Research Of Channel Estimation Based On Pilot For MIMO-OFDM System

In the MIMO-OFDM system, channel estimation determines whether the codec and equalization processes can be accurate, and it is necessary to obtain the channel state information. So the channel estimation for system function is critical. This paper studies MMO-OFDM system channel estimation and focuses on the pilot channel estimation methods of MIMO-OFDM systems.First, the fading characteristics of radio channel are described, and the system capacity of MIMO system with the different number of antennas and different diversity modes is analyzed, and then the three commonly used kinds of space-time coding for MIMO system are studied, including the technical analysis and performance comparison. Then the paper analyzes the principle, system model and key technologies of OFDM system. As the separate study of MIMO and OFDM systems, the space-time coding MIMO-OFDM system model is established finally. Then, the paper starts form the studies of pilot channel estimation algorithm under flat fading channel, and next, researches and studies pilot channel estimation algorithm under the time varying channel. Under the flat fading channel, a number of common algorithms, such as LS, MMSE, and LMMSE algorithms are analyzed. Then a new LS algorithm with adding window and a recursive LMMSE estimation algorithm are introduced. With the results above, establish a MIMO-OFDM system model channel based on fast time-varying channel. Accounting to the deficiency of Wiener filtering method which is widely used now and has better performance, the Kalman filter is introduced. Owing to the occasional nonlinear characteristics of wireless channel, this paper uses extended Kalman filter (EKF) for MIMO-OFDM system channel estimation, which can linearize nonlinear system. As the large defect that when the system reaches steady state, extended Kalman filter will lose the ability to track the status of the mutation, this paper designes a closed loop and strong tracking extended Kalman filter for achieving the purpose of improving estimation accuracy. In order to achieve strong tracking performance, this paper adopts the time-varying fading factor through real-time adjustment of the estimation error covariance matrix and the corresponding gain matrix, to weak the impact of the old data on the current filter output.Finally, as the continuous improved requirements of real-time for future mobile communication systems, this paper introduces the adaptive filter algorithm for MIMO-OFDM system channel estimation, and then separately researches and analyzes the least mean square (LMS) and recursive least squares (RLS) adaptive Filter algorithm in MIMO-OFDM system, which lays the foundation for further research about adaptive algorithm in this field.