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Robust Blind Beamforming Algorithm Using Joint Multiple Matrix Diagonalization

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3 Author(s)
Xiaozhou Huang ; Dept. of Electr. & Comput. Eng., Louisiana State Univ., Baton Rouge, LA ; Hsiao-Chun Wu ; Principe, J.C.

The objective of the blind beamforming is to restore the unknown source signals simply based on the observations, without a priori knowledge of the source signals and the mixing matrix. In this paper, we propose a new joint multiple matrix diagonalization (JMMD) algorithm for the robust blind beamforming. This new JMMD algorithm is based on the iterative eigen decomposition of the fourth-order cumulant matrices. Therefore, it can avoid the problems of the stability and the misadjustment, which arise from the conventional steepest-descent approaches for the constant-modulus or cumulant optimization. Our Monte Carlo simulations show that our proposed algorithm significantly outperforms the ubiquitous joint approximate diagonalization of eigen-matrices algorithm, relying on the Givens rotations for the phase-shift keying source signals in terms of signal-to-interference-and-noise ratio for a wide variety of signal-to-noise ratios

Published in:

Sensors Journal, IEEE  (Volume:7 ,  Issue: 1 )