Limits of detection for the consecutive mean excision algorithms

Johanna Vartiainen; Janne Lehtomäki; Harri Saarnisaari; Markku Juntti

5th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications

Research Article

Limits of detection for the consecutive mean excision algorithms

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@INPROCEEDINGS{10.4108/ICST.CROWNCOM2010.9177,
    author={Johanna Vartiainen and Janne Lehtom\aa{}ki and Harri Saarnisaari and Markku Juntti},
    title={Limits of detection for the consecutive mean excision algorithms},
    proceedings={5th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications},
    publisher={IEEE},
    proceedings_a={CROWNCOM},
    year={2010},
    month={9},
    keywords={Algorithm design and analysis Bandwidth Cognitive radio Niobium Prediction algorithms Signal processing algorithms Signal to noise ratio},
    doi={10.4108/ICST.CROWNCOM2010.9177}
}

Johanna Vartiainen
Janne Lehtomäki
Harri Saarnisaari
Markku Juntti
Year: 2010
Limits of detection for the consecutive mean excision algorithms
CROWNCOM
IEEE
DOI: 10.4108/ICST.CROWNCOM2010.9177

Johanna Vartiainen¹, Janne Lehtomäki¹, Harri Saarnisaari¹, Markku Juntti¹

1: University of Oulu, Centre for Wireless Communications (CWC), P.O. Box 4500, FIN-90014 University of Oulu, FINLAND

Abstract

Iterative backward and forward consecutive mean excision (CME/FCME) algorithms are efficient in suppressing and detecting narrowband signals. Being computationally relatively simple, they can be applied for spectrum sensing in cognitive radios. In this paper, theoretical limits of detection for the CME algorithms are derived. These limits predict whether a signal is detectable or not. More specifically, resulting signal-to-noise ratio (SNR) values at which the signals can be detected are presented. In addition, rules for choosing the optimal CME algorithm are conveyed. The validity of the presented limits of detection is confirmed with computer simulations.

Keywords: Algorithm design and analysis Bandwidth Cognitive radio Niobium Prediction algorithms Signal processing algorithms Signal to noise ratio

Published: 2010-09-16
Publisher: IEEE

: http://dx.doi.org/10.4108/ICST.CROWNCOM2010.9177