Non-uniform spectrum sensing for Cognitive Radio using sub-nyquist sampling

Spectrum sensing is the very task upon which the entire operation of Cognitive Radio rests. In this paper, we propose a spectrum sensing technique based on the estimates of the spectrum of a multiband signal obtained from its compressed samples. We show that our proposed spectrum sensing method provides accurate results using less data samples. We also show the effect of false detection on the average sampling rate of a non-uniform sub-Nyquist sampler.