BLIND ADAPTIVE MULTIUSER DETECTION OVER TIME-VARYING TIME-DISPERSIVE CHANNELS

Abstract

<p>In this thesis, blind multiuser detection of Direct Sequence Code Division Multiple Access (DS-CDMA) signals over time-varying time-dispersive channels is considered. A number of methods for multiuser detection over time-dispersive channels have been proposed previously. Blind multiuser detection requires that the signature waveform of the desired user be reconstructed (blindly) at the receiver. In time-dispersive channels the knowledge of the channel order (length) is needed in order to reconstruct the signature waveform exactly. Previous works in this regard assumed the knowledge of the channel length or they considered an over estimated channel length. However, when the channel length assumed at the receiver differs from the actual one, the performance of the system can degrade significantly. Hence we propose a new multiple model approach that considers many channel-conditioned multiuser detectors in parallel in order to obtain a better estimate via soft decision, instead of making a hard decision about the channel length. We use the Interacting Multiple Model (IMM) estimator, which consists of multiple Kalman filters, to find a better overall estimate from the channel-conditioned filters. Further, in a time-varying environment, where the channel length varies with time, the proposed scheme tracks the channel order very well (without assuming known channel length), and hence performs better than previous methods. Simulation results show that the proposed method outperforms the existing ones in terms of signal to interference plus noise ratio and bit error rate in a time-varying channel.</p>