Performance Analysis of SAGIN from the Relay Perspective: A Spherical Stochastic Geometry Approach

TL;DR

This paper evaluates the performance of SAGIN from a relay perspective using spherical stochastic geometry, introducing new metrics and analytical expressions to assess network performance and the impact of satellite topology.

Contribution

It presents a novel relay perspective analysis of SAGIN using spherical stochastic geometry, deriving analytical expressions for key performance metrics.

Findings

Derived closed-form expression for backhaul rate exceedance probability (BREP)

Analyzed the impact of satellite topology on network performance

Determined minimum HAP transmission power for data rate demands

Abstract

In recent years, the satellite-aerial-ground integrated network (SAGIN) has become essential in meeting the increasing demands for global wireless communications. In SAGIN, high-altitude platforms (HAPs) can serve as communication hubs and act as relays to enhance communication performance. In this paper, we evaluate network performance and analyze the role of HAPs in SAGIN from the relay perspective. Based on this unique perspective, we introduce three metrics to evaluate the performance, named the average access data rate, the average backhaul data rate, and the backhaul rate exceedance probability (BREP). Considering the need for dynamic topology and interference analysis, we choose spherical stochastic geometry (SSG) as a tool and derive analytical expressions for the above metrics to achieve low-complexity performance evaluation. Specifically, we provide a closed-form expression for the end-to-end performance metric BREP. Given that there is no existing literature in the SSG field studying networks from a relay perspective, we specifically investigate the impact of satellite network topology on performance in our numerical results to further highlight the advantages of the SSG framework. Additionally, we analyze the minimum HAP transmission power required to maintain both short-term and long-term data rate demands.