A Novel Analytical Model for LEO and MEO Satellite Networks Based on Cox Point Processes

Chang Sik Choi, Francois Baccelli

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This work develops an analytical framework for downlink low Earth orbit (LEO) or medium Earth orbit (MEO) satellite communications, leveraging tools from stochastic geometry. We propose a tractable approach to the analysis of such satellite communication systems, accounting for the fact that satellites are located on circular orbits. We accurately incorporate this geometric property of LEO or MEO satellite constellations by developing a Cox point process model that jointly produces orbits and satellites on these orbits. Our work contrasts with previous modeling studies that presumed satellite locations to be entirely random, thereby overlooking the fundamental fact that satellites are jointly positioned on orbits. Employing this Cox model, we analyze the network performance experienced by users located on Earth. Specifically, we evaluate the no-satellite probability of the proposed network and the Laplace transform of the interference created by such a network. Using it, we compute its SIR (signal-to-interference) distribution, namely its coverage probability. By presenting fundamental network performance as functions of key parameters, this model allows one to assess the statistical properties of downlink LEO or MEO satellite communications and can thus be used as a system-level design tool to operate and optimize forthcoming complex LEO or MEO satellite networks.

Original languageEnglish
Pages (from-to)2265-2279
Number of pages15
JournalIEEE Transactions on Communications
Volume73
Issue number4
DOIs
StatePublished - 2025

Keywords

  • coverage probability
  • Cox point process
  • isotropic model
  • LEO satellite networks
  • MEO satellite networks
  • stochastic geometry

Fingerprint

Dive into the research topics of 'A Novel Analytical Model for LEO and MEO Satellite Networks Based on Cox Point Processes'. Together they form a unique fingerprint.

Cite this