Modeling and Analysis of GEO Satellite Networks

TL;DR

This paper models GEO satellite networks using stochastic geometry, deriving coverage probabilities and validating results through simulations, providing a new analytical framework for network performance estimation.

Contribution

It introduces a novel stochastic geometry-based model for GEO satellite distribution and analyzes coverage, incorporating satellite visibility and distance distributions.

Findings

Derived analytical expressions for coverage probability.

Validated model accuracy with Monte Carlo simulations.

Provided a practical approach for estimating GEO network performance.

Abstract

The extensive coverage offered by satellites makes them effective in enhancing service continuity for users on dynamic airborne and maritime platforms, such as airplanes and ships. In particular, geosynchronous Earth orbit (GEO) satellites ensure stable connectivity for terrestrial users due to their stationary characteristics when observed from Earth. This paper introduces a novel approach to model and analyze GEO satellite networks using stochastic geometry. We model the distribution of GEO satellites in the geostationary orbit according to a binomial point process (BPP) and examine satellite visibility depending on the terminal's latitude. Then, we identify potential distribution cases for GEO satellites and derive case probabilities based on the properties of the BPP. We also obtain the distance distributions between the terminal and GEO satellites and derive the coverage probability of the network. We further approximate the derived expressions using the Poisson limit theorem. Monte Carlo simulations are performed to validate the analytical findings, demonstrating a strong alignment between the analyses and simulations. The simplified analytical results can be used to estimate the coverage performance of GEO satellite networks by effectively modeling the positions of GEO satellites.