SCA-based energy-efficient design of UAV-RIS-assisted NTN systems with joint trajectory and beamforming optimization

This study proposes an energy-efficient framework for non-terrestrial networks (NTNs) integrating a low Earth orbit (LEO) satellite, an unmanned aerial vehicle (UAV)-mounted reconfigurable intelligent surface (RIS), and a terrestrial user. The framework jointly optimizes the UAV’s 3D trajectory, satellite beamforming vectors, and RIS reflection coefficients to maximize energy efficiency (EE), accounting for UAV propulsion energy consumption and Quality of Service (QoS) constraints. The resulting non-convex fractional problem is solved using a low-complexity iterative algorithm combining successive convex approximation (SCA) and second-order cone programming (SOCP). Simulation results reveal up to 35% EE improvement over baseline schemes, highlighting the framework’s scalability and practicality for sustainable NTN systems.