The Intensity Matching Approach: A Tractable Stochastic Geometry Approximation to System-Level Analysis of Cellular Networks

TL;DR

The paper introduces the intensity matching approach, a stochastic geometry-based method for tractable and accurate system-level analysis of cellular networks, accounting for practical factors like propagation, traffic, and environment.

Contribution

It presents a novel approximation technique that simplifies complex cellular network models using intensity measures, enabling practical analysis of various system parameters.

Findings

Provides integral expressions for spectral efficiency and throughput.

Validates the approach with empirical urban data.

Unveils impact of base station density and blockages.

Abstract

The intensity matching approach for tractable performance evaluation and optimization of cellular networks is introduced. It assumes that the base stations are modeled as points of a Poisson point process and leverages stochastic geometry for system-level analysis. Its rationale relies on observing that system-level performance is determined by the intensity measure of transformations of the underlaying spatial Poisson point process. By approximating the original system model with a simplified one, whose performance is determined by a mathematically convenient intensity measure, tractable yet accurate integral expressions for computing area spectral efficiency and potential throughput are provided. The considered system model accounts for many practical aspects that, for tractability, are typically neglected, e.g., line-of-sight and non-line-of-sight propagation, antenna radiation patterns, traffic load, practical cell associations, general fading channels. The proposed approach, more importantly, is conveniently formulated for unveiling the impact of several system parameters, e.g., the density of base stations and blockages. The effectiveness of this novel and general methodology is validated with the aid of empirical data for the locations of base stations and for the footprints of buildings in dense urban environments.