Link-Aware Routing in Multi-Tier LEO Mega-Constellations

Abstract

In multi-tier low-Earth orbit (LEO) mega-constellations, the mobility of satellites across different orbital altitudes leads to dynamic changes in network topology and inter-satellite link (ISL) states, including ISL duration and capacity. These changes often result in unstable connectivity and disrupted end-to-end data transmission. To address this issue, we formulate a routing optimization problem to determine the optimal ISL path between two end users by maximizing the average ISL utility, considering both ISL duration and capacity. To solve this problem, we propose a routing method that first prunes unstable ISLs using a graph neural network (GNN) and then selects optimal end-to-end paths on the pruned graph using a heuristic routing algorithm. Simulation results demonstrate that the proposed algorithm achieves higher throughput and a lower packet loss rate compared to benchmark methods.