5 research outputs found
Large-scale Spatial Distribution Identification of Base Stations in Cellular Networks
The performance of cellular system significantly depends on its network
topology, where the spatial deployment of base stations (BSs) plays a key role
in the downlink scenario. Moreover, cellular networks are undergoing a
heterogeneous evolution, which introduces unplanned deployment of smaller BSs,
thus complicating the performance evaluation even further. In this paper, based
on large amount of real BS locations data, we present a comprehensive analysis
on the spatial modeling of cellular network structure. Unlike the related
works, we divide the BSs into different subsets according to geographical
factor (e.g. urban or rural) and functional type (e.g. macrocells or
microcells), and perform detailed spatial analysis to each subset. After
examining the accuracy of Poisson point process (PPP) in BS locations modeling,
we take into account the Gibbs point processes as well as Neyman-Scott point
processes and compare their accuracy in view of large-scale modeling test.
Finally, we declare the inaccuracy of the PPP model, and reveal the general
clustering nature of BSs deployment, which distinctly violates the traditional
assumption. This paper carries out a first large-scale identification regarding
available literatures, and provides more realistic and more general results to
contribute to the performance analysis for the forthcoming heterogeneous
cellular networks
Large-scale Spatial Distribution Identification of Base Stations in Cellular Networks
International audienceThe performance of cellular system significantlydepends on its network topology while cellular networks areundergoing a heterogeneous evolution. This promising trendintroduces unplanned deployment of smaller base stations (BSs),thus complicating the performance evaluation even further. Inthis paper, based on large amount of real BS locations data,we present a comprehensive analysis on the spatial modeling ofcellular network structure. Unlike the related works, we dividethe BSs into different subsets according to geographical factor(e.g. urban or rural) and functional type (e.g. macrocells ormicrocells), and perform detailed spatial analysis to each subset.After recovering the inaccuracy of the Poisson point process(PPP) in BS locations modeling, we take into account the Gibbspoint processes as well as Neyman-Scott point processes andcompare their performance in view of large-scale modeling test.Finally, we turn to the BS quantitative distribution analysis,and reveal the general clustering nature of BSs deployment,which distinctly violates the traditional assumption. Specifically,the -Stable distribution can most precisely reproduce the BSdensity among the popular candidate distributions. This papercarries out a first large-scale identification regarding availableliteratures, and provides more realistic and general results tocontribute to the performance analysis for the forthcomingheterogeneous cellular networks