Blind Bayesian multiuser detection for impulse radio UWB systems with Gaussian and impulsive noise

In this paper, we address the problem of blind parameter estimation and multiuser detection for impulse radio ultra-wide band (UWB) systems under frequency selective fading. We consider unknown ambient and impulsive noise parameters as well as an unknown UWB channel characterized by a large number of taps, and propose a blind Bayesian multiuser detector based on Gibbs sampling. Because Gibbs sampler is a soft-input soft-output module, capable of exchanging probabilistic information, the proposed detector is also employed within a turbo multiuser detection structure for coded UWB systems. The simulation results show that the Gibbs sampler is effective in estimating the system parameters and that the proposed receiver provides significant performance gains after a few detection/decoding iterations.