Improved Coverage of Massive MIMO HetNets Modeled Using Stochastic Geometry Techniques

Abstract

Most current stochastic geometric modeling of heterogeneous cellular networks (HetNets) assumes independent deployment of small-cell base stations (SBSs) with respect to macrocell base stations (MBSs), which leads to limited enhancement in network coverage and capacity. Therefore, in this paper we propose a new HetNet deployment model where the locations of SBSs are correlated with those of the MBSs. We place the SBSs at the vertices of each macrocell, where the macrocells are modeled by a Poisson-Voronoi tessellation with the MBSs as seeds. Theoretical analysis of this deployment scheme is performed using the tools of stochastic geometry. A novel distribution is also derived for the distance between the typical user and its closest SBS. Two tractable expressions for the distance distribution between a user and its closest SBS are presented, obtained by modeling the locations of SBSs as a Poisson point process and a $\beta$-Ginibre point process. The latter models the SBS placement more accurately as it captures the correlation between the MBSs and SBSs. The performance of the proposed model is evaluated for several values of the network parameters and our results demonstrate the improvement in the coverage probability and rate coverage compared to other schemes in the literature.