Matrix analysis
Matrix computations (3rd ed.)
Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion
Rank-deficient and discrete ill-posed problems: numerical aspects of linear inversion
Array Signal Processing: Concepts and Techniques
Array Signal Processing: Concepts and Techniques
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Random matrix theory and wireless communications
Communications and Information Theory
Reduced-rank adaptive filtering using Krylov subspace
EURASIP Journal on Applied Signal Processing
Generalized consistent estimation on low-rank Krylov subspaces of arbitrarily high dimension
IEEE Transactions on Signal Processing
Reduced-rank adaptive filtering
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
A Competitive Mean-Squared Error Approach to Beamforming
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Optimal reduced-rank estimation and filtering
IEEE Transactions on Signal Processing
A multistage representation of the Wiener filter based on orthogonal projections
IEEE Transactions on Information Theory
Performance of reduced-rank linear interference suppression
IEEE Transactions on Information Theory
Simple polynomial detectors for CDMA downlink transmissions on frequency-selective channels
IEEE Transactions on Information Theory
Design of reduced-rank MMSE multiuser detectors using random matrix methods
IEEE Transactions on Information Theory
Large system transient analysis of adaptive least squares filtering
IEEE Transactions on Information Theory
A Systematic Approach to Multistage Detectors in Multipath Fading Channels
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Asymptotic Performance of Reduced-Rank Linear Receivers With Principal Component Filter
IEEE Transactions on Information Theory
Asymptotic Performance of MMSE Receivers for Large Systems Using Random Matrix Theory
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Linear parallel interference cancellation in long-code CDMA multiuser detection
IEEE Journal on Selected Areas in Communications
Design and analysis of low-complexity interference mitigation on vector channels
IEEE Journal on Selected Areas in Communications
Generalized consistent estimation on low-rank Krylov subspaces of arbitrarily high dimension
IEEE Transactions on Signal Processing
| Hi-index | 35.69 |
An improved construction of the optimal reduced-rank linear minimum mean-square error (MMSE) estimator of a signal waveform of interest is derived that is consistent under a limited number of samples per filtering degree-of-freedom. The new filter design generalizes traditional filter realizations based on directly replacing the theoretical covariance matrix by its sample estimate, and being consistent when all dimensions in the model but the number of samples remain bounded. Our solution not only generalizes the conventional estimator, but also turns out to appropriately characterize model mismatch constraints due to finite sample-size limitations of fundamental importance in practical situations. The proposed implementation results from a generalized consistent estimation of the set of MMSE filter subspace coefficients on the reduced-dimensional subspace. Results are based on the theory of the spectral analysis of large-dimensional random matrices. In particular, we build on the analytical description of the asymptotic spectrum of sample-covariance-type matrices in the limiting regime defined as both the number of samples and the observation dimension grow without bound at the same rate. As a result, the proposed MMSE signal waveform estimator is shown to present a superior mean-square error performance under a finite sample-size by avoiding the breakdown experienced as the selected rank increases.