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Predictive Channel Selection for over-the-Air Video Transmission Using Software-Defined Radio Platforms

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Book cover Cognitive Radio Oriented Wireless Networks (CrownCom 2016)

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Abstract

This paper demonstrates a predictive channel selection method by implementing it in software-defined radio (SDR) platforms and measuring the performance using over-the-air video transmissions. The method uses both long term and short term history information in selecting the best channel for data transmission. Controlled interference is generated in the used channels and the proposed method is compared to reference methods. The achieved results show that the predictive method is a practical one, able to increase the throughput and reduce number of collisions and channel switches by using history information intelligently.

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Authors and Affiliations

  1. VTT Technical Research Centre of Finland Ltd., P.O. Box 1100, 90571, Oulu, Finland

    Marko Höyhtyä, Juha Korpi & Mikko Hiivala

Authors
  1. Marko Höyhtyä
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  2. Juha Korpi
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  3. Mikko Hiivala
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Corresponding author

Correspondence to Marko Höyhtyä .

Editor information

Editors and Affiliations

  1. CEA-LETI , Grenoble, France

    Dominique Noguet

  2. University of Surrey, Guildford, United Kingdom

    Klaus Moessner

  3. CentraleSupélec – Campus de Rennes, Institut d'Électronique et de Télécommunications de Rennes UMR CNRS 6164, Cesson-Sévigné, France

    Jacques Palicot

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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Höyhtyä, M., Korpi, J., Hiivala, M. (2016). Predictive Channel Selection for over-the-Air Video Transmission Using Software-Defined Radio Platforms. In: Noguet, D., Moessner, K., Palicot, J. (eds) Cognitive Radio Oriented Wireless Networks. CrownCom 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 172. Springer, Cham. https://doi.org/10.1007/978-3-319-40352-6_47

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  • DOI: https://doi.org/10.1007/978-3-319-40352-6_47

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40351-9

  • Online ISBN: 978-3-319-40352-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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