Abstract
Channel estimation is an important issue for wireless communication system. A Channel estimation scheme using Takagi-Sugeno (T-S) fuzzy-based Kalman filter under the time-varying velocity of mobile station in a multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) system is proposed in this paper. We consider the orthogonal space time block coding (OSTBC) scheme of MIMO system where the mobile radio channel is modeled as an autoregressive (AR) random process. The parameters of the AR process and the channel gain are simultaneously estimated by the proposed T-S fuzzy-based Kalman filter to achieve robust nonlinear parameter estimation and prediction by interpolating several linear parameter systems at different mobile speeds to approximate the nonlinear parameter systems in MIMO-OFDM communication. It is useful for the decision-directed channel tracking design, especially in fast fading channel due to time-varying velocity of mobile station. The inherent delay problem of decision-directed scheme can also be compensated by a fuzzy Kalman-based channel prediction method. Further, the robust MMSE equalization design can be achieved by the consideration of channel prediction error to improve the performance of symbol detection. To confirm the performance of proposed method, several simulation results are given in comparison with other methods. With consideration of time-varying velocity of the mobile station communicated in the MIMO-OFDM system, the enhanced equalizer based on the T-S fuzzy-based Kalman filter performs better than those based on the conventional channel estimators in symbol error rate.