LAUSR

In massive multiple input multiple output (M-MIMO) systems where the number of antennas mounted at the base station (BS) is much larger than that of the mobile users, the existing beamforming schemes generally choose all users over the downlink as receivers. However, due to the fact that various channels may be significantly different, the existing solutions may not be appropriate in case that the number of users becomes sufficiently large, and hence the system throughput is not optimal. In addition, if all antennas at the BS are selected to transmit data streams, the hardware complexity requirement is consequently high, which results in the waste of RF chains and transmit power. In this paper, we propose a new zero-forcing beamforming algorithm on the basis of joint user grouping and antenna selection for M-MIMO systems. When a M-MIMO BS serves a number of users, we divide users into two groups and select an optimal antennas subset. The proposed user grouping method can maximize the total throughput by grouping users into two subsets and selecting the group with better channel station to receive data streams, and the antenna selection method aims to alleviate the system complexity and RF chains cost. The zero-forcing beamforming algorithm based on user grouping and antenna selection will greatly reduce the hardware complexity by lowering the cost and power consumption of radio-frequency chains with only a small performance loss. Simulations illustrate the proposed algorithm provides a better trade-off between the system throughput performance and the hardware complexity in M-MIMO systems.