Density Estimation and Application to Robust Multiuser Detection in Heavy Tailed Noise

We address the problem of robust multiuser detection in heavy tailed noise. A number of multiuser detectors which have been proposed require parametric channel noise models. The rigidity in the design of these detectors can make them far from optimal when the channel noise is not close to the assumed distribution. Nonparametric detectors, on the other hand, make no assumption about the noise parameters and have been shown to be robust in different types of channel noise. In this paper, we propose a new class of detector which makes use of some a priori channel information. Simulations show that the proposed detector, under regular circumstances, exhibits robust detection over a wide range of channel noise types and outperforms the nonparametric detector at a lower computational cost.