This paper develops an adaptive maximum likelihood sequence estimator (MLSE
) for rapidly fading channels corrupted by additive white Gaussian noise. T
his estimator is based on an explicit incorporation of the time-varying cha
racteristics in channel modelling. When the multipath is caused by a few st
rong reflectors, the channel is shown to be poly-periodically time varying.
The channel impulse response is then approximated by a linear combination
of a finite set of complex exponential functions whose frequencies are term
ed Doppler frequencies. This modelling is well motivated in aeronautical ra
dio communications and cellular telephony. During the training period, a cy
clic statistics-based approach is developed to estimate the Doppler frequen
cies. An eigenvector approach as well as a maximum likelihood method are pr
oposed to estimate the coefficients of linear expansion. After this initial
ization, the channel parameters are updated using a modified version of the
LMS algorithm. Computer simulations are carried out to evaluate the propos
ed receiver performance. The new approach exhibits a large saving in comput
ational complexity and offers superior performance over conventional adapti
ve MLSE in rapidly fading environment. (C) 2000 Published by Elsevier Scien
ce B.V. All rights reserved.