Cooperative Clustering Performance Enhancement Using Genetic Algorithm in CRNs

Salah, Ibrahim; Saad, Waleed; Shokair, Mona

doi:10.21608/mjeer.2020.69021

Cooperative Clustering Performance Enhancement Using Genetic Algorithm in CRNs

Document Type : Original Article

Authors

¹ CCE Department, Faculty of Eng., Nahda University, New BeniSuieif, Egypt

² ECE Department, Faculty of Electronic and Electrical Eng., Menoufia University, Egypt.

10.21608/mjeer.2020.69021

Abstract

Cognitive radio (CR) is a substantial technology for spectrum utilization in wireless communication networks. Cooperative Spectrum Sensing (CSS) has been ensured to enhance the performance of detection for cognitive users in the existence of spectral variation, moreover, it tends to be an essential section in Cognitive Radio Network (CRN) due to being fit for decreasing the probability of bumble in blurring channels. Generally, cooperative clustering in spectrum detection is consolidated to limit Jostle of revealing channel, update execution of sensing and decrease the computational use. In this research, the proposed co-operative clustering in CRN using optimization scheme (Genetic) constrains the total power wasted by CRN and time delay. Therefore, the simulation analysis demonstrates that the proposed scheme able to accomplish preferred energy gains less over the traditional cooperative scheme, lessen delay time and upgrade the total performance of CRN.

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