A second-order statistical method for spectrum sensing in correlated shadowing and fading environments

Spectrum sensing is one of the most important tasks of cognitive radios (CRs) in future wireless systems and of user equipments (UEs) in next generation wireless networks (NGWNs). Therefore, deciding whether a specific portion of radio frequency (RF) spectrum is occupied or not is of paramount importance for all sorts of future wireless communications systems. In this study, a spectrum sensing method that employs a second-order statistical approach is proposed for detecting fast fading signals in spatially correlated shadowing environments. Analysis and performance results are presented along with the discussion related to the performance comparison of energy detection method.