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Blind adaptive multiple-input decision-feedback equalizer with a self-optimized configuration

Abstract : This paper introduces a novel blind adaptive multiple-input decision-feedback equalizer (MI-DFE) which is basically characterizd by its ability to self-optimize its configuration, in terms of both structure and criteria, according to the severity of the transmission medium. In the first running mode, the novel equalizer is recursive, linear and "blindly" adapted by criteria leading to a solution closely related to the minimum MSE solution. In the second running mode, it becomes the conventional MI-DFE. From the viewpoints of both robustness and spectral efficiency, this equalizer proves to be very attractive since it avoids pathological behaviors, often encountered with the conventional trained MI-DFE, while requiring no training sequence. Furthermore, its very high speed of convergence renders it competitive in various standard applications, even in the case of burst mode transmission systems. Finally the novel blingd MI-DFE has been successfully tested on underwater acoustic communications signals, in a very severe context. The results are clearly convincing.
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https://hal.archives-ouvertes.fr/hal-02133914
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Submitted on : Monday, May 20, 2019 - 10:18:05 AM
Last modification on : Saturday, May 1, 2021 - 3:53:07 AM

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Joël Labat, Christophe Laot. Blind adaptive multiple-input decision-feedback equalizer with a self-optimized configuration. IEEE Transactions on Communications, Institute of Electrical and Electronics Engineers, 2001, 49 (4), pp.646 - 654. ⟨10.1109/26.917771⟩. ⟨hal-02133914⟩

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