile (Chengdu) Institute of Research and Development, Chengdu 610200, China 6. College of Communication Engineering, Chengdu University of Information Technology, Chengdu 610225, China 7. Research and Development Center, Sony (China) Limited, Beijing 100027, China
  • Received:2023-11-15 Revised:2024-01-05 Accepted:2024-02-22 Online:2024-02-29 Published:2024-02-29
  • Contact: Corresponding author: Li Linpei, E-mail:
  • Supported by:
    This work was supported by National Key Research and Development Program of China (2021YFB2900801), supported by Guangdong Basic and Applied Basic Research Foundation (2022A1515110335), supported by Fundamental Research Funds for the Central Universities (FRF-TP-22-094A1), supported by Science, Technology and Innovation Project of Xiongan New Area (2022XAGG0114), and supported by Meteorological information and Signal Processing Key Laboratory of Sichuan Higher Education Institutes of Chengdu University of Information Technology (CXHCL202201).

Abstract: 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.

Key words: mobile edge computing, unmanned aerial vehicle, reflecting intelligent surface