K-mean clustering based cooperative spectrum sensing in generalized к-μ fading channels

Machine learning based approaches for spectrum sensing and spectrum occupancy prediction in cognitive radio applications appear to have attracted sufficient interest in the current literature. In this paper, K-mean clustering based unsupervised learning method has been adopted for the performance enhancement of cooperative spectrum sensing in generalized κ-μ fading channels. Extensive simulation has been carried out for different system parameter trade-off in characterizing the receiver operating characteristics.