In mobile communications the movement of the users makes the propagation channel to be time-varying. Algorithms that track channel variations have to trade between complexity and accuracy. Since the second-order statistic of time-varying channels is stationary, estimation of the channel can be reduced to track a set of r un-correlated parameters. Based on this decomposition, in this paper we propose to simplify the optimum Kalman filter (KF) by tracking the r channel modes separately and by using the steady-state solution of the KF gain.

Kalman filter of channel modes in time-varying wireless systems

NICOLI, MONICA BARBARA;SPAGNOLINI, UMBERTO
2005-01-01

Abstract

In mobile communications the movement of the users makes the propagation channel to be time-varying. Algorithms that track channel variations have to trade between complexity and accuracy. Since the second-order statistic of time-varying channels is stationary, estimation of the channel can be reduced to track a set of r un-correlated parameters. Based on this decomposition, in this paper we propose to simplify the optimum Kalman filter (KF) by tracking the r channel modes separately and by using the steady-state solution of the KF gain.
2005
ICASSP
0780388747
Algorithms; Computational complexity; Kalman filtering; Optimization; Parameter estimation; Time varying control systems; User interfaces Optimum Kalman filters; Steady state solution; Time varying channels; Track channel variations
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/258397
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