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Motivated by finding reduced complexity versions of the maximum-likelihood (ML) detector for highly distorted underwater channels, a multiuser detection (MUD) algorithm for joint data detection and channel estimation based on the cyclic coordinate descent method is proposed. Assuming that the data symbols are available, they are used to estimate the channel responses, which, in turn, are used to refine the symbol estimates. Adaptive estimation is performed using minimum mean square error as the overall optimization criterion. The receiver is implemented in a multichannel configuration, which provides the array processing gain necessary for many of the underwater acoustic channels. The complexity of the detection algorithm is linear in the number of receive elements and it does not depend on the modulation level of the transmitted signals. The algorithm has been tested using real data obtained over a 2-km shallow-water channel in a 20-kHz band, demonstrating good results.