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Adaptive Long-Range Prediction of Three-State LMS Channel Model

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Abstract

In order to provide the accurate real-time knowledge of future channel state information for the adaptive transmission of narrowband land mobile satellite (LMS) communication systems, an adaptive long-range prediction (ALRP) method, suitable for a three-state LMS channel model at S-band, is proposed. The very slow shadowing conditions’ variations of satellite propagation channel can be described as a three-state Gilbert–Elliot channel model based on Markov chain. The channel state of future long-range is predicted based on weighting prediction while the parameters of linear auto-regression model are updated using an iterative adaptive tracking algorithm. The future channel fading series are predicted by the latest observations within current channel state. Simulation results show that the proposed method can be used to predict the future long-range channel state and fading series of three-state Gilbert–Elliot channel model accurately; and it is observed from the mean square error results that the prediction performance of the ALRP method is much more accurate than that of long-range prediction method. Moreover, the method has advantage of real-time and low-complexity which will make the adaptive transmission techniques feasible for LMS channel models.

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Acknowledgments

This paper is funded by the International Exchange Program of Harbin Engineering University for Innovation-oriented Talents Cultivation, the China Postdoctoral Science Foundation funded project (2011M500640), and Postdoctoral Science Foundation of Heilongjiang Province (LBH-Z10206) and China Fundamental Research Funds for Central Universities (HEUCF130802).

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  1. College of Information and Communication Engineering, Harbin Engineering University, Harbin, 150001, China

    Dan-feng Zhao, Xi Liao & Yang Wang

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  1. Dan-feng Zhao
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  2. Xi Liao
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  3. Yang Wang
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Correspondence to Xi Liao.

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Zhao, Df., Liao, X. & Wang, Y. Adaptive Long-Range Prediction of Three-State LMS Channel Model. Wireless Pers Commun 82, 745–756 (2015). https://doi.org/10.1007/s11277-014-2250-9

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  • DOI: https://doi.org/10.1007/s11277-014-2250-9

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