This paper presents a new method for automatic radio spectrum segmentation. Spectrum segmentation serves as a first step to identify the subbands that are in use at a certain time, when a wide portion of the spectrum is observed. The proposed method, based on the evaluation of the histogram of the power spectral density of the received signal, is designed for obtaining a low processing complexity and to be implemented in a measurement instrument or a cognitive radio receiver. The proposed method is validated on emulated signals, and the results show good accuracy of the subband boundary estimation and a processing complexity much lower than the other segmentation methods.

A Histogram-Based Segmentation Method for Wideband Spectrum Sensing in Cognitive Radios

De Vito L;Rapuano S
2013-01-01

Abstract

This paper presents a new method for automatic radio spectrum segmentation. Spectrum segmentation serves as a first step to identify the subbands that are in use at a certain time, when a wide portion of the spectrum is observed. The proposed method, based on the evaluation of the histogram of the power spectral density of the received signal, is designed for obtaining a low processing complexity and to be implemented in a measurement instrument or a cognitive radio receiver. The proposed method is validated on emulated signals, and the results show good accuracy of the subband boundary estimation and a processing complexity much lower than the other segmentation methods.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12070/415
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