Achieving Near Optimal Sum Rate in Downlink Massive Multiple Antenna System

Abstract

In this paper, a massive multiple input multiple output (massive-MIMO) system with up to 600 base station antennas exploiting the channel state information (CSI) to improve the capacity of system while serving multiple UEs was proposed. Two precoding schemes: zero-forcing (ZF) and maximum ratio transmission (MRT) were implemented and used to test the effectiveness of the proposed system. In order to study the effectiveness of the system, its performance was analyzed in terms of achievable sum rate. MATLAB codes were developed for the simulations test conducted to study the sum rate performance of the system. Simulations were carried out by varying the number of base station antennas from 300 to 600 with respect to the number of users to determine the achievable sum rate of the system. Results showed that increasing the number of base station antennas brings about better spectral efficiency for optimal multiuser interference reduction such that highest sum rates: 317.5 Bits/s/Hz and 317.0 Bits/s/Hz, were achieved using ZF considering vector/matrix normalizations for number of base station antennas (M) equal to 600 and number of UEs (K) equal to 200 when sum rate is plotted against number of base station antennas in high transmitted power scenarios. Also, when sum rate is plotted against number of users, the system achieves highest sum rate of 433.7 Bits/s/Hz and 433.3 Bits/s/Hz for ZF considering vector/matrix normalizations at M 600, for K equal to 200 for high transmitted power scenarios. The results show that for low transmitted power, MRT outperforms ZF, while ZF gives better performance than MRT for high transmitted power. Generally, the results obtained revealedthat increasing the number of base station antennas can provide near optimal (or best possible) achievable sum rate and mitigate multiuser interference (MUI).