Orthogonal minimum noise subspace for multiple-input multiple-output system identification

Author

Safavi, Anahid ; Abed-Meraim, Karim

Author_Institution

Telecom Paris, France

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

285

Lastpage

288

Abstract

This contribution deals with a particular family of blind system identification techniques, referred to as minimum noise subspace (MNS) method. The MNS method is a computationally fast version of the subspace method. We develop an orthogonal version of MNS method. The orthogonal minimum subspace (OMNS) method is more efficient in computation than a standard subspace method, and is more robust to channel noise than MNS

Keywords

MIMO systems; computational complexity; identification; noise; telecommunication channels; MIMO system identification; channel noise robustness; computation complexity; computer simulations; estimation accuracy; minimum noise subspace; multiple-input multiple-output system identification; orthogonal minimum noise subspace; orthogonal minimum subspace method; stationary time series; Concurrent computing; Covariance matrix; Finite impulse response filter; Integrated circuit modeling; MIMO; Noise robustness; Signal to noise ratio; System identification; Telecommunications; Transfer functions;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on

Print_ISBN

0-7803-7011-2

Type

conf

DOI

10.1109/SSP.2001.955278

Filename

955278

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1608170