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Modeling and Analysis of Hybrid GEO-LEO Satellite Networks

Dong-Hyun Jung, Hongjae Nam, Junil Choi, David J. Love

TL;DR

This letter considers a hybrid GEO-LEO satellite network where GEO and LEO satellites are distributed according to independent Poisson point processes and share the same frequency resources and derives an analytical expression for the network’s coverage probability.

Abstract

As the number of low Earth orbit (LEO) satellites rapidly increases, the consideration of frequency sharing or cooperation between geosynchronous Earth orbit (GEO) and LEO satellites is gaining attention. In this paper, we consider a hybrid GEO-LEO satellite network where GEO and LEO satellites are distributed according to independent Poisson point processes (PPPs) and share the same frequency resources. Based on the properties of PPPs, we first analyze satellite-visible probabilities, distance distributions, and association probabilities. Then, we derive an analytical expression for the network's coverage probability. Through Monte Carlo simulations, we verify the analytical results and demonstrate the impact of system parameters on coverage performance. The analytical results effectively estimate the coverage performance in scenarios where GEO and LEO satellites cooperate or share the same resource.

Modeling and Analysis of Hybrid GEO-LEO Satellite Networks

TL;DR

This letter considers a hybrid GEO-LEO satellite network where GEO and LEO satellites are distributed according to independent Poisson point processes and share the same frequency resources and derives an analytical expression for the network’s coverage probability.

Abstract

As the number of low Earth orbit (LEO) satellites rapidly increases, the consideration of frequency sharing or cooperation between geosynchronous Earth orbit (GEO) and LEO satellites is gaining attention. In this paper, we consider a hybrid GEO-LEO satellite network where GEO and LEO satellites are distributed according to independent Poisson point processes (PPPs) and share the same frequency resources. Based on the properties of PPPs, we first analyze satellite-visible probabilities, distance distributions, and association probabilities. Then, we derive an analytical expression for the network's coverage probability. Through Monte Carlo simulations, we verify the analytical results and demonstrate the impact of system parameters on coverage performance. The analytical results effectively estimate the coverage performance in scenarios where GEO and LEO satellites cooperate or share the same resource.

Paper Structure

This paper contains 8 sections, 5 theorems, 14 equations, 3 figures, 1 table.

Table of Contents

  1. Introduction
  2. System model
  3. Mathematical preliminaries
  4. Coverage analysis
  5. Simulation results
  6. Conclusions
  7. Proof of Lemma \ref{['lem:LT']}
  8. Proof of Theorem \ref{['thm:Pcov_tot']}

Key Result

Lemma 1

The probability that the terminal can see at least one GEO satellite is given by and the probability that the terminal can see at least one LEO satellite is

Figures (3)

  • Figure 1: Satellite visible regions, i.e., $\mathcal{A}^{\sigma}_{\mathrm{vis}}$, $\sigma\in\{\mathrm{G},\mathrm{L}\}$.
  • Figure 2: Association probabilities. Unless otherwise stated, we set $\{\alpha_{\mathrm{G}},\alpha_{\mathrm{L}}\}=\{3.6, 4\}$, $\hat{P}_{\mathrm{t}}^{\mathrm{G}} \hat{G}_{0}^{\mathrm{G}}=50$ dB, and $m=3$.
  • Figure 3: Coverage probability versus SINR threshold $\tau$ with various Nakagami fading parameters $m=\{1,2\}$ where $\{\alpha_{\mathrm{G}},\alpha_{\mathrm{L}}\}=\{2.7, 3\}$.

Theorems & Definitions (6)

  • Lemma 1
  • Lemma 2
  • Lemma 3
  • proof
  • Lemma 4
  • Theorem 1