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

arXiv: https://arxiv.org/abs/2606.12667 · HTML: https://mlsanity.com/paper/2606.12667/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 54 references that are in the map.
- First posted on arXiv 10 Jun 2026.

## Builds on (most cited first, 6 of 6)

- [Infiltrating the Sky: Data Delay and Overflow Attacks in Earth Observation Constellations](https://mlsanity.com/paper/2409.00897/) (2024)
- [Gateway Station Geographical Planning for Emerging Non-Geostationary Satellites Constellations](https://mlsanity.com/paper/2309.10581/) (2023)
- [Optimal Ground Station Selection for Low-Earth Orbiting Satellites](https://mlsanity.com/paper/2410.16282/) (2024)
- [Optimizing Satellite Network Infrastructure: A Joint Approach to Gateway Placement and Routing](https://mlsanity.com/paper/2405.01149/) (2024)
- [Optimizing Location Allocation in Urban Management: A Brief Review](https://mlsanity.com/paper/2412.06032/) (2024)
- [Scalable Ground Station Selection for Large LEO Constellations](https://mlsanity.com/paper/2510.03438/) (2025)

## Built on by (most cited first, 1 of 1)

- [Distributed Constraint Optimization via Online Learning and Iterative Pricing with Application to Large-Scale Satellite Scheduling](https://mlsanity.com/paper/2607.25835/) (2026)

## Abstract (arXiv)

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.