Training sequence design for channel state information acquisition in massive MIMO systems

With the rapid growth of global mobile data transmission, the conventional multiple-input multiple-output (MIMO) systems are not able to accommodate the increasing data demand. The massive MIMO has been proposed as one of the key technologies for the next generation wireless communication systems. Compared to the conventional MIMO systems, massive MIMO systems are advantaged in energy and spectral efficiency. However, the advantage of massive MIMO systems is realized only when the channel state information (CSI) is acquired by both the base station (BS) and users accurately. In frequency division duplex (FDD) massive MIMO systems, the overhead of channel estimation could overwhelm the precious downlink resource. In this paper, a design method of optimal training sequence is studied based on the sequential channel estimation scheme with Kalman filter. Simulation results show the performance of the proposed optimal training sequence outperforms the exist ones.