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

Marko Höyhtyä; Juha Korpi; Mikko Hiivala

Cognitive Radio Oriented Wireless Networks. 11th International Conference, CROWNCOM 2016, Grenoble, France, May 30 - June 1, 2016, Proceedings

Research Article

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

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@INPROCEEDINGS{10.1007/978-3-319-40352-6_47,
    author={Marko H\o{}yhty\aa{} and Juha Korpi and Mikko Hiivala},
    title={Predictive Channel Selection for over-the-Air Video Transmission Using Software-Defined Radio Platforms},
    proceedings={Cognitive Radio Oriented Wireless Networks. 11th International Conference, CROWNCOM 2016, Grenoble, France, May 30 - June 1, 2016, Proceedings},
    proceedings_a={CROWNCOM},
    year={2016},
    month={6},
    keywords={Cognitive radio Spectrum databases Dynamic spectrum access},
    doi={10.1007/978-3-319-40352-6_47}
}

Marko Höyhtyä
Juha Korpi
Mikko Hiivala
Year: 2016
Predictive Channel Selection for over-the-Air Video Transmission Using Software-Defined Radio Platforms
CROWNCOM
Springer
DOI: 10.1007/978-3-319-40352-6_47

Marko Höyhtyä¹^,*, Juha Korpi¹^,*, Mikko Hiivala¹^,*

1: VTT Technical Research Centre of Finland Ltd.

*Contact email: marko.hoyhtya@vtt.fi, juha.korpi@vtt.fi, mikko.hiivala@vtt.fi

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.

Keywords: Cognitive radio Spectrum databases Dynamic spectrum access

Published: 2016-06-06
Appears in: SpringerLink

: http://dx.doi.org/10.1007/978-3-319-40352-6_47