Artificial Intelligence-Defined 5G Radio Access Networks
This work addresses network optimization for 5G and beyond systems, but it appears incremental as it builds on existing AI and 5G concepts without introducing a fundamentally new approach.
The paper tackles the challenge of meeting demands on 5G and beyond infrastructure by proposing an AI-based framework that combines sensing, learning, understanding, and optimizing in 5G base stations, with example use cases demonstrating its value for network evolution.
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 in 5G base station which combines sensing, learning, understanding 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 infrastructure. We present example AI-enabled 5G use cases that accommodate important 5G-specific capabilities and discuss the value of AI for enabling beyond 5G network evolution.