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This paper addresses the evolving role of Non-geostationary (Non-GSO) satellite systems, specifically focusing on homogeneous constellations in either low Earth orbit (LEO) or medium Earth orbit (MEO). These systems, known for their low latency due to their proximity to Earth, incorporate advanced developments in payload and antenna technologies including adaptive radio resource management and beamforming capabilities. The study investigates key issues in multi-beam satellite systems, including beam footprint design, user-to-beam assignments, and the optimal distribution of radio resources. We introduce a novel problem aimed at optimizing beam placement and balancing user loads in Non-GSO satellite systems, which results in a mixed-integer non-convex formulation. For practically appealing applications, we relax the binary variables and propose the continuous relaxation problem using the inner convex approximation framework and a penalty method to further speed up the convergence. The proposed method addresses a complex, previously unexplored non-convex and NP-hard optimization problem, offering a practical and efficient polynomial-time solution. Experimental results underscore the effectiveness of our approach, demonstrating significant improvements over existing benchmarks and providing new insights into the optimization of satellite communication systems.

Demand-Based Adaptive Multi-Beam Placement and Resource Allocation in Non-GSO Satellite Systems