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The large system analysis of randomly spread direct-sequence code-division multiple-access systems operating over frequency-selective fading channels is considered. Iterative Multi-User Detection and Decoding (MUDD) based on generalized posterior mean estimation and single-user sum-product decoding is assumed to be used at the receiver. The Channel State Information (CSI) at the MUDD is mismatched and obtained by a linear channel estimator whose initial decisions are iteratively refined with the help of information feedback provided by the MUDD. Furthermore, a new training method by means of probability-biased signaling is proposed.
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