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

Abstract

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.

Reduced-Rank MMSE Detection in Space-Time Coded Space-Division Multiple-Access Systems

“…The ponents (PC), cross-spectral metric (CSM) and Taylor poly-three classes of reduced-rank MMSE algorithms are derived, nomial approximation (TPA). Our study and simulation re-respectively, based on the principles of PC [4] - [7], CSM [6,8] sults show that the reduced-rank MMSE detection is capable and TPA [9]. The characteristics of these reduced-rank MMSE of achieving a satisfactory trade-off between the affordable de-algorithms are considered, and their BER performance is intection complexity and the achievable detection BER perfor-vestigated by simulation, when communicating over indepenmance.…”

Robust Rank Reduction Algorithm with Iterative Parameter Optimization and Vector Perturbation

“…In this section, we examine the efficient implementation of two stopping criteria for selecting the rank number d. Unlike prior methods for rank selection, which utilize MSWF-based algorithms [20] or AVF-based recursions [21], we focus on an approach that jointly determines the rank number d based on the LS criterion computed by the filters S D [i] andω [i]. In particular, we present a method for automatically selecting the ranks of the algorithms based on the exponentially-weighted a posteriori least-squares type cost function described by:…”

Adaptive Signal Processing Techniques for Robust, High Capacity Spread- Spectrum Multiple Access

“…Adaptive versions of the MSWF have been presented in [8], which require only a training sequence for filter estimation. In [22] a simple rank-order-recursive method is presented for updating the reduced-rank filter coefficients.…”