Optimizing Satellite Selection and User Association in Multi-Orbit Satellite Constellations

LEO satellites are key to global coverage in 6G wireless communications. However, efficiently selecting service satellites in multi-orbit systems remains a challenge due to dynamic topologies and limited resources. To address this challenge, this paper proposes a joint optimization framework for satellite selection, user association, and resource allocation in Space-AirGround Integrated Networks (SAGINs). We design a computationally efficient algorithm that leverages Markov approximation for satellite selection and employs matching game theory for user association and resource allocation. Our simulation results show that the proposed algorithms outperform benchmark methods.