EURASIP Journal on Applied Signal Processing 
Volume 2004 (2004), Issue 9, Pages 1354-1363
doi:10.1155/S1110865704401036

Multidimensional Rank Reduction Estimator for Parametric MIMO Channel Models

Marius Pesavento,1 Christoph F. Mecklenbräuker,2 and Johann F. Böhme1

 1Lehrstuhl für Signaltheorie, Ruhr-Universität Bochum, Bochum 44780, Germany
2FTW - Forschungszentrum Telekommunikation Wien, Wien, 1220, Austria
Received 28 May 2003; Revised 25 November 2003

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.