English

Hierarchical Battery-Aware Game Algorithm for ISL Power Allocation in LEO Mega-Constellations

Computer Science and Game Theory 2026-04-10 v2

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 Shell~A (M=172M=172, θ=0.38\theta=0.38) show that HBAG achieves \textbf{100\% energy sustainability rate} (ESR) in all 10 independent runs, representing a \textbf{+87.4\%} gain over the traditional static-power baseline (SATFLOW-L, ESR\,=\,12.6\%). At the same time, HBAG reduces the flow violation ratio by \textbf{78.3\%} to 7.62\% (below the 10\% industry tolerance). HBAG further maintains ESR 93.4%\geq 93.4\% across eclipse fractions θ[0,0.6]\theta \in [0,\,0.6] and scales linearly to 5{,}000 satellites with less than 75\,ms per-slot runtime, confirming deployment feasibility at full Starlink scale.

Cite

@article{arxiv.2603.29506,
  title  = {Hierarchical Battery-Aware Game Algorithm for ISL Power Allocation in LEO Mega-Constellations},
  author = {Kangkang Sun and Jianhua Li and Xiuzhen Chen and Jianyong Zheng and Minyi Guo},
  journal= {arXiv preprint arXiv:2603.29506},
  year   = {2026}
}

Comments

19 pages, 4 figures, has submitted to IEEE Transactions on Mobile Computing

R2 v1 2026-07-01T11:45:52.373Z