Coverage analysis for cellular-connected uavs with 3D antenna patterns

Xueyuan Wang, M. Cenk Gursoy

Research output: Chapter in Book/Entry/PoemConference contribution

3 Scopus citations

Abstract

In this paper, we consider cellular-connected unmanned aerial vehicle (UAV) networks, in which the UAVs are aerial user equipments (UEs) served by the ground base stations (GBSs). A realistic ground-to-air channel model, with line of sight (LOS) and non-LOS (NLOS) transmissions, is incorporated into the analysis. Three dimensional (3D) antenna radiation combing the vertical and horizontal patterns is taken into account for the GBSs. More importantly, 3D antenna patterns are also considered for the UAVs. In particular, we compare the performances of four types of antenna configurations, namely an omni-directional pattern, a doughnut-shaped sine pattern, a doughnut-shaped cosine pattern, a directional pattern with tilting angle toward the serving GBS. Via numerical results, it is demonstrated that the directional pattern with tilting angle provides the best signal-to-interference-plus-noise ratio (SINR) coverage probability. It is also shown that the optimal UAV altitude varies depending on the environment and antenna patterns.

Original languageEnglish (US)
Title of host publicationGlobalSIP 2019 - 7th IEEE Global Conference on Signal and Information Processing, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728127231
DOIs
StatePublished - Nov 2019
Event7th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2019 - Ottawa, Canada
Duration: Nov 11 2019Nov 14 2019

Publication series

NameGlobalSIP 2019 - 7th IEEE Global Conference on Signal and Information Processing, Proceedings

Conference

Conference7th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2019
Country/TerritoryCanada
CityOttawa
Period11/11/1911/14/19

Keywords

  • 3D antenna pattern
  • Cellular networks
  • SINR coverage
  • Unmanned aerial vehicles

ASJC Scopus subject areas

  • Information Systems
  • Information Systems and Management
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing

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