ARTIFICIAL INTELLIGENCE-BASED RADIO ACCESS NETWORK OPTIMIZATION IN 5G

The advent of 5G networks marks a significant milestone in telecommunications, promising unprecedented speed, capacity, and connectivity. However, the complexity of 5G networks poses significant challenges, necessitating advanced solutions for optimization. Artificial Intelligence (AI) has emerged as a potent tool in this regard, offering innovative approaches to enhance Radio Access Network (RAN) performance. This article discusses relevant research and studies on AI-based RAN optimization, organized by key themes: traffic prediction and management, resource allocation and scheduling, interference mitigation and management, and cell deployment and optimization. The three key enablers for the deployment and development of 5G systems are millimeter-wave communications, ultra-dense network, and massive multiple-input multi-output antennas. This article describes the intelligent agent which combines sensing and learning with optimizing in order to facilitate these enablers. The article presents a flexible and rapidly deployable artificial intelligence (AI), cross-layer framework that will enable future and imminent demands for 5G, and beyond. We present AI-enabled use cases for 5G that include important 5G capabilities, and we discuss the value of AI in enabling network evolution.