MEP-Based Channel Estimation under Complex Communication Environment

In this paper, we study the channel state information (CSI) estimation by utilizing maximum entropy principle (MEP) and noise modeling method. The new model can not only represent the characters of the complex communication environment, but can also adjust itself according to the environment by using machine learning. In addition, a new iteration algorithm is presented to derive numerical results. Adaptive parameters learning and features choosing capability make the proposed method outperform the existing methods. The accuracy of estimation is verified by the Monte Carlo simulations.