Coverage in Downlink Heterogeneous mmWave Cellular Networks with User-Centric Small Cell Deployment

TL;DR

This paper models and analyzes the coverage probability in downlink mmWave heterogeneous networks with user-centric small cell deployment, considering clustered user distributions, directional beamforming, and LOS/NLOS path loss effects.

Contribution

It introduces a stochastic geometry framework for modeling clustered UEs in mmWave networks and derives coverage probability expressions considering realistic propagation and beamforming features.

Findings

Coverage improves with smaller UE clusters.

Narrower beamwidth enhances coverage.

Clustered users outperform Poisson distributed users in coverage.

Abstract

A K-tier heterogeneous downlink millimeter wave (mmWave) cellular network with user-centric small cell deployments is studied in this paper. In particular, we consider a heterogeneous network model with user equipments (UEs) being distributed according to a Poisson Cluster Process (PCP). Specifically, we address two cluster processes, namely (i) Thomas cluster process, where the UEs are clustered around the base stations (BSs) and the distances between UEs and the BS are modeled as Gaussian distributed, and (ii) Matern cluster process, where the UEs are scattered according to a uniform distribution. In addition, distinguishing features of mmWave communications including directional beamforming and a sophisticated path loss model incorporating both line-of-sight (LOS) and non-line-of-sight (NLOS) transmissions, are taken into account. Initially, the complementary cumulative distribution function (CCDF) and probability density function (PDF) of path loss are provided. Subsequently, using tools from stochastic geometry, we derive a general expression for the signal-to-interference-plus-noise ratio (SINR) coverage probability. Our results demonstrate that coverage probability can be improved by decreasing the size of UE clusters around BSs, decreasing the beamwidth of the main lobe, or increasing the main lobe directivity gain. Moreover, interference has noticeable influence on the coverage performance of our model. We also show that better coverage performance is achieved in the presence of clustered users compared to the case in which the users are distributed according to a Poisson Point Process (PPP).