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Blind channel equalization algorithm based on dual unscented Kalman filter for chaotic multi-input multi-output communication systems

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Abstract

To reduce channel noise, fading, and inter-user interference effectively in the chaotic communication systems with multi-user, a blind channel equalization algorithm based on dual unscented Kalman filter algorithm is proposed. Assuming that the coefficients of a multi-input multi-output (MIMO) channel can be described by an autoregressive model, two separate state-space representations are used for the signals and coefficients. Then two unscented Kalman filters are used to estimate chaotic signals and channel coefficients simultaneously. The simulation results indicate that the algorithm can effectively track the coefficients of the multi-path fading channel in chaotic MIMO communication systems at a fast convergence speed.

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Authors and Affiliations

  1. School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510641, China

    Zhihui Hu  (胡志辉) & Jiuchao Feng  (冯久超)

Authors
  1. Zhihui Hu  (胡志辉)
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  2. Jiuchao Feng  (冯久超)
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Corresponding author

Correspondence to Zhihui Hu  (胡志辉).

Additional information

Supported by National Natural Science Foundation of China (No. 60872123), Joint Fund of National Natural Science Foundation of China and Guangdong Provincial Natural Science Foundation (No. U0835001) and Fundamental Research Funds for Central Universities (No. 2011ZM0033).

HU Zhihui, born in 1984, male, doctorate student.

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Hu, Z., Feng, J. Blind channel equalization algorithm based on dual unscented Kalman filter for chaotic multi-input multi-output communication systems. Trans. Tianjin Univ. 18, 33–37 (2012). https://doi.org/10.1007/s12209-012-1621-0

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  • DOI: https://doi.org/10.1007/s12209-012-1621-0

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