Research Article
A Wavelet Approach to Wideband Spectrum Sensing for Cognitive Radios
@INPROCEEDINGS{10.1109/CROWNCOM.2006.363459, author={Zhi Tian and Georgios B. Giannakis}, title={A Wavelet Approach to Wideband Spectrum Sensing for Cognitive Radios}, proceedings={1st International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications}, publisher={IEEE}, proceedings_a={CROWNCOM}, year={2007}, month={5}, keywords={Cognitive radio Frequency estimation Information analysis Radio spectrum management Radiofrequency identification Signal processing Wavelet analysis Wavelet transforms Wideband Wireless sensor networks}, doi={10.1109/CROWNCOM.2006.363459} }- Zhi Tian
Georgios B. Giannakis
Year: 2007
A Wavelet Approach to Wideband Spectrum Sensing for Cognitive Radios
CROWNCOM
IEEE
DOI: 10.1109/CROWNCOM.2006.363459
Abstract
In cognitive radio networks, the first cognitive task preceding any form of dynamic spectrum management is the sensing and identification of spectrum holes in wireless environments. This paper develops a wavelet approach to efficient spectrum sensing of wideband channels. The signal spectrum over a wide frequency band is decomposed into elementary building blocks of subbands that are well characterized by local irregularities in frequency. As a powerful mathematical tool for analyzing singularities and edges, the wavelet transform is employed to detect and estimate the local spectral irregular structure, which carries important information on the frequency locations and power spectral densities of the subbands. Along this line, a couple of wideband spectrum sensing techniques are developed based on the local maxima of the wavelet transform modulus and the multi-scale wavelet products. The proposed sensing techniques provide an effective radio sensing architecture to identify and locate spectrum holes in the signal spectrum