Model Predictive Control-Based 3D Navigation of a RIS-Equipped UAV for LoS Wireless Communication With a Ground Intelligent Vehicle

Intelligent vehicles need high bandwidth wireless communication links for safety and commercial communication. However, the new generations of wireless communication networks (WCNs), such as quasi-optic millimeter-wave (mmWave) (5G) and visible light optic (6G) WCNs, are exposed to blockage/scattering problems in highly dense (urban) areas. In this paper, we propose a reconfigurable intelligent surface (RIS)-equipped (unmanned aerial vehicle) UAV (RISeUAV) to secure an uninterrupted line-of-sight (LoS) communication link for an intelligent vehicle. The vehicle can be a smart ambulance and needs a stable high-speed link for autonomous navigation, also for continuous monitoring/diagnosing of the health condition of a patient. A two-stage method is proposed to address the NP-hardness and nonconvexity of planning an optimal trajectory for autonomous navigation of the RISeUAV limited to UAV motion and LoS constraints. In the first stage, the optimal tube path is determined by considering the energy consumption, LoS link, and UAV speed/acceleration constraints. In the second stage, an accurate RISeUAV trajectory is obtained through the secured tube path by considering the communication performance, passive beamforming, and nonholonomic constraint of the RISeUAV. Dynamic programming and successive convex approximation methods are used in the first and second stages, respectively. Simulation results show the accuracy/effectiveness of the method.

Automated summary

This paper proposes a reconfigurable intelligent surface (RIS)-equipped unmanned aerial vehicle (RISeUAV) to provide uninterrupted line-of-sight communication for intelligent vehicles. A two-stage method is used to plan the optimal trajectory considering energy consumption, speed/acceleration constraints, and communication performance. Simulation results show the accuracy and effectiveness of the proposed method.