Joint User Grouping and Beamforming for Low Complexity Massive MIMO Systems

Abstract

In massive MIMO systems, to partition users into groups and serve the groups separately can significantly reduce the processing complexity. In the existing literature, user grouping is done by classifying the channel covariance matrices. Consequently, the inter-group interference due to user grouping and per group processing is not taken into account. In addition, those methods only work for a fixed number of groups, and the optimal group number is hard to determine. In this paper, a joint user grouping and beamforming strategy is proposed to jointly optimize the number of groups, the user grouping, and the beamforming. The scheme is derived by maximizing the total expected signal-to-interference-leakage-and-noise-ratio (SLNR) lower bound in the network via two-timescale stochastic optimization techniques. Numerical results demonstrate significant sum rate performance gain over the baseline scheme in the literature.