Adaptive filter theory
Fundamentals of matrix computations
Fundamentals of matrix computations
The SVD and reduced rank signal processing
Signal Processing - Theme issue on singular value decomposition
Matrix computations (3rd ed.)
Multiuser Detection
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Adaptive Filtering: Algorithms and Practical Implementation
Adaptive Filtering: Algorithms and Practical Implementation
Space-time adaptive reduced-rank multistage Wiener filtering for asynchronous DS-CDMA
IEEE Transactions on Signal Processing
An iterative algorithm for the computation of the MVDR filter
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Optimal reduced-rank estimation and filtering
IEEE Transactions on Signal Processing
Blind multiuser detection: a subspace approach
IEEE Transactions on Information Theory
A multistage representation of the Wiener filter based on orthogonal projections
IEEE Transactions on Information Theory
Blind adaptive reduced-rank detection for DS-CDMA signals in multipath channels
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Journal of Electrical and Computer Engineering
Mobile Networks and Applications
International Journal of Communication Systems
On the performance of adaptive pruned Volterra filters
Signal Processing
Hi-index | 35.69 |
We present an adaptive reduced-rank signal processing technique for performing dimensionality reduction in general adaptive filtering problems. The proposed method is based on the concept of joint and iterative interpolation, decimation and filtering. We describe an iterative least squares (LS) procedure to jointly optimize the interpolation, decimation and filtering tasks for reduced-rank adaptive filtering. In order to design the decimation unit, we present the optimal decimation scheme and also propose low-complexity decimation structures. We then develop low-complexity least-mean squares (LMS) and recursive least squares (RLS) algorithms for the proposed scheme along with automatic rank and branch adaptation techniques. An analysis of the convergence properties and issues of the proposed algorithms is carried out and the key features of the optimization problem such as the existence of multiple solutions are discussed. We consider the application of the proposed algorithms to interference suppression in code-division multiple-access (CDMA) systems. Simulations results show that the proposed algorithms outperform the best known reduced-rank schemes with lower complexity.