Spectrum Quantization and Feedback for Downlink Massive MIMO Systems With Cascaded Precoding.

In this paper, we investigate the quantization and the feedback of downlink statistical channel information for massive multiple-input multiple-output (MIMO) systems with cascaded precoding. Massive MIMO has gained a lot of attention recently because of its ability to significantly improve the network performance. To reduce the overhead of downlink channel estimation and uplink feedback in frequency-division duplex massive MIMO systems, cascaded precoding has been proposed, where the outer precoder is implemented using traditional limited feedback while the inner precoder is determined by the spatial covariance matrix of the channels. In massive MIMO systems, it is difficult to quantize the spatial covariance matrix because of its large size caused by the huge number of antennas. In this paper, we propose a low-complexity and low-overhead approach based on the quantization and the feedback of the spatial spectrum to construct a codebook composed of quantized covariance matrices. The proposed approach has much smaller leakage than the traditional discrete Fourier transform submatrix based precoding. Simulation results show that the proposed approach can significantly reduce the feedback overhead at the cost of a slight performance degradation.