Pilotcontamination analysis of Massive MIMO 5G networks based on HetNets weighted scheduling with reinforcement markov encoder model

Abstract

A single base station can simultaneously transmit signals to dozens of mobile users in huge multiple-input multiple-output (MIMO) systems. Researchers have looked into the ideal number of scheduled users for one time slot in order to get the most spectral efficiency (SE). However, we must take the quality of service (QoS) restriction into account in real-world situations. This research propose novel method in PC in massive MIMO 5G networks based on heterogenous networks and deep learning techniques. Here network analysis has been carried out based on HetNets weighted scheduling architecture. then the analysis of pilot contamination is carried out using reinforcement markov encoder model. the experimental analysis has been carried out in terms of sum rate, BER, SINR, spectral efficiency, MSE, Throughput based on network analysis as well as pilot contamination analysis.