Cooperative Clustering Performance Enhancement Using Genetic Algorithm in CRNs | ||||
Menoufia Journal of Electronic Engineering Research | ||||
Article 8, Volume 29, Issue 1, January 2020, Page 61-65 PDF (1.33 MB) | ||||
Document Type: Original Article | ||||
DOI: 10.21608/mjeer.2020.69021 | ||||
View on SCiNiTO | ||||
Authors | ||||
Ibrahim Salah1; Waleed Saad2; Mona Shokair2 | ||||
1CCE Department, Faculty of Eng., Nahda University, New BeniSuieif, Egypt | ||||
2ECE Department, Faculty of Electronic and Electrical Eng., Menoufia University, Egypt. | ||||
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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