Adaptive reduced-rank interference suppression based on the multistage Wiener filter

A class of adaptive reduced-rank interference suppression algorithms is presented based on the multi-stage Wiener filter (MSWF). The performance is examined in the context of direct-sequence (DS) code division multiple access (CDMA). Unlike the Principal Components method for reduced-rank filtering, the algorithms presented can achieve near full-rank performance with a filter rank much less than the dimension of the signal subspace. We present batch and recursive algorithms for estimating the filter parameters, which do not require an eigen-decomposition. Algorithm performance in a heavily loaded DS-CDMA system is characterized via computer simulation. Results show that the reduced-rank algorithms require significantly fewer training samples than other reduced- and full-rank algorithms.