Publication

Abstract : Cognitive radio is a solution for the spectral crowding problem by introducing opportunistic usage of frequency bands that are not occupied by licensed primary users. Spectrum sensing is the most important task of cognitive radio which identifies the existence of the primary users in the frequency band under consideration. Energy detector (ED) is one of the simplest and basic methods for spectrum sensing but it suffers from noise uncertainty problem. Covariance Absolute Value (CAV) is another spectrum sensing method which is based on the statistical covariance of the received signal but it works well only if the signal samples are highly correlated. Hence another novel selection based hybrid spectrum sensing method is proposed which combines the advantages of both the methods. Simulation results prove that the novel selection based spectrum sensing method outperforms both the energy detection as well as CAV method and identifies the spectrum hole irrespective of the nature of the signal under consideration.