Parameter estimation for MIMO system based on MUSIC and ML methods

Abstract

The frequency offset and channel gain estimation problem for multiple-input multiple-output (MIMO) systems in the case of flat-fading channels is addressed. Based on the multiple signal classification (MUSIC) and the maximum likelihood (ML) methods, a new joint estimation algorithm of frequency offsets and channel gains is proposed. The new algorithm has three steps. A subset of frequency offsets is first estimated with the MUSIC algorithm. All frequency offsets in the subset are then identified with the ML method. Finally, channel gains are calculated with the ML estimator. The algorithm is a one-dimensional search scheme and therefore greatly decreases the complexity of joint ML estimation, which is essentially a multi-dimensional search scheme.

Keywords

multiple-input multiple-output (MIMO) / multiple signal classification (MUSIC) / frequency offsets / channel estimation / maximum likelihood (ML) estimation

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Acknowledgements

This work was supported by the National Science Fund for Distinguished Young Scholars (No. 60725105), the National Basic Research Program of China (No. 2009CB320404), the National Natural Science Foundation of China (Grant No. 60572146), The Research Fund for the Doctoral Program of Higher Education (No. 20050701007), the Fund of Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institute of China, the Key Project of Science and Technologies Research of MOE (No. 107103) and the 111 Project (B08038).

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg