A sequential Monte-Carlo Kalman filter based delay and channel estimation method in the MIMO-OFDM system

We propose a new propagation delay and channel estimation algorithm for a MIMO-OFDM system. To estimate delay parameters which enter the observation function in a nonlinear manner, we propose a sequential Monte-Carlo (SMC) filter which incorporates the extended Kalman filter (EKF) to generate delay samples. To reduce the complexity, the SMC filter employs sequential importance sampling. In the MIMO-OFDM system, the initial estimate for the delays and channels are obtained using one training symbol. In the remaining OFDM symbol intervals, the QRD-M algorithm is employed to detect the transmitted data symbols. The QRD-M data detector and SMC channel/delay estimator are finally combined in a joint decision-directed algorithm.