Skip to main navigation Skip to search Skip to main content

Interference Analysis and Mitigation for Aerial IoT Considering 3D Antenna Patterns

  • Sung Joon Maeng
  • , Mrugen A. Deshmukh
  • , Ismail Guvenc
  • , Arupjyoti Bhuyan
  • , Huaiyu Dai

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

Due to dense deployments of Internet of things (IoT) networks, interference management becomes a critical challenge. With the proliferation of aerial IoT devices, such as unmanned aerial vehicles (UAVs), interference characteristics in 3D environments will be different than those in the existing terrestrial IoT networks. In this paper, we consider 3D topology IoT networks with a mixture of aerial and terrestrial links, with low-cost cross-dipole antennas at ground nodes and both omni-directional and cross-dipole antennas at aerial nodes. Considering a massive-access communication scenario, we first derive the statistics of the channel gain at IoT receivers in closed form while taking into account the radiation patterns of both ground and aerial nodes. These are then used to calculate the ergodic achievable rate as a function of the height of the aerial receiver and the cumulative interference. We propose a low-complexity interference mitigation scheme that utilizes 3D antenna radiation pattern with different dipole antenna settings. Our results show that using the proposed scheme, the ergodic achievable rate improves as the height of the aerial receivers increases. In addition, we also show that the ratio between the ground and aerial receivers that maximizes the peak rate increases with the height of the aerial IoT receiver.

Original languageEnglish
Article number9301370
Pages (from-to)490-503
Number of pages14
JournalIEEE Transactions on Vehicular Technology
Volume70
Issue number1
DOIs
StatePublished - Jan 2021

Keywords

  • 3D topology
  • 5G
  • IoT
  • UAV
  • antenna radiation pattern
  • uncoordinated network

Fingerprint

Dive into the research topics of 'Interference Analysis and Mitigation for Aerial IoT Considering 3D Antenna Patterns'. Together they form a unique fingerprint.

Cite this