Artificial Intelligence-Defined 5G Radio Access Networks

ABSTRACT Massive multiple-input multiple-output antenna systems, millimeter wave communications, and ultra-dense networks have been widely perceived as the three key enablers that facilitate the development and deployment of 5G systems. This article discusses the intelligent agent that combines sensing, learning, and optimizing to facilitate these enablers. We present a flexible, rapidly deployable, and cross-layer artificial intelligence (AI)-based framework to enable the imminent and future demands on 5G and beyond. We present example AIenabled 5G use cases that accommodate important 5G-specific capabilities and discuss the value of AI for enabling network evolution. I. Introduction Does 5G cellular communications technology in the age of intelligence really look like the Thomas W. Lawson Schooner (the last of the large cargo sailing ships) of modern times? However, concerns are raised whether this is a revolutionary leap from today's wireless communications or a simple piling upof less innovative wireless functionalities. The International TelecommunicationUnion (ITU) classifies 5G into three categories of usage scenarios: enhanced mobile broadband (eMBB),massive machine-type communication (mMTC), and ultra-reliable and low latency communication (URLLC) to account for more diverse services and resourcehungry applications.eMBB is a service category that addresses bandwidth-hungryapplications, such as massive video streaming and virtual/augmented reality (VR/AR). URLLC is a service category that supports latency sensitive services including autonomous driving,drones and the tactile Internet.