Title :
Large-sample performance of blind and Group-blind multiuser detectors: a perturbation perspective
Author :
Xu, Zhengyuan ; Wang, Xiaodong
Author_Institution :
Dept. of Electr. Eng., Univ. of California, Riverside, CA, USA
Abstract :
In blind and group-blind multiuser detection, different detectors can be designed using either the sample data covariance matrix directly or its eigencomponents. Due to finite-sample effect in practice, their performance deviates from the corresponding optimum. A perturbation technique is developed rigorously and systematically to analyze those detectors in this work. Subject to the assumption that the first-order perturbation dominates, corresponding results can be applied to a practical system of a given sample size. In particular, performance of the following typical detectors is studied for either flat or estimated multipath channels: direct-matrix-inversion (DMI) blind minimum mean-square error (MMSE) detector, subspace blind MMSE detector, direct zero-forcing (ZF) detector, subspace ZF detector, and group-blind hybrid detector. Simulation examples further verify various analytical results.
Keywords :
channel estimation; covariance matrices; least mean squares methods; matrix inversion; multipath channels; multiuser detection; perturbation techniques; asymptotic performance; blind minimum mean-square error detector; direct-matrix-inversion; direct-subspace zero forcing detector; eigencomponent; finite-sample effect; first-order perturbation technique; flat-estimated multipath channel; group-blind multiuser detector; sample data covariance matrix; subspace blind MMSE detector; subspace decomposition; Analytical models; Covariance matrix; Detectors; Fading; Multiaccess communication; Multipath channels; Multiuser detection; Performance analysis; Performance gain; Perturbation methods; Asymptotic performance; multiuser detection; perturbation analysis; subspace decomposition;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2004.834853
