Abstract : In this paper, a solution for a cluster formation in cognitive radio networks is presented. The solution features a network-wide energy consumption model for these networks. The particle swarm optimisation (PSO) and least squares support vector machines (LS-SVMs) have been transformed into our clustering problem. The obtained results show that the given hybrid AI system provides a good estimate of a cluster formation. Through extensive simulations, we observed that the PSO-LS-SVM method can be effectively used under various spectrum characteristics. Moreover, the formed clusters are reliable and stable in a dynamic frequency environment.
https://hal.inria.fr/hal-01385347 Contributor : Hal IfipConnect in order to contact the contributor Submitted on : Friday, October 21, 2016 - 11:37:27 AM Last modification on : Tuesday, December 7, 2021 - 3:33:15 PM
Jerzy Martyna. PSO-Least Squares SVM for Clustering in Cognitive Radio Sensor Networks. 11th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI 2015), Sep 2015, Bayonne, France. pp.91-102, ⟨10.1007/978-3-319-23868-5_7⟩. ⟨hal-01385347⟩