Teaching and Learning based 5G cognitive radio application for future application

Wireless Communication Network (WSN) applications are growing drastically daily, and their extensive nature attracts researchers and development authorities. The critical issues in wireless communication have been answering by advancements in cognitive radio (CR) techniques. The dynamic spectrum analysis allows cognitive radio at the receiver section to increase the spectrum efficiency and power consumption. The next-generation wireless networks, namely 5G technologies, accept advanced cognitive radios in their functionality. In this work, teaching and Learning based optimization are proposed for future communications purpose. The main aim of the study is to increase the spectral efficiency as well as energy consumption. The earlier methods can only targeting transmission rate and network complexity. The proposed adaptive teaching and learning based WCN can improve 78% energy efficiency and 47% data rate.