SWIFT-SAT: Efficient and On-Demand Spectrum Coexistence for Satellite-Terrestrial Systems

The escalating demand for wireless communications, fueled by emerging applications, has led to radio spectrum congestion. This project designs efficient schemes for spectrum coexistence between satellite and terrestrial systems. One spectrum sharing approach used today is called a Spectrum Access System (SAS), a centralized database and control system that assigns channels to users in real-time such that other users are protected from interference. Existing SAS solutions support terrestrial-terrestrial sharing in situations where every device transmits as well as receives. The new schemes developed in this project extend the SAS concept to manage satellite-terrestrial spectrum sharing. Key challenges addressed in the project include (a) some devices on the ground and in orbit are passive receivers that cannot be detected by spectrum sensing, and (b) the SAS must manage aggregate interference of multiple transmitters with awareness of dynamically changing receiver beams. The findings from this project will provide valuable insights for ongoing efforts by government policy-makers to open mid-bands and high-bands for spectrum sharing and commercial use. The project has three main research thrusts. The first thrust explores architectural options for the satellite-terrestrial SAS. Key considerations for the architecture include: effective data collection regarding systems, locations, and beams; efficient calculation of aggregate interference; efficient calculation of coexistence solutions, which may involve scalable decentralized algorithms run by affected users; and minimization of changes to existing satellite system protocols. The second thrust develops effective SAS-based methods to achieve interference protection for satellite systems, including channel estimation and aggregate interference computation. Factors considered include directional antennas, advanced interference management schemes such as MIMO and successive interference cancellation, terrain blockage, idle periods, partial spectrum utilization, and risk-based interference protection. The third thrust designs a multi-time scale coexistence scheme: precalculated solutions for satellites with fixed beams or ground systems, and real-time calculated solutions for satellites with unpredictable beams and mobile ground systems. The initially nonlinear optimization problem is linearized to obtain Mixed Integer Linear Program (MILP) formulations. Multiple algorithms to solve the MILP problems are developed: use subproblem partitioning to enable real time optimization on GPUs, use reinforcement learning to develop low-complexity algorithms, and use federated learning to enable decentralized solution across a network of terrestrial users. Evaluation of the research includes technical and policy assessment of candidate architectures, verification of channel predictions, and software prototypes of coexistence algorithms. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.