Sky's the Limit: Navigating 6G with ASTAR-RIS for UAVs Optimal Path Planning

• Published in: Proceedings - IEEE Symposium on Computers and Communications pp. 582 - 587
• Main Authors: Ahmed, Shakil, Kamal, Ahmed E.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 09.07.2023
• Subjects: actively simultaneously transmitting and reflecting-reflecting reconfigurable intelligent surface; Autonomous aerial vehicles; Dynamic scheduling; mobility; Path planning; rate maximization; Reflection; resource allocation; Resource management; Simulation; unmanned aerial vehicle; Wireless networks
• ISSN: 2642-7389
• DOI: 10.1109/ISCC58397.2023.10218058

The surge in the number of various types of connected devices with the upcoming 6G networks may surpass the capabilities of traditional wireless infrastructure. Specifically, unmanned aerial vehicles (UAV s) can serve users to enhance network coverage and capacity in regions with limited or no existing infrastructure. However, resource allocation constraints and complex dynamics of UAV s pose significant challenges in optimal operation, such as path planning. Recently, researchers proposed simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RISs), which may serve the multiple users residing in the transmission and reflection regions. Unfortunately, STAR-RIS is only capable of reflecting incident signals, thus restricting its potential to enhance service quality in intricate channel conditions, particularly when the node distance is substantial. Motivated by this, we introduce a novel concept named actively simultaneously transmitting and reflecting (ASTAR)- RISs, which can amplify incident signals in addition to reflection. When mounted on UAVs, they can provide an improved signal-to-noise ratio (SNR) to numerous users in remote or inaccessible areas. We formulate the ASTAR-RIS-UAV-assisted rate maximization problem subject to the UAV mobility constraint and aim to find the UAV optimal path planning for a given flight time. While the formulated problem is non-convex, successive convex approximation and iterative algorithms are used to find the optimal solution to the problem, followed by a heuristic approach. Simulation results show that the proposed model outperforms existing approaches regarding network performance and resource allocation, highlighting the potential of adding ASTAR-RISs in UAV-assisted wireless networks.