Adaptive Entanglement-Aware Routing for Satellite Quantum Networks under Orbital and Atmospheric Variability

TL;DR

This work tackles the problem of maintaining entanglement distribution in satellite-based quantum networks subject to orbital dynamics and atmospheric variability. It introduces a dynamic, entanglement-aware routing framework that jointly models orbital geometry, channel fading, and trust-based link evaluation, using a multi-layer loop of sensing, adaptive weighting, routing, and recovery. Key contributions include a time-dependent link state model $\mathcal{L}_{ij}(t)$ with a composite cost $W_{ij}(t)$, a constrained shortest-path routing strategy with entanglement purification, and a Monte Carlo evaluation showing up to $275\%$ gains in key rate and $15\%$ gains in fidelity across realistic LEO scenarios, with sub-linear scaling to networks of up to 100 nodes. This approach demonstrates robust, scalable routing under diverse atmospheric regimes and supports near-term deployment of global quantum satellite constellations.

Abstract

The expansion of satellite-based quantum networks requires adaptive routing mechanisms that can sustain entanglement under dynamic orbital and atmospheric conditions. Conventional schemes, often tailored to static or idealised topologies, fail to capture the combined effects of orbital motion, fading, and trust variability in inter-satellite links. This work proposes an \textit{adaptive entanglement-aware routing framework} that jointly accounts for orbital geometry, atmospheric attenuation, and multi-parameter link evaluation. The routing metric integrates fidelity, trust, and key-rate weights to maintain connectivity and mitigate loss from turbulence and fading. Monte Carlo simulations across multiple orbital densities ($ρ= 10^{-6}$~km$^{-3}$) and environmental regimes, standard atmosphere, strong turbulence, and clear-sky LEO show up to a 275\% improvement in key generation rate and a 15\% increase in effective entanglement fidelity over existing adaptive methods. The framework achieves sub-linear path-length scaling with network size and remains robust for fading variances up to $σ_{\mathrm{fade}}=0.1$, demonstrating strong potential for future global quantum constellations.

Figures (4)

• Figure 1: Proposed multi-layer methodology integrating environment awareness, adaptive intelligence, routing, and fidelity-trust recovery.
• Figure 2: Mean Effective Fidelity vs. Node Count Across Environmental Regimes.
• Figure 3: Normalised Key Rate vs. Fading Variance for Different Network Sizes.
• Figure 4: Mean Path Length vs. Satellite Density Across Atmospheric Regimes.