Model-based channel estimation framework for MIMO multicarrier communication systems
The multicarrier modulation (MCM) using multiple antennas is a promising technique for broadband communications over mobile wireless channels. In this work, we investigate the channel estimation problem for the MCM system with multiple transmitter and receiver antennas. The difficulty of such a problem is that the number of the channel parameters increases proportionally with the number of transmitter antennas while the observations at the receiver do not. A model-based channel estimation framework is proposed to identify the multiple channels simultaneously. Based on this framework, we further discuss the identification condition and the training sequence design by taking into account both the model error and residual noise. Finally, we show the performance of the proposed model-based channel estimation scheme using two types of models, Fourier-transform-based model and polynomial model. We also show the system performance of two space-time codes using the proposed channel estimation algorithm.