Analysis of coloured noise in received signal strength using the Allan Variance

Chunbo Luo, Pablo Casaseca, S. McClean, G. Parr, C. Grecos

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

5 Citations (Scopus)

Abstract

The received signal strength (RSS) of wireless signals has been widely used in communications, localization and tracking. Theoretical modelling and practical applications often make a white noise assumption when dealing with RSS measurements. However, as we will show in this paper, the noise present in RSS measurements has time-dependency properties. In order to study these properties and provide noise characterisation, we propose to use the Allan Variance (AVAR) and show its better performance in comparison with direct analysis in the frequency domain using a periodogram. We further study the contribution of each component by testing real RSS data. Our results confirm that the noise associated with RSS signals is actually coloured and demonstrate the appropriateness of AVAR for the identification and characterisation of these components.
Original languageEnglish
Title of host publicationProceedings of the 22nd European Signal Processing Conference (EUSIPCO), 2014
PublisherIEEE
Pages994-998
Number of pages5
ISBN (Print)9781479946037
Publication statusPublished - 2014

Keywords

  • frequency-domain analysis
  • radio networks
  • signal processing
  • white noise
  • AVAR
  • Allan variance
  • RSS measurements
  • coloured noise analysis
  • direct frequency domain analysis
  • periodogram
  • real RSS data testing
  • received signal strength
  • time-dependency properties
  • white noise assumption
  • wireless signals
  • Colored noise
  • Educational institutions
  • Estimation
  • Noise measurement
  • Wireless communication
  • 802.11
  • RSS
  • coloured noise
  • noise characterisation

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  • Cite this

    Luo, C., Casaseca, P., McClean, S., Parr, G., & Grecos, C. (2014). Analysis of coloured noise in received signal strength using the Allan Variance. In Proceedings of the 22nd European Signal Processing Conference (EUSIPCO), 2014 (pp. 994-998). IEEE.