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Artificial Neural Network Channel Estimation Based on Levenberg-Marquardt for OFDM Systems

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Abstract

The many advantages responsible for the widespread application of orthogonal frequency division multiplexing (OFDM) systems are limited by the multipath fading. In OFDM systems, channel estimation is carried out by transmitting pilot symbols generally. In this paper, we propose an artificial neural network (ANN) channel estimation technique based on levenberg-marquardt training algorithm as an alternative to pilot based channel estimation technique for OFDM systems over Rayleigh fading channels. In proposed technique, there are no pilot symbols which added to OFDM. Therefore, this technique is more bandwidth efficient compared to pilot-based channel estimation techniques. Also, this technique is making full use of the learning property of neural network. By using this feature, there is no need of any matrix computation and the proposed technique is less complex than the pilot based techniques. Simulation results show that ANN based channel estimator gives better results compared to the pilot based channel estimator for OFDM systems over Rayleigh fading channel.

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Authors and Affiliations

  1. Kayseri Vocational College, Erciyes University, 38039, Melikgazi, Kayseri, Turkey

    Cebrail Çiflikli & A. Tuncay Özşahin

  2. Faculty of Engineering, Department of Electrical & Electronics Engineering, Atilim University, 06836, Golbasi, Ankara, Turkey

    A. Çağrı Yapici

Authors
  1. Cebrail Çiflikli
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  2. A. Tuncay Özşahin
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  3. A. Çağrı Yapici
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Correspondence to A. Tuncay Özşahin.

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Çiflikli, C., Özşahin, A.T. & Yapici, A.Ç. Artificial Neural Network Channel Estimation Based on Levenberg-Marquardt for OFDM Systems. Wireless Pers Commun 51, 221–229 (2009). https://doi.org/10.1007/s11277-008-9639-2

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  • DOI: https://doi.org/10.1007/s11277-008-9639-2

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