A Novel Scheme for Spectrum Prediction in Cognitive Radio Networks
Mehdi Askari, Rezvan Dastanian · Journal of Electrical & Electronic Systems Research · 2021
An efficient spectrum prediction model is presented to improve the spectrum utilization in cognitive radio network.In this model, a novel improved version of Teaching-Learning-Based-Optimization algorithm, also referred to iTLBO algorithm, is proposed to train a feedforward artificial neural network (ANN).The performance of the proposed iTLBO-ANN model is compared with some hybrid prediction models, including the genetic algorithm with ANN (GA-ANN), the firefly algorithm with ANN (FF-ANN), and the conventional TLBO algorithm with ANN (TLBO-ANN).Performance evaluation via a real-word spectrum dataset (GSM-900) confirms that iTLBO-ANN outperforms other spectrum prediction schemes in terms of prediction error and prediction efficiency.