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Authors: Shibing Zhang ; Jinming Hu ; Zhihua Bao and Jianrong Wu

Affiliation: Nantong University, China

ISBN: 978-989-8565-74-7

Keyword(s): Cognitive Radio, Spectrum Prediction, K-means Clustering, RBF Neural Network.

Related Ontology Subjects/Areas/Topics: Cognitive Radio and Software Defined Radio ; Mobile Software and Services ; Radio Resource Management ; Telecommunications ; Wireless and Mobile Technologies ; Wireless Information Networks and Systems

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.

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Paper citation in several formats:
Zhang, S.; Hu, J.; Bao, Z. and Wu, 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

@conference{winsys13,
author={Shibing Zhang. and Jinming Hu. and Zhihua Bao. and Jianrong Wu.},
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},
}

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 - Hu, J.
AU - Bao, Z.
AU - Wu, J.
PY - 2013
SP - 243
EP - 247
DO - 10.5220/0004537002430247

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