Agglomerative user clustering and downlink group scheduling for FDD massive MIMO systems

Two-stage precoding is a promising transmission strategy for multi-user frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) systems due to its large multiplexing gain with overhead reduction in both downlink channel estimation and channel state information (CSI) feedback. The performance of existing two-stage precoding schemes mainly depends on appropriate selection and clustering of the users, which is sometimes difficult to realize in a realistic scenario with limited number of users having different covariance eigenspace. In this paper, we propose a new agglomerative clustering method for user grouping which can be easily implemented in realistic scenario. We also develop an average signal-to-leakage-plus-noise ratio (SLNR) based downlink group scheduling method to achieve combination of user groups in a particular time-frequency slot. Numerical results validate the performance improvement of the proposed methods over existing methods.