Abstract
Modern wireless communication systems are limited to line-of-sight (LoS) links due to high path loss and blockage issues in millimeter wave (5G) and beyond in optical/visible light communication networks. This letter proposes utilizing (optical) reconfigurable intelligent surface (RIS)-equipped UAV (RISeUAV) to support indirect aerial LoS (ALoS) links for mobile vehicles that deliver critical metropolitan emergency/security services. The RISeUAV performs as an aerial transponder and reflects optical and wireless communication signals in dense urban areas. The navigation problem of the RISeUAV is nontrivial where RISeUAV should be autonomously navigated through an energy-efficient obstacle-free path. Notably, the flight altitude should be relatively low to ensure the quality of ALoS service while the maximum possible ALoS links for vehicles are provided in an obstructed environment. However, designing the flight path for rendering valid ALoS service is an NP-hard problem that is not feasible in real-time for autonomous navigation. We model the RISeUAV navigation as an optimization problem and propose an efficient technique to make the problem computationally tractable in real-time using Benders’ decomposition method and sequential convex programming. Simulation results validate the effectiveness of the proposed method.
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