Performance Analysis and Comparison of Linear Precoding Techniques in Massive MIMO Under Different Fading Channels

Applications in academia and industry are increasingly interested in massive multiple-input–multiple-output (MIMO) technology. When there are many antennas and users, massive MIMO and beamforming techniques help the system operate effectively. Since precoding techniques are very important to minimize interference and sum rate, curiously, analyzing them is more important in the massive antenna system. Most of the research has been done on either matched filter (MF), zero forcing (ZF), or regularized zero forcing (RZF) under different channel conditions. However, works that consider regularized zero forcing (RZF), matched filter (MF), or zero forcing (ZF), under Rician and Rayleigh fading channels for performance analysis and comparison, considering channel state information, number of users, base station antennas, and so on, are the concern of this research. In this research, analysis and performance comparison of linear precoding schemes including regularized zero forcing (RZF), matched filter (MF), and zero forcing (ZF) under Rayleigh fading channels and Rican fading channels with perfect channel state information in massive MIMO have been performed. The computed results from MATLAB software show that as the number of users increases, the spectral efficiency increases for regularized zero forcing (RZF), matched filter (MF), and zero forcing (ZF) linear precoding schemes under Rayleigh and Rician fading channels. The ZF scheme gives better performances at all transmission powers and in an increasing number of base station antennas over RZF and MF in perfect channel state information under Rayleigh and Rician fading channels.