FDD Massive MIMO Without CSI Feedback
Deokhwan Han, Jeonghun Park, Namyoon Lee
Abstract
Transmitter channel state information (CSIT) is indispensable for the spectral efficiency gains offered by massive multiple-input multiple-output (MIMO) systems. In a frequency-division-duplexing (FDD) massive MIMO system, CSIT is typically acquired through downlink channel estimation and user feedback, but as the number of antennas increases, the over-head for CSI training and feedback per user grows, leading to a decrease in spectral efficiency. In this paper, we show that, using uplink pilots in FDD, the downlink sum spectral efficiency gain with perfect downlink CSIT is achievable when the number of antennas at a base station is infinite by leveraging the partial channel reciprocity between uplink and downlink channels. Specifically, the key idea showing our result is the mean squared error-optimal downlink channel reconstruction method using uplink pilots, and the robust downlink precoding method harnessing the reconstructed channel with the error covariance matrix. Our simulation results show that our proposed precoding method can attain comparable sum spectral efficiency to zero-forcing precoding with perfect downlink CSIT, without CSI training and feedback.