C. Ambhika1,*, C. Murukesh2
Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 827-838, 2023, DOI:10.32604/iasc.2023.026832
Abstract With the demand for wireless technology, Cognitive Radio (CR) technology is identified as a promising solution for effective spectrum utilization. Connectivity and robustness are the two main difficulties in cognitive radio networks due to their dynamic nature. These problems are solved by using clustering techniques which group the cognitive users into logical groups. The performance of clustering in cognitive network purely depends on cluster head selection and parameters considered for clustering. In this work, an adaptive neuro-fuzzy inference system (ANFIS) based clustering is proposed for the cognitive network. The performance of ANFIS improved using hybrid particle swarm and whale optimization… More >
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