2015Unpublished venueRequires access

Wideband spectrum sensing technique based on Goodness-of-Fit testing

Bart Scheers, Djamel Teguig, Vincent Le Nir

Open publisher page 20 citations

Abstract

Recently, Goodness-of-Fit (GoF) based spectrum sensing has been proposed as a method for blind narrowband spectrum sensing. GoF based spectrum sensing has the nice feature that, compared to Energy Detection, it needs fewer samples to achieve the same sensing performance. In this paper, we present how GoF based spectrum sensing can be integrated in a conventional wideband spectrum sensing scheme, resulting in an accurate technique with a very short sensing time, which makes this method attractive for cognitive radio applications.

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What this paper is about

Recently, Goodness-of-Fit (GoF) based spectrum sensing has been proposed as a method for blind narrowband spectrum sensing. GoF based spectrum sensing has the nice feature that, compared to Energy Detection, it needs fewer samples to achieve the same sensing performance. In this paper, we present how GoF based spectrum sensing can be integrated in a conventional wideband spectrum sensing scheme, resulting in an accurate technique with a very short sensing time, which makes this method attractive for cognitive radio applications.

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OpenAlex reports 20 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Recently, Goodness-of-Fit (GoF) based spectrum sensing has been proposed as a method for blind narrowband spectrum sensing. GoF based spectrum sensing has the nice feature that, compared to Energy Detection, it needs fewer samples to achieve the same sensing performance. In this paper, we present how GoF based spectrum sensing can be integrated in a conventional wideband spectrum sensing scheme, resulting in an accurate technique with a very short sensing time, which makes this method attractive for cognitive radio applications.

Key concepts: Wideband, Narrowband, Cognitive radio, Goodness of fit, Spectrum (functional analysis), Computer science, Electronic engineering, Energy (signal processing)

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