Kalman-filter channel estimator for OFDM systems in time and frequency-selective fading environment

We present a Kalman-filter method for the estimation of time-frequency-selective fading channels in OFDM systems. Based on the Jakes model, an autoregressive (AR) model of the channel dynamics is built. To reduce the complexity of the high-dimensional Kalman filer for joint estimation of the subchannels, we propose to use a low-dimensional Kalman filter for the estimation of each subchannel. Then, a minimum mean-square-error (MMSE) combiner is used to refine the Kalman estimates. The per-subchannel Kalman estimator explores the time-domain correlation of the channel, while the MMSE combiner explores the frequency-domain correlation. This two-step solution offers a performance comparable to the much more complicated joint Kalman estimator.