CCA based algorithms for blind equalization of FIR MIMO systems

Author

Vía, Javier ; Santamaría, Ignacio

Author_Institution

Dept. of Commun. Eng., Cantabria Univ., Santander

fYear

2005

fDate

17-20 July 2005

Firstpage

155

Lastpage

160

Abstract

In this work the problem of blind equalization of multiple-input multiple-output (MIMO) systems is formulated as a set of canonical correlation analysis (CCA) problems. CCA is a classical tool that finds maximally correlated projections of several data sets, and it is typically solved using eigendecomposition techniques. Recently, it has been shown that CCA can be alternatively viewed as a set of coupled least squares regression problems, which can be solved adaptively using a recursive least squares (RLS) algorithm. Unlike other MIMO blind equalization techniques based on second-order statistics (SOS), the CCA-based algorithms does not require restrictive conditions on the spectral properties of the source signals. Some simulation results are presented to demonstrate the potential of the proposed CCA-based algorithms

Keywords

MIMO systems; blind equalisers; correlation methods; eigenvalues and eigenfunctions; least squares approximations; regression analysis; transient response; CCA based algorithm; FIR MIMO system; RLS algorithm; SOS; blind equalization; canonical correlation analysis; eigendecomposition technique; finite impulse response; least squares regression problem; multiple-input multiple-output system; recursive least square; second-order statistics; Adaptive equalizers; Blind equalizers; Finite impulse response filter; Higher order statistics; Least squares methods; MIMO; Mobile communication; Resonance light scattering; Signal processing algorithms; Wireless communication;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal Processing, 2005 IEEE/SP 13th Workshop on

Conference_Location

Novosibirsk

Print_ISBN

0-7803-9403-8

Type

conf

DOI

10.1109/SSP.2005.1628583

Filename

1628583