Expectation-Maximization-Based Channel Estimation for Multiuser MIMO Systems

Multiuser multiple-input multiple-output (MUMIMO) transmission techniques have been popularly used to improve the spectral efficiency and user experience. However, due to the coarse knowledge of channel state information at the transmitter, the quality of transmit precoding to control multiuser interference is degraded, and hence, co-scheduled user equipment may suffer from large residual multiuser interference. In this paper, we propose a new channel estimation technique employing reliable soft symbols to improve the channel estimation and subsequent detection quality of MU-MIMO systems. To this end, we pick reliable data tones from both desired and interfering users and then use them as pilots to re-estimate the channel. In order to jointly estimate the channel and data symbols, we employ the expectation maximization algorithm, where the channel estimation and data decoding are performed iteratively. From numerical experiments in realistic MU-MIMO scenarios, we show that the proposed method achieves substantial performance gain in channel estimation and detection quality over conventional channel estimation approaches.