Comparative Study of Bayesian and Energy Detection Including MRC Under Fading Environment in Collaborative Cognitive Radio Network

Abstract

Abstract-The most important component of Cognitive RadioNetwork (CRN) is to sense the underutilised spectrum efficiently in fading environment for incorporating the increasing demand of wireless applications. The result of spectrum sensing can be affected by incorrect detection of the existence of Primary User (PU). In this paper, we have considered Collaborative spectrum sensing to maximise the spectrum utilisation of Cognitive Radio (CR) user. We proposed a new architecture and algorithm that shows the step by step spectrum sensing procedure using Energy detection and Bayesian detection in collaborative environment for an optimal number of users. This algorithm also includes Maximal Ratio Combining (MRC) diversity techniques in fusion centre to make a final decision under fading condition. The simulation result shows the significant optimisation of detection performance with less misdetection for large number of users. It is also observed that MRC produces better results in collaborative manner under Nakagami-m, Rayleigh and Normal fading. Finally in this paper, we have analysed the relative performance of different wireless channels for various SNR levels and from that analysis it concludes that ED technique works better in high SNR and BD technique works for low SNR.