Hierarchical Battery-Aware Game Algorithm for ISL Power Allocation in LEO Mega-Constellations
Kangkang Sun, Jianhua Li, Xiuzhen Chen, Jianyong Zheng, Minyi Guo

TL;DR
The paper introduces HBAG, a game-theoretic algorithm for ISL power allocation in LEO mega-constellations, ensuring energy sustainability and scalability across different constellation sizes.
Contribution
It presents a unified hierarchical framework that guarantees equilibrium convergence and scalability, outperforming static methods in energy sustainability and flow regulation.
Findings
HBAG achieves 100% energy sustainability rate in experiments.
It reduces flow violation ratio by 78.3%.
Scales linearly to 5,000 satellites with less than 75 ms per-slot runtime.
Abstract
Sustaining high inter-satellite link (ISL) throughput under intermittent solar harvesting is a fundamental challenge for LEO mega-constellations. Existing works impose static power ceilings that ignore real-time battery state and comprehensive onboard power budgets, causing eclipse-period energy crises. Learning-based approaches capture battery dynamics but lack equilibrium guarantees and do not scale beyond small constellations. We propose the \textbf{Hierarchical Battery-Aware Game (HBAG)} algorithm, a unified game-theoretic framework for ISL power allocation that operates identically across finite and mega-constellation regimes. For finite constellations, HBAG converges to a unique variational equilibrium; as constellation size grows, the same distributed update rule converges to the Mean Field Game (MFG) equilibrium without algorithm redesign. Comprehensive experiments on Starlink…
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