Title :
Least squares channel estimation for a channel with fast time variations
Author :
Zhou, Ning ; Holte, Nils
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Norwegian Inst. of Technol., Trondheim, Norway
Abstract :
It is shown how to improve the tracking properties of least squares (LS) estimation for a time-variant channel estimation (system identification) problem by introducing a parametric time-variant model instead of the conventional model, which is a constant impulse response in each iteration. A recursive LS algorithm is developed for the case that the model varies linearly with time. Simulation results are given for examples where the unknown channel has linear, sinusoidal, and stochastic variations with time. A significant improvement of the tracking properties compared to LMS and conventional LS algorithms is demonstrated for cases with high signal to noise ratio and smooth variations of the unknown channel
Keywords :
least squares approximations; parameter estimation; telecommunication channels; least squares channel estimation; linear variations; parametric time-variant model; recursive LS algorithm; signal to noise ratio; simulation results; sinusoidal variations; stochastic variations; system identification; time-variant channel estimation; tracking properties; Adaptive algorithm; Adaptive signal detection; Channel estimation; Digital communication; Least squares approximation; Paper technology; Parametric statistics; Signal to noise ratio; Stochastic resonance; System identification;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0532-9
DOI :
10.1109/ICASSP.1992.226632
