Computer Science ›› 2017, Vol. 44 ›› Issue (12): 86-89.doi: 10.11896/j.issn.1002-137X.2017.12.017

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Wavelet Neural Network Model for Cognitive Radio Spectrum Prediction

ZHU Zheng-guo, HE Ming-xing, LIU Rong-qi and LIU Ze-min   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Accurate spectrum prediction can effectively reduce the energy consumption of cognitive radio system and improve the throughput of cognitive radio system.In order to solve the problem of the prediction accuracy of spectrum prediction method,a wavelet neural network model was proposed to predict the state of channel occupancy.The discrete wavelet transform was used to generate the time-frequency distribution of the signal,and a time series was used to represent the state of a sub channel.The tradeoff between prediction accuracy,utilization and parameter initialization was analyzed to select a near optimal model.The experimental results show that,compared with the model based on BP neural network,the proposed model shows better performance in terms of prediction accuracy and energy consumption.

Key words: Cognitive radio,Spectrum prediction,Wavelet neural network,Model,Prediction accuracy,Wavelet basis function

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