A Novel Weighted Cluster Based Co-operative Spectrum Sensing Scheme for Cognitive Radio Network

Abstract

Background: Cognitive radio can be described as a radio system where it familiarizes to the situations of the environs by some procedure like analyzing, observing and learning. Cognitive radio can basically recycle the unused white space in the license spectrum through sensing the network thus the method can achieve the maximum implementation of the radio bandwidth. Objective: The motivation of this research is to improve the performance of spectrum sensing of a group of users in every cluster where various channel environment will be presented in comparison with the conventional weighted sensing. Methods: With the intention of lessening the fading and shadowing, co-operative detection is favored over independent detection. Clustered based cooperation has been employed to expand the sensing enactment moderately. Sensing of co-operative spectrum which is weighted has been used to boost the cluster cooperation scheme. To crack the critical problem this research proposed a weighted cluster based co-operative sensing in which the weight calculation is performed at FC reducing all available redundancies. Results: From the simulation it is found that our proposed algorithm has better probability of detection (i.e, at -6 dB of SNR, clustered, Weighted Clustered and Novel Weighted Clustered probability of detections are 67%,84% and 95% respectively). Even if Novel Weighted Clustered has the lower False Alarm probability. Conclusion: Proposed novel weighted co-operative spectrum sensing algorithm for cognitive radio network spectrum sensing scheme can attain better performance under different fading environments.