Performance Analysis of Optimized Particle Filter Precoding for Multi User Massive MIMO System

Abstract

Due to globalization, 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 in a way to support the growing demand. To address the growing demands of users, higher spectral efficiency, higher data rates (HDR), and higher throughput with low latency are required. However, getting higher spectral efficiency, higher data rates (HDR), and higher throughput with low latency in the transmission medium is a very difficult challenge. Due to the above-mentioned and more factors the current network systems are unable to deliver the required spectral efficiency (SE). Precoding is essential in massive MIMO systems because it optimizes throughput while reducing the impacts of path loss and interference.Massive MIMO systems gain greatly from the precoding approach, but adding more computations, also makes the system's total computations more difficult. With more antennas, the computational complexity rises as well. Therefore, it is more practicable to employ simple and effective precoders for massive MIMO systems. For this issue to be solved different researchers have suggested different linear and non-linear precoding techniques. In this thesis work optimized particle filter non-linear precoding technique is proposed to mitigate this issue. The computational complexity analysis of TH, DPC, and VP and proposed optimized particle filter precoding techniques. From the analysis result optimized particle filter has less execution time than others non-linear precoding techniques. Signal-to-noise ratio versus bit error rate, Signal-to-noise ratio versus spectral efficiency, the number of transmit antennas versus average sum spectral efficiency, and other were used to analyze the results. The simulation result shows that the proposed optimized particle filter precoding outperforms the existing non-linear precoding those are, Tomlinson- Harashima (TH), Dirty Paper Coding (DPC) and Vector Perturbation (VP) precoding techniques in average sum spectral efficiency and bit error rate performance on different modulation techniques.