5G New Radio: Dynamic Time Division Duplex Radio Resource Management Approaches

Abstract

The Internet of Everything is currently in demand and has burdened the network tremendously. Accommodating this exponential increase in demand will require improved Radio Resource Management technology. This problem can be curbed with higher spectrum bands, reevaluation of Time Division Duplex, deployment of Software Defined Network, and Network Function Virtualization into 5G New Radio (NR) network. Therefore, this work aims to provide an in-depth survey on the recent resource management schemes that can be proposed for 5G NR enhancement by exploiting both rule-based algorithms and machine learning methods. Radio resource management consists of managing user allocation, the antenna transmission power, bandwidth, and modulation scheme. Therefore, in this paper, three categories of radio resource management technologies are introduced: resource allocation, energy efficiency, and interference management. The discussion revolves around their potentials and contributions as well as challenges faced to produce efficient 5G resource management schemes.

Keywords

• 5G
• resource management
• machine learning
• wireless communication