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We consider the problem of joint equalization and decod ing, using the method of turbo equalization originally de veloped by Douillard, et al. [3]. In its original form, turbo equalization requires accurate knowledge of the channel at the receiver. We propose a receiver structure, based on a soft-input Kalman channel estimator, that can operate ef fectively without accurate channel knowledge and without training data. The resulting joint channel and data estimator is shown to outperform standard turbo equalization based on moderate-length traning data.

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