Statistical CSI Acquisition in the Nonstationary Massive MIMO Environment.

This paper studies the statistical channel state information (S-CSI) acquisition problem in the nonstationary massive multiple-input multiple-output (MIMO) environment, where both the instantaneous and statistical channel states are time varying. First, we set up a hidden statistical channel state Markov model (HSCSM model). Then, the parameter of the HSCSM model is estimated through the observed sequence of received signals. Next, based on the HSCSM model and its estimated parameter, the S-CSI is obtained through a maximum a-posteriori decision process. Simulation results show that an accurate S-CSI acquisition can be achieved by the proposed approach in the nonstationary massive MIMO environment. In addition, the estimation accuracy rate of the proposed approach increases with the length of observation sequence as well as the number of antennas, where a tradeoff between them exists given a limited computing ability/storage space. [ABSTRACT FROM AUTHOR]