UAV Trajectory Planning for RIS-Assisted Data Collection

초록

This paper investigates energy-efficient trajectory planning for reconfigurable intelligent surface (RIS)-assisted unmanned aerial vehicle (UAV) data collection in Internet of Things (IoT) networks. A rotary-wing UAV collects data from multiple ground nodes (GNs), while the RIS enhances wireless links to improve data collection efficiency. The propulsion energy consumption model (PECM), speed and acceleration constraints, no-fly zone (NFZ) avoidance, and data requirements are jointly considered. Based on the uniform linear array (ULA) structure, a closed-form RIS phase-shift solution is derived to coherently combine the direct and reflected links. The resulting non-convex problem is solved via successive convex approximation (SCA). Numerical results show that the proposed framework significantly reduces UAV energy consumption and generates smooth, feasible trajectories.

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