Ultra Reliable Low Latency Routing in LEO Satellite Constellations: A Stochastic Geometry Approach

TL;DR

This paper develops a stochastic geometry-based framework to optimize and analyze ultra-reliable, low-latency routing in LEO satellite constellations, providing theoretical bounds and practical algorithms.

Contribution

It introduces a multi-objective optimization approach for reliability and latency, deriving analytical expressions and proposing a near-optimal relay selection algorithm.

Findings

Derived upper bounds for reliability and latency in LEO routing

Proposed a relay selection algorithm approaching optimal performance

Validated analytical models with Monte Carlo simulations

Abstract

In recent years, LEO satellite constellations have become envisioned as a core component of the next-generation wireless communication networks. The successive establishment of mega satellite constellations has triggered further demands for satellite communication advanced features: high reliability and low latency. In this article, we first establish a multi-objective optimization problem that simultaneously maximizes reliability and minimizes latency, then we solve it by two methods. According to the optimal solution, ideal upper bounds for reliability and latency performance of LEO satellite routing can be derived. Next, we design an algorithm for relay satellite subset selection, which can approach the ideal upper bounds in terms of performance. Furthermore, we derive analytical expressions for satellite availability, coverage probability, and latency under the stochastic geometry (SG) framework, and the accuracy is verified by Monte Carlo simulation. In the numerical results, we study the routing performance of three existing mega constellations and the impact of different constellation parameter configurations on performance. By comparing with existing routing strategies, we demonstrate the advantages of our proposed routing strategy and extend the scope of our research.