A low-complexity contextual Hebbian detector for blind multiuser detection

This paper proposes a blind multiuser detector for CDMA systems based on a contextual Hebbian paradigm. Conventional blind detectors employ second-order statistics in their formulation, leading to first-order filter update procedure. These approaches restrict the convergence rate and tracking capability of the detectors. Hebbian learning has shown potential in handling blind source separation problems. Nevertheless, it experiences order ambiguity of the extracted sources. This often leads to undesirable local convergence and consequently erroneous symbol demodulation. This paper presents a new contextual Hebbian paradigm that encapsulates domain information of the multiple-access interference to achieve blind detection. An adaptive detector is developed to address the issues of source indeterminacy and slow convergence. Experimental results show that the detector provides good performance in terms of fast convergence rate, optimal steady-state SINR profile, and low BER when compared with other detectors.