Wireless link prediction and triggering using modified Ornstein-Uhlenbeck jump diffusion process

Eric Chin, David Chieng, Victor Teh, Marek Natkaniec, Krzysztof Loziak, Janusz Gozdecki

Research output: Journal PublicationArticlepeer-review

9 Citations (Scopus)

Abstract

Through time domain observation, typical wireless signal strength values seems to exhibit some forms of mean-reverting and discontinuous "jumps" behaviour.Motivated by this fact, we propose a wireless link prediction and triggering (LPT) technique using a modified mean-reverting Ornstein-Uhlenbeck (OU) jump diffusion process.The proposed technique which we refer as OU-LPT is an integral component of wireless mesh network monitoring system developed by ICT FP7 CARrier grade wireless MEsh Network project.In particular, we demonstrate how this technique can be applied in the context of wireless mesh networks to support link switching or handover in the event of predicted link degradation or failure.The proposed technique has also been implemented and evaluated in a real-time experimental testbed.The results show that OU-LPT technique can significantly enhance the reliability of wireless links by reducing the rate of false triggers compared to a conventional linear prediction technique and therefore offers a new direction on how wireless link prediction, triggering and switching process can be conducted in the future.

Original languageEnglish
Pages (from-to)379-396
Number of pages18
JournalWireless Networks
Volume20
Issue number3
DOIs
Publication statusPublished - Apr 2014
Externally publishedYes

Keywords

  • Data analysis
  • Link prediction
  • Link triggering
  • Monitoring system
  • Wireless mesh networks

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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