A Wideband Spectrum Sensing Method for Cognitive Radio using Sub-Nyquist Sampling

Spectrum sensing is a fundamental component in cognitive radio. A major challenge in this area is the requirement of a high sampling rate in the sensing of a wideband signal. In this paper a wideband spectrum sensing model is presented that utilizes a sub-Nyquist sampling scheme to bring substantial...

Full description

Saved in:
Bibliographic Details
Published inarXiv.org
Main Authors Rashidi, Moslem, Haghighi, Kasra, Owrang, Arash, Viberg, Mats
Format Paper
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 11.10.2010
Subjects
Broadband
Cognitive radio
Correlation analysis
Detection
Occupancy
Sampling
Online AccessGet full text

Cover

More Information
Summary:Spectrum sensing is a fundamental component in cognitive radio. A major challenge in this area is the requirement of a high sampling rate in the sensing of a wideband signal. In this paper a wideband spectrum sensing model is presented that utilizes a sub-Nyquist sampling scheme to bring substantial savings in terms of the sampling rate. The correlation matrix of a finite number of noisy samples is computed and used by a subspace estimator to detect the occupied and vacant channels of the spectrum. In contrast with common methods, the proposedmethod does not need the knowledge of signal properties that mitigates the uncertainty problem. We evaluate the performance of this method by computing the probability of detecting signal occupancy in terms of the number of samples and the SNR of randomly generated signals. The results show a reliable detection even in low SNR and small number of samples.
ISSN:2331-8422