Cognitive Radio Spectrum Sensing Algorithms Based on Eigenvalue and Covariance Methods
Spectrum sensing method is the fundamental factor when the authors are working with cognitive radio systems. Main aim and fundamental problem of cognitive radio is to identify weather primary users in authorized or licensed spectrum is presented or not. Paper deals with a new scheme of sensing based on the eigenvalues concept. It contains signals of covariance matrix received by the secondary users. In this method they are suggested two algorithms of sensing, one algorithm established by the maximum to minimum eigenvalue ratio. Other algorithm focused on average to minimum eigenvalue ratio. These two are done by using Random Matrix Theories (RMT), and also these RMT are latest and also produce some accurate results.