A mechanism for 5G MIMO performance optimization and evaluation

MIMO (Multiple-Input Multiple-Output) technology has become a fundamental technique in current wireless communications, both in cellular and Wi-Fi networks. Fifth generation networks (5G) are expected to support extremely high data rates and more reliable services. The performance of 5G networks can be significantly improved with MIMO; yet the integration of optimization algorithms can further improve its performance. The purpose of this paper is to study an optimization technique for Channel State Prediction in a MIMO environment. We will examine a specific interconnection between 5G and optimization algorithms, to produce a feasible Channel State Prediction mechanism. For our experiments, we use a Dataset produced by the DeepMIMO simulator, which sets up all necessary parameters for our experiment. On this dataset we apply the Hungarian Algorithm to optimize the total throughput and based on the results we conclude that such mechanism is feasible and required for the introduction of 5G Networks in day-to-day tasks.