Stochastic geometry modeling of mmWave cellular networks: Analysis and experimental validation

Abstract

Due to the increasing interest of the emerging millimeter wave (mmWave) frequency band for application to cellular networks, new flexible and scalable approaches for their modeling, 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 [1]. In the present paper, we investigate the accuracy of this emerging approach for modeling mmWave cellular networks, by explicitly taking realistic base stations locations, buildings footprints, spatial blockages and empirical channel models into account. The databases of base stations locations and buildings footprints are the same as those used in [2] for the analysis of microwave cellular networks. Our study confirms that an abstraction model based on stochastic geometry is capable of providing accurate estimates of the downlink performance of mmWave cellular networks in dense urban environments.