Stochastic Geometry-Based Low Latency Routing in Massive LEO Satellite Networks

TL;DR

This paper introduces a stochastic geometry-based routing algorithm for massive LEO satellite networks that minimizes latency through optimal relay selection and provides bounds and insights on latency factors.

Contribution

It proposes a novel nearest neighbor search algorithm for realistic scenarios and derives bounds on latency, improving routing efficiency in massive LEO satellite networks.

Findings

The proposed algorithm approaches the global optimum in ideal conditions.

Latency is significantly reduced compared to other routing strategies.

Latency bounds are effectively estimated using the proposed approximation techniques.

Abstract

In this paper, the routing in massive low earth orbit (LEO) satellite networks is studied. When the satellite-to-satellite communication distance is limited, we choose different relay satellites to minimize the latency in a constellation at a constant altitude. Firstly, the global optimum solution is obtained in the ideal scenario when there are available satellites at all the ideal locations. Next, we propose a nearest neighbor search algorithm for realistic (non-ideal) scenarios with a limited number of satellites. The proposed algorithm can approach the global optimum solution under an ideal scenario through a finite number of iterations and a tiny range of searches. Compared with other routing strategies, the proposed algorithm shows significant advantages in terms of latency. Furthermore, we provide two approximation techniques that can give tight lower and upper bounds for the latency of the proposed algorithm, respectively. Finally, the relationships between latency and constellation height, satellites' number, and communication distance are investigated.