Energy-Efficient Link Optimization for RIS-Assisted LEO Satellite Communications in NTN

Integrating Low Earth Orbit (LEO) satellites into 6G networks is crucial for achieving global coverage and high-speed connectivity. However, mmWave communication at LEO altitudes faces challenges, including substantial path loss and signal degradation. To address these issues, this paper explores the application of Reconfigurable Intelligent Surface (RIS) technology for energy-efficient link optimization in LEO satellite systems. RIS plays a crucial role in extending Non-Terrestrial Network (NTN) coverage for vehicular communications, particularly in regions with limited terrestrial network infrastructure. We propose a novel optimization framework to maximize the Signal-to-Noise Ratio (SNR) by jointly optimizing RIS phase shifts and transmit covariance matrices in an uplink MIMO configuration. Our approach leverages an Alternating Optimization (AO) algorithm to efficiently solve the non-convex optimization problem, achieving substantial SNR gains and power savings. Simulation results validate the effectiveness of our method, demonstrating that RIS-assisted LEO systems can significantly enhance link quality, paving the way for more robust satellite-terrestrial networks in future 6G ecosystems.