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Generalized eigenvector algorithm for blind equalization
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DOI：10.1016/S0165-1684(97)00108-4.png)
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In 1994, an eigenvector solution to the problem of blind equalization of possibly mixed-phase linear time-invariant transmission channels was published in this journal. Unfortunately, this solution is ambiguous on a certain condition. In this paper, we introduce a novel iterative method termed EigenVector Algorithm for blind equalization (EVA), which not only overcomes the uniqueness problem, but also ensures, after some iterations, optimum linear equalization from few samples of the received signal. In the second part of the paper, the eigenvector solution is generalized to multiple output channels. The resulting algorithm, called GenEVA (Generalized EVA), can be applied to the iterative adjustment of (i) multiple parallel symbol-rate FIR equalizers, (ii) fractional tap spacing FIR equalizers, (iii) non-linear decision-feedback and (iv) time-variant FIR equalizers. Extensive simulation results illustrate the exceptional capabilities of GENEVA. (C) 1997 Elsevier Science B.V.
Keyword:
blind equalization
blind deconvolution
higher order statistics
cumulants
EVD
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3.6
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9.9K
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1.7W
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