Reliable wideband multichannel spectrum sensing using randomized sampling schemes

A wideband multichannel spectrum sensing approach that utilizes nonuniform sampling and digital alias-free signal processing (DASP) to reliably sense the spectrum using sampling rates well below the ones used in classical DSP is proposed. The approach deploys a periodogram-type spectral analysis tool to estimate the spectrum of the incoming signal from a finite number of its noisy nonuniformly distributed samples. The statistical characteristics of the adopted estimator are analyzed and its accuracy is assessed. It is demonstrated here that owing to the use of nonuniform sampling, the sensing task can be carried out with the use of arbitrary low sampling rates. Most importantly, general guidelines are provided on the required signal analysis time window for a chosen sampling rate to guarantee sensing reliability within a particular scenario. The extra requirement on such recommendations imposed by the presence of noise is given. The analytical results are illustrated by numerical examples. This paper establishes a new framework for multiband spectrum sensing where substantial saving on the used sampling rates can be achieved