NDLI: On the Spatial Distribution of Base Stations and Its Relation to the Traffic Density in Cellular Networks

Content Provider	IEEE Xplore Digital Library
Author	Sheng Zhou Dongheon Lee Bingjie Leng Xuan Zhou Honggang Zhang Zhisheng Niu
Copyright Year	2013
Abstract	The spatial distribution of base stations (BSs) and traffic demands is essential for efficient network planning and BS sleeping, which are key elements of green cellular networking. This paper investigates their statistics, relation, and modeling, based on large-scale measurement data from commercial cellular networks. The spatial distribution of BSs shows not only high nonuniformity over a region but also diverse patterns in different regions, and thus the widely used homogeneous Poisson point process can only approximate the BS patterns in a specific small area. Therefore, the inhomogeneous PPP (IPPP), in particular, the Cox point process with spatially varying intensity is used to model the BS distribution over any spatial scale. To model the intensity distribution of the IPPP, we exploit the relation, shown to be sublinear, between the BS distribution and the peak hour (PH) traffic density, based on the finding that the PH traffic density can be approximated by a log-normal distribution. Finally, we propose a spatial modeling framework for network simulations, and discuss potential applications of the proposed spatial distribution model of the BS patterns and the PH traffic density.
Starting Page	998
Ending Page	1010
Page Count	13
File Size	10180321
File Format	PDF
ISSN	21693536
Volume Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Spatial analysis Modeling Pattern recognition Base stations Poisson equations Cellular networks Telecommunication traffic inhomogeneous Poisson point process Spatial analysis and modeling spatial pattern of base stations Cox point process traffic density
Content Type	Text
Resource Type	Article
Subject	Computer Science Engineering Materials Science

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