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State Description of Wireless Channels Using Change-Point Statistical Tests

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Wired/Wireless Internet Communications (WWIC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 3970))

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Abstract

We consider the state of the wireless channel in terms of the covariance stationary signal-to-noise ratio (SNR) process and parameterize it using the probability distribution function of SNR and lag-1 autocorrelation coefficient of associated autocorrelation function (ACF). In order to discriminate the state of the wireless channel we apply methods of statistical process control. Particularly, we use exponential weighted moving average (EWMA) change-point statistical test to detect shifts in the mean of the SNR process. The proposed approach is verified using SNR measurements of IEEE 802.11b wireless channel.

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References

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Author information

Authors and Affiliations

  1. Institute of Communication Engineering, Tampere University of Technology, P.O. Box 553, Tampere, Finland

    D. Moltchanov

Authors
  1. D. Moltchanov
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Editor information

Editors and Affiliations

  1. Institute of Computer Science and Applied Mathematics, University of Bern, Switzerland

    Torsten Braun

  2. Wilhelm-Schickard-Institut für Informatik, University of Tübingen, Germany

    Georg Carle

  3. Department of Computer Science, Purdue University, 250 N. University Street, IN 47907-2066, West Lafayette, USA

    Sonia Fahmy

  4. Department of Communications Engineering, Tampere University of Technology, Korkeakoulunkatu 10, 33720, Tampere, Finland

    Yevgeni Koucheryavy

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© 2006 Springer-Verlag Berlin Heidelberg

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Moltchanov, D. (2006). State Description of Wireless Channels Using Change-Point Statistical Tests. In: Braun, T., Carle, G., Fahmy, S., Koucheryavy, Y. (eds) Wired/Wireless Internet Communications. WWIC 2006. Lecture Notes in Computer Science, vol 3970. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11750390_24

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  • DOI: https://doi.org/10.1007/11750390_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34023-2

  • Online ISBN: 978-3-540-34024-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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