A NOVEL POLYNOMIAL FILTERING METHOD FOR DATA SMOOTHING IN COGNITIVE RADIO APPLICATIONS

Giovanni Betta, Domenico Capriglione, Gianni Cerro, Luigi Ferrigno, Gianfranco Miele

Abstract

The smoothing process is a fundamental task in many application fields. This paper proposes a novel method to smooth raw data, based on the concept of polynomial fitting. It is thought to be effective in Cognitive Radio applications, especially focused on spectrum sensing tasks. The method is intended to be used instead of today’s traditional smoothing filters, because of some advantages in terms of shaping retainment, data shifting problem avoidance, acceptable computational intensity, appreciable noise reduction property. The goodness of the proposal has been proved considering the <i>H</i>₁ norm operator as performance index.

Keywords

smoothing filtering, cognitive radio, polynomial fitting, noise reduction, spectrum management

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IMEKO-WC-2015-TC4-106.pdf

DOI

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IMEKO TC

TC4 - Measurement of Electrical Quantities

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