Title :
Fast blind and semi-blind identification and equalization of mobile radio fading channels
Author :
Schmidbauer, Andreas
Author_Institution :
Inst. for Commun. Eng., Munich Univ. of Technol., Germany
Abstract :
An iterative algorithm for fast blind and semi-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.) transmitted 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. The complete algorithm makes use of a-priori information, e.g., from an outer decoding stage (channel decoder) to improve the performance. Also exploiting training symbols is possible. Despite of the use of fourth order cumulants the complexity of the algorithm is rather low compared with alternative blind methods. According to the BER rates after channel decoding the iterative blind scheme is as efficient as a training sequence based system
Keywords :
AWGN; blind equalisers; convergence of numerical methods; error statistics; fading channels; higher order statistics; identification; iterative decoding; iterative methods; mobile radio; parameter estimation; BER; additive white Gaussian noise; blind channel identification; channel decoding; channel estimation; complexity; fading channels; fast convergence properties; fourth order cumulants; i.i.d. transmitted data; iterative algorithm; mixed-phase moving average channels; mobile radio; semi-blind channel identification; super-exponential-algorithm; training symbols; Blind equalizers; Convergence; Fading; Iterative algorithms; Iterative decoding; Land mobile radio; Mobile communication; Signal processing; Signal processing algorithms; Vectors;
Conference_Titel :
Signal Processing and its Applications, Sixth International, Symposium on. 2001
Conference_Location :
Kuala Lumpur
Print_ISBN :
0-7803-6703-0
DOI :
10.1109/ISSPA.2001.949832