A transform domain based Least Mean Mixed-Norm algorithm to improve adaptive beamforming

Author

Tinati, M.A. ; Rastegarnia, A. ; Rezaii, T.Y.

Author_Institution

Fac. of Electr. & Comput. Eng., Tabriz Univ., Tabriz

fYear

2008

fDate

25-26 March 2008

Firstpage

1

Lastpage

4

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.

Keywords

array signal processing; least mean squares methods; transforms; adaptive beamforming; convergence rate; discreet sine transform; eigenspread problem; least mean mixed-norm algorithm; mean squared error performance; self-orthogonalizing transform; transform domain; Adaptive arrays; Antenna arrays; Array signal processing; Convergence; Directive antennas; Least squares approximation; Linear antenna arrays; Multiaccess communication; Multimedia systems; Wireless communication;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical Engineering, 2008. ICEE 2008. Second International Conference on

Conference_Location

Lahore

Print_ISBN

978-1-4244-2292-0

Electronic_ISBN

978-1-4244-2293-7

Type

conf

DOI

10.1109/ICEE.2008.4553896

Filename

4553896