AI & ML
Topology-Aware Cooperative Beam-Hopping Scheduling for Efficient Resource Allocation in LEO Satellite Systems
arXiv cs.NI0 views
arXiv:2610.11103v1 Announce Type: new Abstract: The dynamic topology and heterogeneous traffic demands of multi-satellite systems present substantial challenges for beam-hopping (BH) resource management. This letter develops a topology-aware cooperative BH framework for multi-satellite systems under partial observability. A lightweight load-balancing scheme first determines the serving relationships, which are then exploited to construct an association-induced satellite-user graph. A two-phase graph neural network (GNN) extracts episode-level topology-aware structural identities for parameter-sharing agents, while a recurrent multi-agent proximal policy optimization (MAPPO) policy handles slot-level dynamics for joint beam scheduling and onboard power control. Simulation results demonstrate notable gains in energy efficiency, throughput, and fairness over the baselines.
Source:https://arxiv.org/abs/2610.11103PreviousFrom Echoes to Evidence: Cooperative Fusion for Integrated Sensing and CommunicationNextOnline Adaptive Computation Reuse in Collaborative Edge Computing: A Two-Timescale Approach
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