Evaluating the Accuracy of Stochastic Geometry Based Models for LEO Satellite Networks Analysis

作者：Ruibo Wang, Mustafa A. Kishk, Mohamed-Slim Alouini · 发表于：IEEE Communications Letters · 年份：2022 · DOI：10.1109/lcomm.2022.3194210 · 被引用次数：55 · 研究领域：Computer Science

This letter investigates the accuracy of recently proposed stochastic geometry-based modeling of low earth orbit (LEO) satellite networks. In particular, we use the Wasserstein Distance-inspired method to analyze the distances between different models, including Fibonacci lattice and orbit models. We propose an algorithm to calculate the distance between the generated point sets. Next, we test the algorithm’s performance and analyze the distance between the stochastic geometry model and other more widely acceptable models using numerical results.