Optimization of Bandwidth Allocation and UAV Placement in Active RIS-Assisted UAV Communication Networks with Wireless Backhaul

• Published in: Drones (Basel) Vol. 9; no. 2; p. 111
• Main Authors: Tran, Thi-Thuy-Minh, Vu, Binh-Minh, Shin, Oh-Soon
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.02.2025
• Subjects: active reconfigurable intelligent surface (ARIS); Algorithms; Bandwidths; Communication networks; Communications networks; Communications systems; Energy consumption; Energy efficiency; Ground stations; Iterative solution; Network reliability; Optimization; Placement; Reconfigurable intelligent surfaces; resource allocation; Resource management; Technology; UAV placement optimization; unmanned aerial vehicle (UAV); Unmanned aerial vehicles; wireless backhaul; Wireless communications; Wireless networks
• ISSN: 2504-446X; 2504-446X
• DOI: 10.3390/drones9020111

In this paper, we present a novel design for unmanned aerial vehicle (UAV) communication networks with wireless backhaul, where an active reconfigurable intelligent surface (ARIS) is deployed to improve connections between a UAV and multiple users, while mitigating channel impairments in complex environments. The proposed design aims to maximize the achievable sum rate of all networks by jointly optimizing UAV placement; resource management strategies; transmit power allocation; and ARIS reflection coefficients, subject to backhaul constraints and power budget limitations in the ARIS system. The resulting optimization problem is highly non-convex, posing significant challenges. To tackle this, we decompose the problem into three interrelated sub-problems and apply inner approximation (IA) techniques to handle the non-convexities within each sub-problem. Moreover, a comprehensive alternating optimization framework is proposed to implement an iterative solution for the sub-problems. Simulation results demonstrate that the proposed algorithm achieves approximately 59% improvement in the average sum rate, substantially enhancing overall network reliability compared to existing benchmark schemes.