LEO Topology Design Under Real-World Deployment Constraints

The performance of large-scale Low-Earth-Orbit (LEO) networks, which consist of thousands of satellites interconnected by optical links, is dependent on its network topology. Existing topology designs often assume idealized conditions and do not account for real-world deployment dynamics, such as partial constellation deployment, daily node turnovers, and varying link availability, making them inapplicable to real LEO networks. In this paper, we develop two topology design methods that explicitly operate under real-world deployment constraints: the Long–Short Links (LSL) method, which systematically combines long-distance shortcut links with short-distance local links, and the Simulated Annealing (SA) method, which constructs topologies via stochastic optimization. Evaluated under both full deployment and partial deployment scenarios using 3-months of Starlink data, our methods achieve up to 45% lower average end-to-end delay, 65% fewer hops, and up to $2.3\times$ higher network capacity compared to +Grid. Both methods are designed to handle daily node turnovers by incrementally updating the topology, maintaining good network performance while avoiding costly full reconstruction of the topology.

💡 Research Summary

This paper addresses the gap between theoretical LEO satellite network topology designs and the realities of operational constellations. Recognizing that real deployments are often partial, uneven, and subject to daily satellite turnover, the authors introduce two topology construction methods that explicitly operate under these constraints: Long‑Short Links (LSL) and Simulated Annealing (SA). Both methods start by constructing a set of “stable links” – inter‑satellite optical links that remain feasible throughout an entire orbital cycle, satisfying line‑of‑sight and maximum‑range requirements. LSL systematically combines short, local links with a configurable proportion of long‑distance shortcut links, providing a tunable balance between local connectivity and global shortcut efficiency. SA treats the topology design as a multi‑objective stochastic optimization problem, minimizing average end‑to‑end delay, hop count, and link breakage while respecting per‑satellite ISL degree limits (3 or 4 links).

To handle the continuous addition and removal of satellites, the authors propose an incremental update algorithm that preserves as much of the previous day’s topology as possible, only adding or dropping links required by the changed node set. This avoids costly full reconstructions and reduces link churn.

The methods are evaluated using three months of real Starlink Shell‑1 data (October–December 2024) and synthetic full‑deployment scenarios. Compared with the widely used +Grid topology and a motif‑style design, LSL achieves up to 45 % lower average latency, while SA reduces average hop count by up to 64 %. Both approaches deliver up to 2.3× higher aggregate throughput and maintain low link breakage rates (1.0–1.3 %). Importantly, these gains persist under partial, uneven deployments and with daily node turnover, demonstrating practical applicability.

The study contributes a comprehensive framework that integrates realistic deployment dynamics, stable‑link selection, and both deterministic and stochastic topology synthesis. It opens avenues for future work on exploiting transient links, extending optimization across multiple shells, and real‑time adaptive topology management in operational LEO networks.