Coverage Analysis of Integrated Sub-6GHz-mmWave Cellular Networks with Hotspots

TL;DR

This paper presents an analytical framework for integrated Sub-6GHz and mmWave cellular networks with hotspot clustering, providing insights into deployment strategies and performance optimization.

Contribution

It introduces a stochastic geometry-based analysis of integrated networks with clustered mmWave BSs, offering new insights into deployment parameters and coverage optimization.

Findings

Deploying mmWave small cells in hotspots improves coverage over traditional networks.

Extreme association weights for mmWave BSs can harm performance at cell edges or interiors.

An optimal dispersion parameter maximizes coverage probability.

Abstract

Deploying Sub-6GHz networks together with millimeter wave (mmWave) is a promising solution to achieve high data rates in traffic hotspots while guaranteeing sufficient coverage, where mmWave small cells are densely deployed to provide high quality of service. In this paper, we propose an analytical framework to investigate the integrated Sub-6GHz-mmWave cellular networks, in which the Sub-6GHz base stations (BSs) are modeled as a Poisson point process, and the mmWave BSs are clustered following a Poisson cluster process in traffic hotspots. We conduct stochastic geometry-based analysis and derive the performance metrics including the association probability, signal-to-interference-plus-noise ratio coverage probability and average achievable rate, which are validated to be accurate by Monte Carlo simulations. We analyze the impact of various deployment parameters on the network performance to give insights on the network design. In particular, it is shown that deploying mmWave small cells in traffic hotspots will outperform both traditional Sub-6GHz heterogeneous network and isolated mmWave system in terms of the coverage probability. It can also be shown that extremely high and extremely small association weight for mmWave BSs will deteriorate the performance for cell edge users and cell interior users, respectively. Moreover, there exists an optimal pre-decided dispersion parameter of mmWave BSs that contributes to the maximum coverage probability.