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We study multiuser detection for direct-sequence code-division multiple-access systems in a multipath environment. Systems with unknown channel information are considered and the well-known result for maximum likelihood multiuser detector is directly used in our work. Due to the high computational cost of the maximum likelihood detector, most existing works have investigated simplified, linearized, and/or suboptimal solutions that have less computational requirements. In our approach, we use the Taguchi method that involves the use of orthogonal arrays in estimating the gradient of the likelihood function. The Taguchi method has been widely used in experimental designs for problems with multiple parameters where the optimization of a cost function is required. In this work, we choose the likelihood function as the cost function in the Taguchi method. The use of the Taguchi method for multiuser detection is a novel idea, and it leads to efficient algorithms that can find a satisfactory solution by maximizing the likelihood function in a small number of iterations. One of the advantages of the present Taguchi method is that it is blind since no channel estimation is required to detect the transmitted data, which is not the case in many existing methods. Simulation results show that the Taguchi multiuser detector significantly outperforms the conventional receivers, is insensitive to initial values of parameters, and has performance close to that of minimum mean square error detectors and decorrelating detectors. In addition, our algorithm is suitable for parallel implementations.