On the use of Compressive Sampling for Wide-band Spectrum Sensing

In a scenario where a cognitive radio unit wishes to transmit, it needs to know over which frequency bands it can operate. It can obtain thisknowledge by estimating the power spectral density from a Nyquist-rate sampled signal. For wide-band signals sampling at the Nyquistrate is a major challenge and may be unfeasible. In this paper we accurately detect spectrum holes in sub-Nyquist frequencies without assuming wide sense stationarity in the compressed sampled signal. A novel extension to further reduce the sub-Nyquist samples is thenpresented by introducing a memory based compressed sensing thatrelies on the spectrum to be slowly varying.
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