Performance of Data-Rate Analysis of Massive MIMO System Using User Grouping

The major challenges in massive MIMO networks are to increase the system throughput and capacity with low complexity and reliability of the wireless communication system. The computational complexity and system capacity of massive MIMO (M-MIMO) systems depend on adequate user grouping, user selection, and antenna scheduling methods. Additionally, the interference of the M-MIMO system is reduced when used suitable signal processing schemes. In this paper, we proposed a novel circular user grouping technique to reduce system complexity. Later, semi-orthogonal user selection with three different combinations of user selection schemes and norm-based antennas scheduling method is used to achieve higher system capacity in M-MIMO systems. Moreover, simple linear zero-forcing and minimum mean square error signal processing schemes are used to minimize the user’s interference. The simulation results show that our proposed algorithm provides very low computational complexity, reduce the interference and higher the system capacity compare to the traditional M-MIMO system.