Analysis of Classical and Machine Learning Techniques in Cognitive Radio Network

In this work, a detailed review of literature is conducted on the state of the research of classical and machine learning methods in cognitive radio networks. While the current focus is on machine learning by the research community, it is always important to understand how the classical methods have the advantage over machine learning methods and vice versa. Hence the analysis of both the approaches are undertaken in this study. Classical methods like energy detection, matched filter methods, cyclostationary methods, cluster methods etc are discussed in detail along with the advantages and limitations. In the space of machine learning techniques, most of the methods applied to cognitive radio system are discussed. Machine learning, deep learning, evolutionary methods, fuzzy methods are discussed in detail.