Modeling interference for wireless sensor network simulators

  • Umber Noreen
  • , Ahcène Bounceur
  • , Laurent Clavier

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Any radio signal gets exposed to some attenuation over dis- tance, and is received at the receiver as its distorted version and is superposed with other wireless signals transmitted in the neighborhood. In wireless communications, the use- ful signal is usually decoded by assuming the sum of all other wireless signal transmissions as noise. Interference be- tween coexisting transmissions can cause severe performance degradation in wireless sensor networks (WSNs). In this paper we have reviewed interference models for wireless sensor networks. Since a decade or more, densifica- tion of networks increases the impact of interference. New models have been proposed but are not yet included into network simulators. This could be source of a big difference between simulations and real deployments.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Big Data and Advanced Wireless Technologies, BDAW 2016
EditorsDjallel Eddine Boubiche, Hani Hamdan, Ahcene Bounceur
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450347792
DOIs
StatePublished - 10 Nov 2016
Externally publishedYes
Event2016 International Conference on Big Data and Advanced Wireless Technologies, BDAW 2016 - Blagoevgrad, Bulgaria
Duration: 10 Nov 201611 Nov 2016

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2016 International Conference on Big Data and Advanced Wireless Technologies, BDAW 2016
Country/TerritoryBulgaria
CityBlagoevgrad
Period10/11/1611/11/16

Bibliographical note

Publisher Copyright:
© 2016 ACM.

Keywords

  • CupCarbon
  • Im-pulsive Interference
  • Smart Cities
  • Wireless Communications
  • Wireless Sensor Networks

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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