Coverage in networks with hybrid terahertz, millimeter wave, and microwave transmissions

Xueyuan Wang, M. Cenk Gursoy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, a three-tier heterogeneous network (HetNet) is considered, where access points (APs), small-cell base stations (SBSs) and macrocell BSs (MBSs) transmit in terahertz (THz), millimeter wave (mmWave), microwave frequency bands, respectively. Distinguishing features of transmission in each frequency band are taken into account, including the blockage model, path loss, beamforming and small-scale fading. Path loss based association criterion is considered for user equipments (UEs). By using tools from stochastic geometry, the complementary cumulative distribution function (CCDF) of the received signal power, the Laplace transform of the aggregate interference, and the SINR coverage probability are investigated, and general expressions are obtained. Finally, numerical results show that making the THz APs more densely distributed can enhance the received signal power but decrease the SINR coverage probability.

Original languageEnglish (US)
Title of host publication2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728197944
DOIs
StatePublished - Jan 9 2021
Event18th IEEE Annual Consumer Communications and Networking Conference, CCNC 2021 - Virtual, Las Vegas, United States
Duration: Jan 9 2021Jan 13 2021

Publication series

Name2021 IEEE 18th Annual Consumer Communications and Networking Conference, CCNC 2021

Conference

Conference18th IEEE Annual Consumer Communications and Networking Conference, CCNC 2021
Country/TerritoryUnited States
CityVirtual, Las Vegas
Period1/9/211/13/21

Keywords

  • Coverage analysis
  • Heterogenous cellular networks
  • MmWave transmissions
  • Stochastic geometry
  • THz transmissions

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition

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