Joint Power Allocation and Beam Scheduling in Beam-Hopping Satellites: A Two-Stage Framework With a Probabilistic Perspective

• Published in: IEEE transactions on wireless communications Vol. 23; no. 10; pp. 14685 - 14701
• Main Authors: Chen, Lin, Wu, Linlong, Lagunas, Eva, Wang, Anyue, Lei, Lei, Chatzinotas, Symeon, Ottersten, Bjorn
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: beam hopping; binary quadratic programming; Design optimization; Energy consumption; Energy conversion efficiency; Energy minimization; Illumination; Iterative methods; Lighting; Payloads; power control; Quadratic programming; Resource management; Satellite broadcasting; Satellite communications; Satellites; Scheduling; Statistical analysis; Vectors; Wireless communication
• DOI: 10.1109/TWC.2024.3417707
• ISSN: 1536-1276

Beam-hopping (BH) technology, integral to multi-beam satellite systems, adapts beam activation to the variable communication demands of terrestrial users. The optimization of power allocation and beam illumination scheduling constitutes the core design challenge in BH systems, especially under the constraint on a limited number of simultaneously active beams due to restricted radio frequency chain availability. This paper proposes a two-stage BH design solution, which minimizes energy consumption in BH satellite communications while accommodating the heterogeneous demands of users. The first stage addresses the coupling variables of power and beam status by recasting the allocation and scheduling problem through a statistical lens, thus breaking down the intricate relationship between variables. To manage the resulting non-convex challenge, we propose an iterative method that capitalizes on the optimality conditions inherent to this problem. This method is designed to procure a statistically-informed solution that aligns with our reformulated interpretation. Subsequently, the second stage maps this solution into a concrete beam illumination schedule, employing binary quadratic programming techniques. A penalty-based iterative method is applied, ensuring convergence to a locally optimal solution. Through numerical simulations, the proposed framework has been validated for its efficacy in improving energy efficiency and accurately matching demands.