Two-tier Spatial Modeling of Base Stations in Cellular Networks
Yifan Zhou, Zhifeng Zhao, Qianlan Ying, Rongpeng Li, Xuan Zhou, and, Honggang Zhang

TL;DR
This paper proposes a two-tier spatial modeling approach for macrocell and microcell base stations in cellular networks, demonstrating that Strauss and Matern cluster processes better fit their respective deployment patterns than Poisson models.
Contribution
It introduces a tier-specific spatial modeling framework that accurately captures the distinct deployment patterns of macrocell and microcell base stations.
Findings
Macrocell BSs are dispersed and modeled by Strauss process.
Microcell BSs are aggregated and modeled by Matern cluster process.
Poisson Point Process is inaccurate for modeling real BS deployments.
Abstract
Poisson Point Process (PPP) has been widely adopted as an efficient model for the spatial distribution of base stations (BSs) in cellular networks. However, real BSs deployment are rarely completely random, due to environmental impact on actual site planning. Particularly, for multi-tier heterogeneous cellular networks, operators have to place different BSs according to local coverage and capacity requirement, and the diversity of BSs' functions may result in different spatial patterns on each networking tier. In this paper, we consider a two-tier scenario that consists of macrocell and microcell BSs in cellular networks. By analyzing these two tiers separately and applying both classical statistics and network performance as evaluation metrics, we obtain accurate spatial model of BSs deployment for each tier. Basically, we verify the inaccuracy of using PPP in BS locations modeling for…
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Taxonomy
TopicsPoint processes and geometric inequalities · Spatial and Panel Data Analysis · Urban Transport and Accessibility
