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New Approaches for Channel Prediction Based on Sinusoidal Modeling

EURASIP Journal on Advances in Signal Processing volume 2007, Article number: 049393 (2006) Cite this article

Abstract

Long-range channel prediction is considered to be one of the most important enabling technologies to future wireless communication systems. The prediction of Rayleigh fading channels is studied in the frame of sinusoidal modeling in this paper. A stochastic sinusoidal model to represent a Rayleigh fading channel is proposed. Three different predictors based on the statistical sinusoidal model are proposed. These methods outperform the standard linear predictor (LP) in Monte Carlo simulations, but underperform with real measurement data, probably due to nonstationary model parameters. To mitigate these modeling errors, a joint moving average and sinusoidal (JMAS) prediction model and the associated joint least-squares (LS) predictor are proposed. It combines the sinusoidal model with an LP to handle unmodeled dynamics in the signal. The joint LS predictor outperforms all the other sinusoidal LMMSE predictors in suburban environments, but still performs slightly worse than the standard LP in urban environments.

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Authors and Affiliations

  1. Department of Signals and Systems, Chalmers University of Technology, Göteborg, SE, 412 96, Sweden

    Ming Chen & Mats Viberg

  2. Department of Electronics and Telecommunications, Norwegian Institute of Science and Technology, Trondheim, NO-7491, Norway

    Torbjörn Ekman

Authors
  1. Ming Chen
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  2. Torbjörn Ekman
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  3. Mats Viberg
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Correspondence to Ming Chen.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Chen, M., Ekman, T. & Viberg, M. New Approaches for Channel Prediction Based on Sinusoidal Modeling. EURASIP J. Adv. Signal Process. 2007, 049393 (2006). https://doi.org/10.1155/2007/49393

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