Performance of Linear Precoding Techniques in Massive MIMO System Over Fading Channels

Abstract

Massive Multiple Input Multiple Output System (MIMO) aims in the 5G communications networks to increase performance and spectral efficiency. However, Multi-User Interference (MUI) is created when a User Terminal (UT) is found near another cellular network User Terminal (UT). In this research, non-linear precoding can be used to address this problem. However, non-linear precoding has higher implementation complexity than linear precoding techniques. Therefore, this project proposes to apply linear precoding techniques as it has a lower computational complexity. Linear precoding is more straightforward, and it has nearly optimal performance. This study simulates the mathematical model linear precoding techniques for a massive MIMO system using MATLAB. Then, to compare the performance of linear precoding in terms of bit error rate (BER) and Sum rate over Rayleigh fading channel and Rician fading channel are evaluated. Zero Forcing and Regularized Zero Forcing precoding technique performs better than Matched Filter in both Rayleigh fading channel and Rician fading channel. Performance of massive MIMO downlink channel over Rayleigh fading channel is outperforming than Rician fading channel.