Abstract
The massive multiple-input multiple-output (MIMO) has been proposed as one of the key technologies for the next generation wireless communication systems. Uniform planar array (UPA) antenna structures have been considered in many researches because it is able to deploy a large number of antennas in a relatively small area. There are lots of performance superiorities in massive MIMO systems. However, in practice, these superiorities is achieved only when the uplink and downlink channel state information (CSI) are known perfectly by both the base station (BS) and users. In frequency division duplex (FDD) massive MIMO systems, a large percentage of precious downlink capacity is reserved by training sequence for channel estimation due to the large number of antennas. In this paper, a design method of optimal training sequence is studied based on the downlink closed-loop training scheme with UPA, in which the Kalman filter is used for CSI acquisition. Simulation results show that the proposed optimal training sequence based on the closed-loop training scheme outperforms the existing ones.
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