Dynamic Bayesian Approach Applied in Link Adaptation Problem for Fifth Generation Network

With technological development, wireless communication has been one of the fastest growing fields of Computing and Engineering in recent years. This fact requires that new approaches be developed to ensure better performance and reliability in wireless communication. In this paper a new approach has been proposed as a solution to the problem of adaptive modulation and coding (AMC), through the development of an extension of the method naive Bayesian classifier, known as dynamic naive Bayesian classifier, to maximize spectral efficiency. The proposed approach exhibits a better performance than k-nearest neighbours algorithm and the traditional Look-Up table solution, with average classification error 2.85%, which represents approximately 10% with respect to the most similar method.