Reduced-complexity ML multi-user detection for dispersive UWB signal based on combined stack and Viterbi trellis search

We propose a novel reduced-complexity maximum-likelihood (ML) detector for multi-user impulse radio ultra-wideband (UWB) signals in multi-path channels. By utilizing the unique trellis feature of a multi-user impulse radio UWB signal, and introducing a novel combined stack and Viterbi based trellis search (CSVS) algorithm, the proposed detector is optimal and enjoys much lower computation complexity compared with the brute-force search based ML detector. Simulation results show that the proposed detector achieves much better performance than the conventional simple matched filter UWB detector.