An Iterative ML-based Carrier Frequency Estimation Algorithm

Author

Wu, Luo ; An, Liu ; Liu, Bin

Author_Institution

Sch. of EECS, Peking Univ., Beijing

fYear

2006

fDate

27-30 Nov. 2006

Firstpage

1

Lastpage

3

Abstract

We propose an iterative data-aided algorithm based on maximum likelihood criteria for carrier frequency estimation in burst-mode phase shift keying (PSK) transmission. The proposed algorithm has a low threshold and its estimation range is large, about plusmn40% of the symbol rate. In addition, its accuracy is close to the Cramer-Rao bound (CRB) at signal-to-noise ratio (SNR) above threshold. The performance of the proposed algorithm is better and its computational complexity is also lower compared with previous ML-based algorithms.

Keywords

computational complexity; maximum likelihood estimation; phase shift keying; signal processing; Cramer-Rao bound; burst-mode phase shift keying transmission; carrier frequency estimation algorithm; computational complexity; iterative data-aided algorithm; maximum likelihood criteria; signal-to-noise ratio; symbol rate; Computational complexity; Digital communication; Frequency estimation; Iterative algorithms; Maximum likelihood detection; Maximum likelihood estimation; Phase estimation; Phase shift keying; Signal to noise ratio; Yield estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Communication Technology, 2006. ICCT '06. International Conference on

Conference_Location

Guilin

Print_ISBN

1-4244-0800-8

Electronic_ISBN

1-4244-0801-6

Type

conf

DOI

10.1109/ICCT.2006.341700

Filename

4146355