Machine Learning Based Spectrum Sensing for Secure Data Transmission Using Cuckoo Search Optimization

This article is about machine Learning (ML) depending spectrum sensing in using cuckoo search optimization method. In Present days as the number of mobile users is increasing, scarcity of spectrum is arising due to allocation of the available spectrum to growing number of the users in cognitive radio. So there is a need to efficiently utilize the limited spectrum that is available for use. Spectrum sensing is one of the prominent method for effective utilization of the spectrum. Among the existing methods of spectrum sensing using Energy detection, Machine learning based sensing is more prominent. For efficiently optimizing the spectrum sensing cuckoo search based optimization has been used in this paper. For analyzing the channels under noise conditions Gaussian function has been considered. Average information per message based classifier is a good technique of detection for spectrum sensing. Classification has been done with the help of support vector machine and K-Nearest Neighbor algorithms. From the obtained results it has been shown that average information based SVM, KNN techniques outperforms the conventional energy detection based techniques and cuckoo search based optimization has yielded better sensing accuracy with minimum loss.