Reconfigurable Intelligent Surface Assisted UAV Communication: Joint Trajectory Design and Passive Beamforming

• Published in: IEEE wireless communications letters Vol. 9; no. 5; pp. 716 - 720
• Main Authors: Li, Sixian, Duo, Bin, Yuan, Xiaojun, Liang, Ying-Chang, Di Renzo, Marco
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.05.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); IEEE comsoc
• Subjects: Algorithms; Antenna arrays; Approximation algorithms; Array signal processing; Beamforming; Communication; Communication systems; Communications systems; Engineering Sciences; Line of sight communication; Mathematical analysis; Optimization; passive beamforming; Phase shift; Propagation; reconfigurable intelligent surface; Reconfigurable intelligent surfaces; Signal and Image processing; Trajectory; trajectory design; Trajectory optimization; UAV communication; Unmanned aerial vehicles; Urban areas; Wireless networks; UAV communication; trajectory design; reconfigurable intelligent surface; passive beamforming
• DOI: 10.1109/LWC.2020.2966705
• ISSN: 2162-2337

Thanks to the line-of-sight (LoS) transmission and flexibility, unmanned aerial vehicles (UAVs) effectively improve the throughput of wireless networks. Nevertheless, the LoS links are prone to severe deterioration by complex propagation environments, especially in urban areas. Reconfigurable intelligent surfaces (RISs), as a promising technique, can significantly improve the propagation environment and enhance communication quality by intelligently reflecting the received signals. Motivated by this, the joint UAV trajectory and RIS's passive beamforming design for a novel RIS-assisted UAV communication system is investigated to maximize the average achievable rate in this letter. To tackle the formulated non-convex problem, we divide it into two subproblems, namely, passive beamforming and trajectory optimization. We first derive a closed-form phase-shift solution for any given UAV trajectory to achieve the phase alignment of the received signals from different transmission paths. Then, with the optimal phase-shift solution, we obtain a suboptimal trajectory solution by using the successive convex approximation (SCA) method. Numerical results demonstrate that the proposed algorithm can considerably improve the average achievable rate of the system.