A MAP Channel Estimation Algorithm for MIMO-OFDM Systems with Better Performance

Maximum a posteriori (MAP) channel estimation algorithm usually uses expectation maximum (EM) algorithm to decrease the high computation. However, this kind of operation has a difficulty in obtaining ideal estimation performance at high signal to noise ratio (SNR) because of the convergent feature of EM algorithm. In addition, for pilot-based multiple-input multiple-output with orthogonal frequency division multiplexing (MIMO-OFDM) systems, data transmission efficiency of OFDM symbol will be reduced with the increasing number of transmit antennas. In order to improve these two drawbacks, firstly, an equivalent signal model is introduced to improve the convergent property of EM algorithm at high SNR. Then, to enhance the data transmission efficiency, joint estimation is implemented by making use of phase shifted orthogonal pilot sequences over multiple OFDM symbols. Whats more, channel matrix is transformed between time domain and angle domain and the concept of angle domain is used to reduce the effect of noise on the estimation by using the spatial independence of MIMO channel in channel matrix of angle domain. Through performance analysis and simulation results, it is indicated that the proposed algorithm has lower estimation error and higher data transmission efficiency than the raw MAP algorithm based on EM process, which only requires increasing the computational complexity a little bit.