Prediction and modeling the behavior of a secondary user in Cognitive Radio using Artificial Intelligence Techniques

Deisy Zambrano(1), Octavio José Salcedo(2*), Miguel Jose Espitia(3)

(1) Universidad Disitrital "Francisco José de Caldas", Colombia
(2) Universidad Disitrital "Francisco José de Caldas" Universidad Nacional de Colombia, Sede Bogotá, Colombia
(3) Universidad Disitrital "Francisco José de Caldas", Colombia
(*) Corresponding author

DOI's assignment:
The DOI number for this article will be assigned as soon as the final version of the IRECAP Vol 7, No 4 (2017) issue will be available


Currently one of the biggest challenges in wireless networks Focuses on the optimal use of use of the radio spectrum, since much of authors agree That the licensed frequency band is not in use MOST of the time. There has - been a lot of research about the use of converging on "Cognitive Radio" as essential for the use of available spectrum licensed possible, use well above parameter values currently are detected. This article describe the process and the main results of a comparative study, Which is based on the use of two tools of computational intelligence, applied on a task of predicting to chaotic time series is presented. The methods of forecasting time series are ANFIS algorithm (Fuzzy Inference System Based on Adaptive Networks) and neural networks. Then they presented and the results of this study are discussed, under the criterion of the sum of squared error and the processing time required.
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Index Anfis; Neural Networks; Secondary Users (SUs); Artificial Intelligence; Cognitive Radio


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