Authors : Danilo Lopez Sarmiento, Edwin Rivas Trujillo and Luis Fernando Pedraza
Abstract: Currently one of the major challenges in wireless networks is the optimal use of the radio spectrum as most researcher agree that the licensed frequency band is not in use most of the time. There has been a large amount of research in this area that converges in the use of Cognitive Radio (CR) as an essential parameter so that the use of the available licensed spectrum is possible (by secondary users) well above the usage values that are currently detected; thus allowing the opportunistic use of the channel in the absence of Primary Users (PU). This study presents the results found when estimating or predicting the future use of a spectral transmission band (from the perspective of the PU) for a chaotic type channel arrival behavior. The time series prediction method (which the PU represents) used is ANFIS (Adaptive Neuro Fuzzy Inference System). The results obtained were compared to those delivered by the RNA (Artificial Neural Network) algorithm. The results show better performance in the characterization (modeling and prediction) with the ANFIS methodology.
Danilo Lopez Sarmiento, Edwin Rivas Trujillo and Luis Fernando Pedraza, 2017. Use of Artificial Intelligence Based Models to Estimate the Use of a Spectral Band in Cognitive Radio. Journal of Engineering and Applied Sciences, 12: 4259-4266.