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Blind Source Separation for Complex-Valued Signals Using Generalized Autocorrelation

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  • Xiaogang Tang
  • Sun’an Wang
  • Jiong Li

Abstract

We introduce a new complex-valued blind source separation approach, based on generalized autocorrelations of sources, to improve the spectrum efficiency for the next-generation wireless communications system. The proposed algorithm considers the temporal structures of communication signals and the natural gradient-based method is used to optimize the demixing matrix. In addition, the local stability condition is proved. Simulation results are presented showing the superior performance of the proposed algorithm in the intersymbol interference of the estimated signals.

Suggested Citation

  • Xiaogang Tang & Sun’an Wang & Jiong Li, 2018. "Blind Source Separation for Complex-Valued Signals Using Generalized Autocorrelation," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-9, July.
    • Handle: RePEc:hin:jnlmpe:8076468
    DOI: 10.1155/2018/8076468
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