Stochastic Geometry Modeling of Cellular Networks: Analysis, Simulation and Experimental Validation

Abstract

Due to the increasing heterogeneity and deployment density of emerging cellular networks, new flexible and scalable approaches for their modeling, simulation, analysis and optimization are needed. Recently, a new approach has been proposed: it is based on the theory of point processes and it leverages tools from stochastic geometry for tractable system-level modeling, performance evaluation and optimization. In this paper, we investigate the accuracy of this emerging abstraction for modeling cellular networks, by explicitly taking realistic base station locations, building footprints, spatial blockages and antenna radiation patterns into account. More specifically, the base station locations and the building footprints are taken from two publicly available databases from the United Kingdom. Our study confirms that the abstraction model based on stochastic geometry is capable of accurately modeling the communication performance of cellular networks in dense urban environments.

arXiv commentsubmitted for publication

References in corpus (2)

• A Tractable Approach to Coverage and Rate in Cellular Networks
• Average Rate of Downlink Heterogeneous Cellular Networks over Generalized Fading Channels - A Stochastic Geometry Approach

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• Performance Analysis of mmWave Ad Hoc Networks
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• The Meta Distribution of the SIR in Linear Motorway VANETs
• Modeling Cellular Networks in Fading Environments with Dominant Specular Components
• Spatial networks with wireless applications
• Partial Non-Orthogonal Multiple Access (NOMA) in Downlink Poisson Networks
• Analyzing Dependent Placements of Small Cells in a Two-Layer Heterogeneous Network with a Rate Coverage Constraint
• Machine to Machine (M2M) Communications in Virtualized Vehicular Ad Hoc Networks
• The Stochastic Geometry Analyses of Cellular Networks with α-Stable Self-Similarity
• Downlink Non-Orthogonal Multiple Access (NOMA) in Poisson Networks