Abstract

In this paper, an adaptive beamforming algorithm based on least mean mixed norm (LMMN) algorithm and self-orthogonalizing transform is presented. In the proposed algorithm, LMMN is used to improve the convergence rate of conventional LMS algorithm. Whereas, discreet sine transform is used as self-orthogonalizing transform to address the eigen-spread problem. The simulation results are the evidence of significantly improvement in the convergence rate and mean squared error (MSE) performance of the proposed algorithm.

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