Radial Basis Function Neural Network Receiver for Wireless Channels

Pedro Henrique Gouvêa Coelho, Fabiana Mendes Cesario

2015

Abstract

Artificial Neural Networks have been widely used in several decision devices systems and typical signal processing applications. This paper proposes an equalizer for wireless channels using radial basis function neural networks. An equalizer is a device used in communication systems for compensating the non-ideal characteristics of the channel. The main motivation for such an application is their capability to form complex decision regions which are of paramount importance for estimating the transmitted symbols efficiently. The proposed equalizer is trained by means of an extended Kalman filter guaranteeing a fast training for the radio basis function neural network. Simulation results are presented comparing the proposed equalizer with traditional ones indicating the efficiency of the scheme.

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Paper Citation


in Harvard Style

Henrique Gouvêa Coelho P. and Mendes Cesario F. (2015). Radial Basis Function Neural Network Receiver for Wireless Channels . In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-096-3, pages 658-663. DOI: 10.5220/0005470106580663


in Bibtex Style

@conference{iceis15,
author={Pedro Henrique Gouvêa Coelho and Fabiana Mendes Cesario},
title={Radial Basis Function Neural Network Receiver for Wireless Channels},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2015},
pages={658-663},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005470106580663},
isbn={978-989-758-096-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Radial Basis Function Neural Network Receiver for Wireless Channels
SN - 978-989-758-096-3
AU - Henrique Gouvêa Coelho P.
AU - Mendes Cesario F.
PY - 2015
SP - 658
EP - 663
DO - 10.5220/0005470106580663