Estimation of OFDM Time-Varying Fading Channels Based on Two-Cross-Coupled Kalman Filters
Date
2008-08-07
Authors
Abdou, Ahmed
Jamoos, Ali
Journal Title
Journal ISSN
Volume Title
Publisher
Springer, Dordrecht
Abstract
This paper deals with the estimation of rapidly timevarying
Rayleigh fading channels in Orthogonal Frequency
Division Multiplexing (OFDM) mobile wireless systems. When
the fading channel is approximated by an Autoregressive (AR)
process, it can be estimated by means of Kalman filtering.
Nevertheless, the AR model order has to be selected. In addition,
the AR parameters must be estimated. One standard solution to
obtain the AR parameters consists in first fitting the AR process
autocorrelation function to the theoretical Jakes one and then
solving the resulting Yule-Walker Equations (YWE). However,
this approach requires the Doppler frequency which is usually
unknown. To avoid the estimation of the Doppler frequency, the
joint estimation of both the channel and its AR parameters can
be addressed. Instead of using the Expectation-Maximization
(EM) algorithm which results in large storage requirements and
high computational cost, we propose to consider a structure
based on two-cross-coupled Kalman filters. It should be noted
that the Kalman filters are all the more interactive as the
variance of the innovation of the first filter is used to drive the
Kalman gain of the second. Simulation results show the
effectiveness of this approach especially in high Doppler rate
environments.
Description
Keywords
Orthogonal Frequency Division Multiplex , Kalman Filter , Fading Channel , Little Mean Square , Orthogonal Frequency Division Multiplex System