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Author

Yassine Afif

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2026

Multi-Agent Reinforcement Learning for Handover Management and Power Allocation in LEO Satellite Networks

Due to their high orbital velocity, low Earth orbit (LEO) satellites traverse overhead in minutes, forcing ground users to frequently switch their serving beam or satellite. Such handover disrupts ongoing transmissions, introduces signalling overheads and synchronization delays across the constellation, and reduces the...

Yassine Afif, M. Almekhlafi, Antoine Lesage-Landry et al. · 0 citations
Preprint Aug 2026

Multi-Agent Reinforcement Learning for Joint Handover Management and Power Allocation in Multi-Orbit Satellite Networks

The proposed multi-agent reinforcement learning policy attains slightly higher throughput with fewer handovers by offloading a fraction of the users to the MEO and GEO layers, an emergent multi-orbit behavior that drives its favorable throughput and handover trade-off.

Yassine Afif, Ashutosh Balakrishnan, Philippe Martins et al. · 0 citations

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