Design And Realization Of Channel Estimation For MIMO-OFDM Systems Based On Subspace

Multiple Input Multiple Output and Orthogonal Frequency Division Multiplexing (MIMO-OFDM) has been considered as the key technology for the next generation wireless communication systems, because of its high rate transmission capability , high spectrum efficiency and its robustness to frequency selective fading. Channel estimation is an important role for coherent detection and for achieving the high transmission performance in the MIMO-OFDM systems. Pilot-assisted channel estimation methods are widely used in MIMO-OFDM systems, they waste rate bandwidth and reduce the efficiency of systems. Blind channel estimation methods can increase the bandwidth efficiency of systems, but their computational complexity is high and their precision is low. Therefore, semi-blind channel estimation, which can combines the advantages of pilot-assisted and blind channel estimation.This paper focuses on the semi-blind channel estimation based on subspace for MIMO-OFDM systems. First, this paper studies the subspace-based channel estimation algorithm in the time domain, and a effective method for solving the fuzzy factor is proposed. The experiment results show that this method can effectively improve the channel estimation accuracy and the communication efficiency due to its no need for pilots. Then, the subspace-based channel estimation algorithm in the frequency domain is investigated in this paper. Similar with in the time domain, a new semi-blind channel estimation method based on subspace for MIMO-OFDM systems in the frequency domain is proposed. The channel matrix is decomposed by two parts. The first part is estimated by received data using the subspace method. By exploiting the frequency correlation among adjacent OFDM subcarriers, the method can reduce the computational complexity. The second part is a rotation matrix, which is then estimated by employing pilot symbols. The proposed method is validated through computer simulation-based experimentations, and simulation results show the effectiveness of the algorithm.