An improvement method for massive multiple-input multiple-output (MIMO) system deployment / Lijun Han, Ling Weay Ang and Sellappan Palaniappan

This paper proposes a novel method for deploying massive multiple-input multiple-output (MIMO) systems, an essential component of next-generation wireless networks. The proposed method is designed to address the challenges of deploying MIMO systems in practical scenarios, including the selection of optimal antenna configurations and the need for efficient use of available resources. The method uses advanced machine learning techniques to optimize the deployment of MIMO systems, considering a variety of factors such as channel characteristics, interference, and network topology. The results of the systematic review show that the combination of channel coding technology and antenna diversity technology can significantly increase the capacity of 5G wireless communication systems, provide diversity and coding benefits for wireless transmission, and enable higher frequency band utilization than conventional single antenna systems. The proposed method has been shown to significantly improve the performance of MIMO systems in a variety of scenarios, making it a promising approach for the deployment of MIMO systems in future wireless networks.