Coverage in Heterogeneous Downlink Millimeter Wave Cellular Networks

Esma Turgut, M. Cenk Gursoy

Research output: Contribution to journalArticlepeer-review

67 Scopus citations

Abstract

In this paper, we provide an analytical framework to analyze heterogeneous downlink millimeter-wave (mm-wave) cellular networks consisting of K tiers of randomly located base stations (BSS), where each tier operates in an mm-wave frequency band. Signal-To-interference-plus-noise ratio (SINR) coverage probability is derived for the entire network using tools from stochastic geometry. The distinguishing features of mm-wave communications, such as directional beamforming, and having different path loss laws for line-of-sight and non-line-of-sight links are incorporated into the coverage analysis by assuming averaged biased-received power association and Nakagami fading. By using the noise-limited assumption for mm-wave networks, a simpler expression requiring the computation of only one numerical integral for coverage probability is obtained. Also, the effect of beamforming alignment errors on the coverage probability analysis is investigated to get insight on the performance in practical scenarios. Downlink rate coverage probability is derived as well to get more insights on the performance of the network. Moreover, the effect of deploying low-power smaller cells and the impact of biasing factor on energy efficiency is analyzed. Finally, a hybrid cellular network operating in both mm-wave and \mu-wave frequency bands is addressed.

Original languageEnglish (US)
Article number7931577
Pages (from-to)4463-4477
Number of pages15
JournalIEEE Transactions on Communications
Volume65
Issue number10
DOIs
StatePublished - Oct 2017

Keywords

  • Heterogeneous cellular networks
  • Poisson point process
  • coverage probability
  • mmWave cellular networks
  • stochastic geometry

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Coverage in Heterogeneous Downlink Millimeter Wave Cellular Networks'. Together they form a unique fingerprint.

Cite this