Title :
Iterative 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
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 (i.i.d.) 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. Also the combination with an outer channel (de-)coder and MAP equalizer is possible to improve the performance
Keywords :
AWGN; blind equalisers; channel coding; convergence of numerical methods; decoding; fading channels; higher order statistics; iterative methods; land mobile radio; moving average processes; multiuser channels; parameter estimation; MAP equalizer; additive white Gaussian noise; algorithm complexity; blind equalizer; channel coefficients; fast blind channel identification; fast convergence properties; fourth order cumulants; i.i.d. data; independent identically distributed data; iterative algorithm; iterative super-exponential-estimator; mixed-phase moving average channels; mobile radio fading channels; outer channel coder; outer channel decoder; performance; super-exponential-algorithm; Blind equalizers; Convergence; Fading; Gaussian noise; Iterative algorithms; Land mobile radio; Mobile communication; Noise robustness; Statistics; Vectors;
Conference_Titel :
Vehicular Technology Conference, 2000. IEEE-VTS Fall VTC 2000. 52nd
Conference_Location :
Boston, MA
Print_ISBN :
0-7803-6507-0
DOI :
10.1109/VETECF.2000.886306
