Multidimensional rank reduction estimator for parametric MIMO channel models

Authors:
Marius Pesavento;Christoph F. Mecklenbräuker;Johann F. Böhme
Affiliations:
Lehrstuhl für Signaltheorie, Ruhr-Universität Bochum, Bochum, Germany;FTW - Forschungszentrum Telekommunikation Wien, Wien, Austria;Lehrstuhl für Signaltheorie, Ruhr-Universität Bochum, Bochum, Germany
Venue:
EURASIP Journal on Applied Signal Processing
Year:
2004

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Abstract

A novel algebraic method for the simultaneous estimation of MIMO channel parameters from channel sounder measurements is developed. We consider a parametric multipath propagation model with P discrete paths where each path is characterized by its complex path gain, its directions of arrival and departure, time delay, and Doppler shift. This problem is treated as a special case of the multidimensional harmonic retrieval problem. While the well-known ESPRIT-type algorithms exploit shift-invariance between specific partitions of the signal matrix, the rank reduction estimator (RARE) algorithm exploits their internal Vandermonde structure. A multidimensional extension of the RARE algorithm is developed, analyzed, and applied to measurement data recorded with the RUSK vector channel sounder in the 2 GHz band.