Challenges in Applying Variational Quantum Algorithms to Dynamic Satellite Network Routing

Do, Phuc Hao, Le, Tran Duc

arXiv.org Artificial Intelligence 

The advent of large-scale Low Earth Orbit (LEO) satellite constellations, spearheaded by initiatives such as SpaceX's Starlink, Amazon's Project Kuiper, and OneWeb, is poised to revolutionize global connectivity Saeed et al. (2020). By deploying thousands of interconnected satellites, these networks promise to deliver high-speed, low-latency internet access to every corner of the globe, including remote and underserved regions Reddy et al. (2023). However, the very characteristics that enable this new paradigm - namely, the massive scale and high orbital velocity of the satellites - introduce unprecedented challenges in network management Hu (2023). The network topology is in a constant state of flux, with inter-satellite links (ISLs) being established and terminated on a timescale of seconds, creating a highly dynamic and complex operational environment Bhattacharjee et al. (2024). At the heart of managing these constellations lies the network routing problem: determining the optimal path for data packets to travel from a source to a destination Zhang et al. (2025); Chen et al. (2021). In this dynamic context, the routing problem is far more complex than in terrestrial networks. It must account for time-varying latencies, intermittent link availability, and vast state spaces.

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