Iterative Algorithms for Channel Identification Using Superimposed Pilots

Author

Varma, Angiras R. ; Andrew, Lachlan L H ; Athaudage, Chandra R N ; Manton, Jonathan H.

Author_Institution

Dept. of Electr. & Electron. Eng., Melbourne Univ., Vic.

fYear

2005

fDate

2-4 Feb. 2005

Firstpage

195

Lastpage

201

Abstract

Channel identification of a time-varying channel is considered using superimposed training. A sequence of known symbols with lower power is arithmetically added to the information symbols before modulation and transmission. The channel estimation is done exploiting the known superimposed data in the transmitted signal. Two iterative algorithms are considered in this paper: recursive least squares (RLS) and the expectation maximization (EM). Performance of the proposed algorithms is compared with a simple averaging scheme and the LMS algorithm. For short data blocks RLS outperforms EM, but with large blocks EM is superior

Keywords

channel allocation; channel estimation; expectation-maximisation algorithm; least squares approximations; modulation; time-varying channels; channel identification; expectation maximization; iterative algorithms; recursive least squares; superimposed pilots; time-varying channel; Bandwidth; Bit error rate; Channel estimation; Iterative algorithms; Least squares approximation; OFDM; Resonance light scattering; Signal to noise ratio; Statistics; Time-varying channels;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications Theory Workshop, 2005. Proceedings. 6th Australian

Conference_Location

Brisbane, Qld.

Print_ISBN

0-7803-9007-5

Type

conf

DOI

10.1109/AUSCTW.2005.1624251

Filename

1624251