Asymptotically optimal simple user scheduling for massive MIMO downlink with two-stage beamforming

Gilwon Lee, Youngchul Sung

Abstract: In this paper, a simple user-scheduling-and-beamforming method is proposed for massive multi-user multiple-input multiple-output (MU-MIMO) downlink adopting two-stage beamforming. The key ideas of the proposed scheduling-and-beamforming method are to divide users into several candidate subsets according to the level of alignment of user channels to the dominant directions of the channel covariance matrix and select the user in each candidate subset based on a certain channel quality indicator (CQI) and to apply post-selection zero-forcing beamforming (ZFBF) to the selected users based on their channel state information (CSI). It is proved that the proposed scheduling-and-beamforming method is asymptotically optimal as the number of users increases. Furthermore, the proposed method significantly reduces the feedback overhead and shows superior sum rate performance compared to existing scheduling methods for MU-MIMO downlink.