Optimising multi-user massive MIMO systems through particle filter precoding: a comprehensive performance analysis

Due to globalisation, the demands of network subscribers for different services and the total number of users in the communication industry is growing day to day. To address the demand of these users, the communication industry needed to be upgraded to support the growing demand. This research proposes an optimised particle filter, and nonlinear precoding technique to mitigate this issue. The computational complexity analysis of TH, DPC, and VP and proposed optimised particle filter precoding techniques. Signal-to-noise ratio versus bit error rate, signal-to-noise ratio versus spectral efficiency, the number of transmits antennas versus average sum spectral efficiency, and others were used to analyse the results. The simulation result shows that the proposed optimised particle filter precoding outperforms the existing nonlinear precoding those are, Tomlinson-Harashima (TH), dirty research coding (DPC), and vector perturbation (VP) precoding techniques in average sum spectral efficiency and bit error rate performance on different modulation techniques.