Free-Placement Optimization of Ground Station Locations for Low-Earth Orbit Satellites

2026-06-10

AI Summary

This study addresses the suboptimal downlink throughput of low Earth orbit (LEO) satellite constellations caused by traditionally pre-specified ground station locations, which hinder globally optimal performance. To overcome this limitation, the authors propose SCORE (Sequential Coordinate Optimization with Refinement), a novel framework that enables flexible co-deployment of newly sited and existing ground stations within continuous geographic space. SCORE integrates sequential coordinate selection with iterative refinement to efficiently solve the high-dimensional non-convex optimization problem. Experimental results demonstrate that SCORE reduces the number of function evaluations required for convergence to one-fifth of that needed by differential evolution while achieving up to a 13% increase in downlink throughput. Compared to fixed-site baselines, SCORE improves total downlink capacity by up to 15% and retains over 92% of its performance gain even under infrastructure deployment constraints.

Abstract

Rapidly expanding low Earth orbit satellite constellations are placing increasing demands on terrestrial ground networks, motivating the development of more efficient ground station network designs. Current approaches select sites from predefined locations, limiting optimization to existing infrastructure and constraining performance. In contrast, free-placement optimization operates over a continuous spatial domain on Earth, broadening the search space and allowing higher-throughput configurations at the cost of potentially requiring new infrastructure deployment. In this work, we introduce SCORE (Sequential Cyclic Optimization via Refinement & Evaluation), a two-stage free-placement method for ground station design. SCORE combines sequential coordinate selection with cyclic refinement to manage high-dimensionality, non-convexity, and local minima that challenge global optimizers. We benchmark SCORE against one-shot methods such as differential evolution (DE) and integer programming approaches using locations from Kongsberg Satellite Services and the World Teleport Association. Tests across two commercial Earth observation constellations (Capella Space and ICEYE) and one synthetic Walker-Star constellation show that SCORE requires up to 5x fewer function evaluations to converge relative to DE while improving downlink throughput by up to 13%. Compared to fixed-site methods, unconstrained SCORE achieves up to 15% greater total downlink, establishing a strong empirical performance benchmark for flexible placement; infrastructure-constrained SCORE retains over 92% of this gain while restricting placement to within proximity of existing fiber and power infrastructure. We also explore trade-offs between expanding existing stations and deploying new sites, informing future ground network design for operational constellations.

Problem

• free-placement optimization
• ground station location
• low Earth orbit satellites
• downlink throughput
• ground network design

Innovation

• free-placement optimization
• ground station network design
• SCORE algorithm
• non-convex optimization
• satellite downlink throughput