Optimal training for ML and LMMSE channel estimation in MIMO systems

Author

Leus, Geert ; von der Veen, A.-J.

Author_Institution

Fac. EEMCS, Delft Univ. of Technol.

fYear

2005

fDate

17-20 July 2005

Firstpage

1354

Lastpage

1357

Abstract

In this paper, we present some optimal training designs for maximum likelihood (ML) and linear minimum mean square error (LMMSE) channel estimation for multiple-input multiple-output (MIMO) systems. As optimization criterion, the channel mean square error (MSE) is chosen. The key idea is not to restrict the channel estimation to a single transmitted symbol block, but to possibly exploit multiple symbol blocks, assuming the channel remains constant over these blocks. This leads to some new optimal training designs

Keywords

MIMO systems; channel estimation; least mean squares methods; maximum likelihood estimation; wireless channels; LMMSE; MIMO systems; channel estimation; linear minimum mean square error; maximum likelihood; multiple-input multiple-output; optimization criterion; transmitted symbol block; Channel estimation; Data models; Feedback; MIMO; Maximum likelihood estimation; Mean square error methods; Receiving antennas; Stacking; Statistics; Transmitting antennas;

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.2005.1628806

Filename

1628806

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1897979