UAV-Aided Aerial Reconfigurable Intelligent Surface Communications With Massive MIMO System

• Published in: IEEE transactions on cognitive communications and networking Vol. 8; no. 4; pp. 1828 - 1838
• Main Authors: Nguyen, Minh-Hien T., Garcia-Palacios, Emiliano, Do-Duy, Tan, Dobre, Octavia A., Duong, Trung Q.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.12.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Array signal processing; Autonomous aerial vehicles; Base stations; Beamforming; Communications systems; Iterative algorithms; Iterative methods; MIMO communication; Optimisation; Optimization; Power consumption; Power control; Radio equipment; reconfigurable intelligent surface (RIS); Reconfigurable intelligent surfaces; Resource management; Throughput; Trajectory; unmanned aerial vehicle (UAV); Unmanned aerial vehicles; User requirements
• ISSN: 2332-7731; 2332-7731
• DOI: 10.1109/TCCN.2022.3187098

To capture the advantages of unmanned aerial vehicle (UAV) and reconfigurable intelligent surface (RIS) technologies, we propose the use of multiple passive aerial RISs in a massive multiple-input multiple-output (MIMO) network. Each aerial RIS is comprised of a RIS panel attached to a UAV, the intention being to support in extending network coverage from the massive MIMO base station. Compared with stationary RISs, our proposed aerial RISs (termed as UAV-RISs) have the ability to reach more users thanks to the line-of-sight links. Our aim is to maximise the total network throughput by finding the optimal power control coefficients at the base station and the phase shifts of the multiple RISs used in the system. This is jointly solved subject to the power consumption constraints, UAV-RIS deployment, and quality-of-service required at the users. We apply zero-forcing precoding for the beamforming design at the base station, and develop an iterative algorithm based on first-order approximation, block coordinate descent, and alternating optimisation technique. Numerical results demonstrate that our proposed method exhibits low computational-complexity and outperforms benchmark schemes in terms of the total network throughput achieved and improvement for the users with worst-case throughput.