Abstract: “In multi input multi output orthogonal frequency division multiplexing (MIMO-OFDM) systems, a low complexity subspace based time domain channel estimation method is studied. This method works based on parametric channel model, where the response of the time varying channel is considered as a collection of sparse propagation paths. Translate the estimation of channel parameters into an unconstrained minimized problem by considering the channel correlation matrix. To solve this problem, Kalman filter based method which tracks the subspace is proposed, which provides the constant subspace to construct state equation and measurement equation. This method represents a low complexity subspace schemes. The approach can be extended to MC-CDMA systems. The simulation results prove that the Kalman filter method can track faster fading channel, and is more accurate with low complexity”

Keywords: Channel estimation, Kalman filter, low rank adaptive filter, subspace tracking and time varying channel.