Improved robust multiuser detection in non-Gaussian channels

A new technique is proposed for robust multiuser detection in the presence of non-Gaussian ambient noise. This method is based on minimizing a certain cost function (e.g., the Huber penalty function) over a discrete set of ca ndidate user bit vectors. The set of candidate points are chosen based on t he so-called "slowest-descent search," starting from the estimate closest t o the unconstrained minimizer of the cost funct:ion and along mutually orth ogonal directions where this cost function grows the slowest. Simulation re sults show that this new technique offers substantial performance improveme nt over the recently proposed robust multiuser detectors with little attend ant increase in computational complexity.