Abstract
In this work the blind equalization of a single-input, multiple-output channel has been carried out using second-order statistics. A sufficient and necessary condition for blind equalization based on second order statistics has been given. It has been proved that a single autocorrelation matrix of the source symbols is sufficient for blind equalization. The proposed scheme is generalized; that is, it is valid for white as well as colored source symbols. A linear artificial neural network is developed with a learning algorithm based on the new condition. The results of the new algorithm verify its validity and superior performance.
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Naveed, A., Qureshi, I., Cheema, T. et al. Blind Channel Equalization Using Second-Order Statistics: A Necessary and Sufficient Condition. Circuits Syst Signal Process 25, 511–523 (2006). https://doi.org/10.1007/s00034-005-0809-0
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DOI: https://doi.org/10.1007/s00034-005-0809-0