Performance Analysis of RIS-Aided Cognitive GEO-LEO Satellite Networks

Reconfigurable intelligent surfaces (RISs) have emerged as a promising solution to enhance the performance and efficiency of satellite communication systems. This paper investigates the performance of RIS technology in enhancing cognitive dual satellite networks, where a low earth orbit (LEO) satellite system opportunistically utilizes spectrum allocated to a geostationary satellite system. By leveraging cognitive capabilities and RIS intelligence, RISs are employed on LEO satellite and on the ground to assist the LEO satellite system in sensing and secondary transmission. Simulations validate a 15% improvement in detection probability during sensing and a 10% increase in secondary throughput over traditional networks without utilizing RISs. Additionally, the effect of RIS dimensions on network performance is investigated.