Statistical performance analysis of the algebraic constant modulus algorithm

Authors:
A.-J. van der Veen
Affiliations:
Dept. of Electr. Eng., Delft Univ. of Technol.
Venue:
IEEE Transactions on Signal Processing
Year:
2002

Citing 0
Cited 2

Tensor-based techniques for the blind separation of DS-CDMA signals

Signal Processing
Multiuser channel estimation for ultra-wideband systems using up to the second-order statistics

EURASIP Journal on Applied Signal Processing

Quantified Score

Hi-index	35.68

Visualization

Abstract

This paper presents a large sample analysis of the covariance of the beamformers computed by the analytical constant modulus algorithm (ACMA) method for blindly separating constant modulus sources. This can be used to predict the signal-to-interference plus noise ratio (SINR) performance of these beamformers, as well as their deviation from the (nonblind) Wiener receivers to which they asymptotically converge. The analysis is based on viewing ACMA as a subspace fitting optimization, where the subspace is spanned by the eigenvectors of a fourth-order covariance matrix. The theoretical performance is illustrated by numerical simulations and shows a good match.