MIMO Time-varying Channel Estimation Based on Kalman Filtering

【Abstract】This paper proposes a novel algorithm which uses the Kalman filtering based on Clarke’s model to track the Multiple-Input Multiple-Output(MIMO) time-varying multi-path fading channel. The channel transport function approximates the square root of the spectrum density, and a state-space model for the fading channel can be built based on the channel transport function. Combining the prior information of the time-varying fading channel power spectral density, MIMO channel state-space model can be obtained. Theoretical analysis and simulations show the algorithm is effective for the estimation of the fading channel when the performance of the channel estimation is presented in terms of the Mean-Square Error(MSE). 【Key words】time-varying channel; Kalman filtering; channel estimation