Clustering Genetic Algorithm for Cognitive Radio Network
Journal Title: International Journal of engineering Research and Applications - Year 2018, Vol 8, Issue 6
Abstract
The well-known Cognitive Radio Network (CRN) is a promising technology to fulfill the requirements of the need of high data rates. The major mechanism to perform CRN is the ability of detecting the existence of the Primary User (PU). Availability of PU can be detected by cooperative spectrum sensing to avoid the hidden terminal and multipath fading. PU information is transmitted to the nodes or so called Secondary Users (SU). SU will forward the information through different channels to the Fusion Center to make the final decision via Soft Detection Fusion (SDF). From that, Clustering Genetic Algorithm (CGA) is proposed to optimize the probability of detection. In this paper, it is shown that the performance of CGA outperforms the Standard Genetic Algorithm. Moreover, CGA is very applicable for CRN since it is showing good performance for such complex problem where it shows faster convergence speed rather than SGA.
Authors and Affiliations
Mohammed A. Alrefaei
Keywords
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- EP ID EP394395
- DOI 10.9790/9622-0806035457.
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