Journal of Computing
Compressive Sampling (CS), or compressive sensing, has the ability for reconstructing a sparse signal with small number of measurements. There are some applications like spectrum sensing in cognitive radio which not necessarily need a perfect reconstruction. Consequently in this application, toward the decrement of high signal acquisition costs in wideband system, CS methods have been used for spectrum sensing. New developments in CS have presented a new way toward the reconstruction of the original signal by using minimum number of observations. In this paper, the authors present a novel method in which CS is employed for compressing spectrum sensing in CRNs.