Pratibha Singh, Manish Kumar Dixit, Arun Kumar Singh and Saurabh Dixit*

Department of Electronics and Communications Engineering, Dr. A P J Abdul Kalam Technical University, India

*Corresponding Author: Saurabh Dixit, Department of Electronics and Communications Engineering, Dr. A P J Abdul Kalam Technical University, India.

Received: December 07, 2021; Published: February 22, 2022

Abstract

The road to Fifth Generation (5G) mobile communication standard runs through the Fourth Generation (4G) wireless infrastructure. 5G promises not only a 100x times increase in the peak data rates but also an ultra-reliable low latency (URLL) connections like autonomous cars, remote surgery and Internet of Things (IoT). These remarkable capabilities have been envisaged because of landmark improvements in enabling technologies like carrier aggregation (CA), small cell, massive multiple-input-multiple-output (MIMO), beamforming, carrier network, active antenna system (AAS), full dimension MIMO (FD-MIMO). MIMO technology employs multiple antennas at both the transmit and receive end to boost capacity and augment network efficiency. It has been demonstrated that multi-user MIMO (MU-MIMO) improves Energy Efficiency (EE). Massive MIMO adds a new paradigm to the MIMO communication. The flexibility and scalability of massive MIMO vastly improves the capacity and reliability of the network. The cell size of the network also needs to scalable to blend with the scalability of massive MIMO. To augur well with the scalability of densification of cell size, the role of machine learning algorithms is paramount, as conventional cell size is unable to optimize the efficiency of the network. In this article, the key aspects of massive MIMO are analysed and a model is presented. The dynamics of wireless communications require a scalable and adaptive system. Hence, we have proposed machine learning algorithms which render the network a fair degree of flexibility and scalability.

Keywords: 5G; Energy Efficiency; Machine Learning; Massive MIMO; Network Densification