UAV-RIS Assisted Multiuser Communications Through Transmission Strategy Optimization: GBD Application

• Published in: IEEE transactions on vehicular technology Vol. 73; no. 6; pp. 8584 - 8597
• Main Authors: Huroon, Aamer Mohamed, Huang, Yu-Chih, Wang, Li-Chun
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Aerial-terrestrial communications; Algorithms; Autonomous aerial vehicles; Base stations; Benders decomposition; Decoding; generalized Benders decomposition; Interference; Interference cancellation; Linear programming; Lower bounds; Mixed integer; mixed-integer nonlinear programming; NOMA; Nonlinear programming; Optimization; Optimization techniques; Reconfigurable intelligent surfaces; Resource management; transmission strategy; Unmanned aerial vehicles
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2024.3362066

In this article, we present a transmission strategy optimization technique for multiple unmanned aerial vehicles (UAVs) base stations assisted by a terrestrial reconfigurable intelligent surface (RIS). While each UAV is designed to serve a particular group of users, whether a UAV is assisted by RIS depends on the distance between the UAV and the terrestrial RIS. As such, a joint optimization problem of the allocation of RIS clusters for each associated UAV and the computation of phase rotations corresponding to terrestrial RIS elements is formulated. Based on the generalized Benders decomposition (GBD), we develop an algorithm to solve the problem efficiently for this mixed integer non-linear programming problem (MINLP) in two cases: 1) treating interference as noise (TIN) and 2) applying successive interference cancellation (SIC) at user terminals. Through extensive simulations, we provide evidence of our algorithm's superiority over existing methods, including alternating optimization and multi-task learning. By checking the upper and lower bounds provided by the proposed algorithm, we show that our algorithm attains the global optimality for the considered simulations. Notably, our results also reaffirm the common belief that SIC decoding can provide performance enhancement over TIN decoding in the UAV-RIS-assisted systems.