A UAV mounted RIS aided communication and localization integration system for ground vehicles

Recent investigations show that, both reconfigurable intelligent surface (RIS) and unmanned aerial vehicle (UAV) could be utilized in enhancing the wireless coverage and improving the positioning accuracy. Since the position information and communication connections are unavailable in urban blind areas, we propose a novel UAV-mounted RIS (URIS)-aided communication and localization integration system for ground vehicles (GVs). We first introduce the metrics of position error bound (PEB) and spectral efficiency (SE) to evaluate the localization and communication performances of the GV. A unified joint UAV trajectory planning and RIS phase-shifts configuration problem is formulated to strike a balance between localization and communication. This non-convex problem can be decomposed into two subproblems: RIS phase-shifts configuration and UAV trajectory planning problems, respectively. A Block Coordinate Descent (BCD) based phase-shifts optimizer and a deep reinforcement learning (DRL) based real-time trajectory generator are designed to tackle the decomposed problems. Finally, numerical results are provided and can verify the effectiveness of our proposed framework.