Joint multicast beamforming and user grouping in massive MIMO systems

In this paper we consider the multicast transmission in massive MIMO systems where the base station (BS) serves multiple multicast groups simultaneously. Each single-antenna user takes interest in multiple groups but can be only assigned to one interested group during each transmission interval. We study the joint optimization of beamformer design and user grouping under the max-min fairness objective. First, when the BS has the perfect channel state information (CSI) of all users, we show that the asymptotic signal to interference plus noise ratio (SINR) is independent of user grouping and derive the optimal beamformers in closed-form. Second, we consider the imperfect CSI case in time-division duplex (TDD) mode where the BS obtains the downlink channel as the reciprocity of the estimated uplink channel. Instead of estimating every individual user channels, the BS estimates the composite channel of each multicast group.With pilot power control and beamformer power allocation, we propose an optimal user grouping algorithm and a low-complexity suboptimal user grouping algorithm. Numerical and simulation results are presented to demonstrate the performances of proposed algorithms.