An Efficient and Fair Scheduling for Downlink 5G Massive MIMO Systems

Massive MIMO (multiple-input multiple-output) is one of the key enabling technology for future generation 5G networks, which groups antenna at both base station and the user terminals to provide high spectral and energy efficiency. Massive MIMO throughput can be increased by scheduling users experiencing good channel conditions, but the users at the edge of the cell with poor channel conditions are often ignored. To improve overall system performance, a certain amount of fairness must be ensured among all the users. In this paper, we propose a fair scheduling algorithm based upon user channel gain to provides higher throughput, sumrate, and better error performance. The simulation results of the proposed algorithm, when compared to the traditional scheduling algorithms, show that the proposed algorithm provides better throughput, sumrate, error performance, and ensures fairness among all users.