Prediction of Spectrum based on Improved RBF Neural Network in Cognitive Radio

Shibing Zhang, Jianrong Wu, Jinming Hu, Zhihua Bao

Abstract

Spectrum prediction is a key technology of cognitive radio, which can help unlicensed users to determine whether the licensed user’s spectrum is idle. Based on radial-basis function (RBF) neural network, this paper proposed a spectrum prediction algorithm with K-means clustering algorithm (K-RBF). This algorithm could predict the spectrum holes according to the historical information of the licensed user’s spectrum. It not only increases the veracity of spectrum sensing, but also improves the efficiency of spectrum sensing. Simulation results showed that this prediction algorithm can predict the spectrum accessing of the licensed user accurately and the prediction error is only one-third of that of the RBF neural network.

References

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Paper Citation


in Harvard Style

Zhang S., Bao Z., Wu J. and Hu J. (2013). Prediction of Spectrum based on Improved RBF Neural Network in Cognitive Radio . In Proceedings of the 10th International Conference on Signal Processing and Multimedia Applications and 10th International Conference on Wireless Information Networks and Systems - Volume 1: WINSYS, (ICETE 2013) ISBN 978-989-8565-74-7, pages 243-247. DOI: 10.5220/0004537002430247


in Bibtex Style

@conference{winsys13,
author={Shibing Zhang and Zhihua Bao and Jianrong Wu and Jinming Hu},
title={Prediction of Spectrum based on Improved RBF Neural Network in Cognitive Radio},
booktitle={Proceedings of the 10th International Conference on Signal Processing and Multimedia Applications and 10th International Conference on Wireless Information Networks and Systems - Volume 1: WINSYS, (ICETE 2013)},
year={2013},
pages={243-247},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004537002430247},
isbn={978-989-8565-74-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Signal Processing and Multimedia Applications and 10th International Conference on Wireless Information Networks and Systems - Volume 1: WINSYS, (ICETE 2013)
TI - Prediction of Spectrum based on Improved RBF Neural Network in Cognitive Radio
SN - 978-989-8565-74-7
AU - Zhang S.
AU - Bao Z.
AU - Wu J.
AU - Hu J.
PY - 2013
SP - 243
EP - 247
DO - 10.5220/0004537002430247