Convergence and tracking of adaptive reduced-rank interference suppression algorithms

The convergence and tracking performance of adaptive reduced-rank interference suppression is studied for Direct-Sequence (DS)- Code Division Multiple Access (CDMA) with randomly assigned spreading sequences. We first consider a reduced-rank filter in which the received signal is partially despread before it is applied to a low-rank Multi-Stage Wiener Filter (MSWF) [1]. Partial Despreading (PD) reduces the computational complexity associated with the MSWF. The large system convergence analysis of Least Squares adaptive algorithms presented in [2] is used to evaluate the output Signal-to-Interference Plus Noise Ratio as a function of number of training samples. Our results show that given a sufficient number of training samples, the combined PD-MSWF performs approximately the same as a training-based adaptive MSWF. We then consider the tracking performance of an adaptive low-rank MSWF in the presence of time- and frequency-selective Rayleigh fading. Our results show that the adaptive low-rank MSWF typically gives a significant improvement in coded error rate relative to a full-rank adaptive filter.