This article proposes a new cooperative wideband spectrum-sensing algorithm based on cooperativesub-Nyquist narrow band spectrum sensing in cognitive radio devices (CRD).Within this scenario, to guarantee optimal detection, the spectrum-sensing function must work with a great amount of samples of the signal obtained at rates equal or higher than the Nyquist rate, which generates high detection times, high power consumption and the need for high processing capabilities in the CRD.Additionally, we must a priori knowledge of the signal characteristics.However, in practice, the characteristics of the multiband signal are unknown and high processing capabilities would be required according to the sampling rate.Due to this, this article proposes a novel spectrumsensing algorithm for these types of systems seeking to minimize the number of samples to process and which operates without a priori knowledge of the characteristics of the multiband signal.The simulation results permit evidencing that the algorithm proposed improves the sensing performance in function of the detection probability and of the receptor's operational characteristics with respect to other cooperative wideband spectrum sensing algorithms based on sub-Nyquist sampling.