An improved blind spectrum sensing technique for cognitive radio systems

Cognitive radio has been proposed as a key solution for the problem of inefficient usage of spectrum bands. Spectrum sensing is one of the most important issues in each cognitive radio system. Classically-used spectrum sensing techniques require that the cognitive transmitter is not in operation while detecting the presence/absence of the primary signal during the sensing period. In this paper, we propose to use the Kurtosis metric, for blind source separation algorithms with the aim of improving the accuracy of conventional spectrum sensing techniques based on blind source separation. We also introduce a new spectrum sensing framework that combines blind source separation with conventional spectrum sensing techniques. In this way, spectrum sensing can continue to work even when the cognitive transmitter is in operation. Simulation results provided in terms of receiver operating characteristic (ROC) curves indicate that the proposed method improves the sensing performance achieved with conventional spectrum sensing techniques.