Super-exponential-estimator for fast blind channel identification of mobile radio fading channels

Author

Schmidbauer, Andreas

Author_Institution

Inst. for Commun. Eng., Tech. Univ. Munchen, Germany

fYear

2000

fDate

2000

Firstpage

673

Lastpage

676

Abstract

An iterative algorithm for blind channel identification (no training symbols necessary) based on the super-exponential algorithm is shown. On the assumption of independent identically distributed (IID) data the algorithm has fast convergence properties. It is robust with respect to system overfit (supernumerarily assumed channel coefficients converge to zero) and influence of modest additive white Gaussian noise even in mixed-phase moving average channels. Despite of the use of fourth order cumulants the complexity of the algorithm is rather low compared with alternative blind methods. So the implementation on a signal processor (TMS320C40) is possible assuming GSM-like conditions

Keywords

AWGN; cellular radio; convergence of numerical methods; exponential distribution; fading channels; higher order statistics; identification; iterative methods; GSM; IID data; TMS320C40; additive white Gaussian noise; blind channel identification; complexity; convergence; fading channels; fourth order cumulants; independent identically distributed data; iterative algorithm; mobile radio; signal processor; super-exponential estimator; system overfit; Additive white noise; Blind equalizers; Convergence; Fading; Iterative algorithms; Land mobile radio; Mobile communication; Signal processing algorithms; Statistics; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal and Array Processing, 2000. Proceedings of the Tenth IEEE Workshop on

Conference_Location

Pocono Manor, PA

Print_ISBN

0-7803-5988-7

Type

conf

DOI

10.1109/SSAP.2000.870211

Filename

870211