Demonstration Platform to Emulate Cognitive GEO-LEO Dual Satellite System

Cognitive radio technology represents a transformative advancement in modern telecommunications, enabling real-time adaptation and optimisation of communication systems through sensing, analysis, and decision-making. In the context of satellite communications, cognitive satellite networks leverage these capabilities to enable dynamic spectrum access, dynamic resource management, and adaptive network optimisation. These enhancements improve spectral efficiency, maximise bandwidth utilisation, and enhance overall network performance, leading to more scalable, resilient, and cost-effective satellite operations. In this study, we develop a laboratory-scale demonstration platform to emulate a cognitive GEO-LEO dual satellite system using software-defined radios, which operate under controlled conditions without incorporating orbital dynamics such as Doppler effects or variable angular velocities. The geostationary satellite is designated as the primary user (PU), while the low Earth orbit satellite operates as the secondary user (SU). A preamble detection-based sensing algorithm is developed to identify PU transmissions, ensuring efficient spectrum utilisation. Additionally, a radio environment map (REM) server is implemented to manage control-plane data required for network decision-making. A dynamic spectrum access algorithm, integrated into the REM server, utilises spectrum sensing reports to enable cognitive network behaviour. We evaluate the performance of the PU and SU in terms of spectral occupancy and throughput. Furthermore, the performance of the proposed sensing algorithm is assessed based on missed detection rates. The results demonstrate that the cognitive system’s dynamic spectrum access capabilities significantly enhance spectral occupancy and system throughput, validating its effectiveness in optimising satellite communication networks.