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Channel Estimation in Long Term Evolution Uplink Using Minimum Mean Square Error-Support Vector Regression

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An Erratum to this article was published on 15 November 2014

Abstract

In this paper, minimum mean square error-support vector regression (MMSE-SVR) is proposed, which is shown to be adequate for the estimation of the long term evolution (LTE) uplink channel with nonlinear features. MMSE-SVR was applied to estimate real channel environments such as the vehicular A channels defined by the International Telecommunication Union (ITU). The simulation results show that the proposed method has a better performance than the least squares support vector machine (LS-SVM) and the standard MMSE with linear and spline interpolation.

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Authors and Affiliations

  1. Division of Electronics and Information Engineering, Chonbuk National University, Jeonju, Korea

    Allaeddine Djouama & Myoung-Seob Lim

  2. University of Science and Technology Houari Boumedien, Algiers, Algeria

    Fatiha Youcef Ettoumi

Authors
  1. Allaeddine Djouama
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  2. Myoung-Seob Lim
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  3. Fatiha Youcef Ettoumi
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Correspondence to Allaeddine Djouama.

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Djouama, A., Lim, MS. & Ettoumi, F.Y. Channel Estimation in Long Term Evolution Uplink Using Minimum Mean Square Error-Support Vector Regression. Wireless Pers Commun 79, 2291–2304 (2014). https://doi.org/10.1007/s11277-014-1985-7

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  • DOI: https://doi.org/10.1007/s11277-014-1985-7

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