A subspace blind identification algorithm based on CGM with reduced computational complexity

Author

Tanabe, Nari ; Aoki, Ken ; Furukawa, Toshihiro ; Matsue, Hideaki ; Tsujii, Shigeo

Author_Institution

Tokyo Univ. of Sci., Nagano

fYear

2007

fDate

Oct. 30 2007-Nov. 2 2007

Firstpage

1

Lastpage

4

Abstract

We propose a subspace blind channel identification algorithm based on CGM (conjugate gradient method). The algorithm estimates (1) the channel order, (2) the noise variance, (3) the noise subspace, and then identifies (4) channel impulse response without using the eigenvalue decomposition. The special features of the proposed algorithm are (1) accurate channel order estimation and (2) the reduction of computational complexity using CGM. Numerical examples show the effectiveness of the proposed algorithm.

Keywords

channel allocation; channel estimation; computational complexity; conjugate gradient methods; CGM; channel impulse response; computational complexity; conjugate gradient method; subspace blind channel identification algorithm; Additive noise; Additive white noise; Computational complexity; Eigenvalues and eigenfunctions; Gaussian noise; Gradient methods; Signal processing; Signal processing algorithms; Statistics; User-generated content;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON 2007 - 2007 IEEE Region 10 Conference

Conference_Location

Taipei

Print_ISBN

978-1-4244-1272-3

Electronic_ISBN

978-1-4244-1272-3

Type

conf

DOI

10.1109/TENCON.2007.4428828

Filename

4428828