Joint Data and Kalman Estimation for Rayleigh Fading Channels

Authors:
M. J. Omidi;S. Pasupathy;P. G. Gulak
Affiliations:
Department of Electrical and Computer Engineering, University of Toronto, Canada M5S 3G4, omidi@eecg.toronto.edu;Department of Electrical and Computer Engineering, University of Toronto, Canada M5S 3G4, omidi@eecg.toronto.edu;Department of Electrical and Computer Engineering, University of Toronto, Canada M5S 3G4, omidi@eecg.toronto.edu
Venue:
Wireless Personal Communications: An International Journal
Year:
1999

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Abstract

Channel estimation is an essential part of many detection techniques proposed for data transmission over fading channels. For the frequency selective Rayleigh fading channel an autoregressive moving average representation is proposed based on the fading model parameters. The parameters of this representation are determined based on the fading channel characteristics, making it possible to employ the Kalman filter as the best estimator for the channel impulse response. For IS-136 formatted data transmission the Kalman filter is employed with the Viterbi algorithm in a Per-Survivor Processing (PSP) fashion and the ove rall bit error rate performance is shown to be superior to that of detection techniques using the RLS and LMS estimators. To allow more than one channel estimation per symbol interval, Per-Branch Processing (PBP) method is introduced as a general case of PSP and its effect on performance is evaluated. The sensitivity of performance to parameters such as fading model order and vehicle speed is also studied.