Beam-Hopping Scheduling for High-Priority and Time-Sensitive Services in Low-Earth-Orbit Satellite Networks

Beam-Hopping (BH) dynamically adjusts beam pointing and dwell time to overcome the rigid resource allocation of traditional fixed beam coverage. This paper addresses the BH scheduling problem in low-Earth-orbit (LEO) satellite networks for high-priority and time-sensitive services. A system-gain maximization model and a heuristic beam scheduling algorithm (HBSA) that pre-schedules critical traffic and greedily allocates remaining resources under interference and fairness constraints are proposed. Furthermore, this paper extends the framework with a graph reinforcement learning beam-hopping scheduling scheme (GRL-BHS) that captures structural network dependencies for near-optimal adaptive scheduling. Simulations against seven benchmarks show that the HBSA achieves near-optimal gain (within 2% of MWC and GRL-BHS), ensures high-priority satisfaction, maintains a Jain fairness index above 0.84 under heavy load, and reduces signaling overhead by an order of magnitude, while preserving a low polynomial complexity of O(T×J×K+T×K2). GRL-BHS offers the highest gain at the cost of offline training, whereas HBSA is the most balanced and practically deployable solution, providing a solid foundation for future intelligent BH scheduling in mega constellations.