Towards 6G Technology: Insights into Resource Management for Cloud RAN Deployment

Abstract

Rapid advancements in the development of smart terminals and infrastructure, coupled with a wide range of applications with complex requirements, are creating traffic demands that current networks may not be able to fully handle. Accordingly, the study of 6G networks deserves attention from both industry and academia. Artificial intelligence (AI) has emerged for application in the optimization and design process of new 6G networks. The developmental trend of 6G is towards effective resource management, along with the architectural improvement of the current network and hardware specifications. Cloud RAN (CRAN) is considered one of the major concepts in sixth- and fifth-generation wireless networks, being able to improve latency, capacity, and connectivity to huge numbers of devices. Besides bettering the current set-up in terms of setting the carriers’ network architecture and hardware specifications, among other potential enablers, the developmental trend of 6G also means that there must be effective resource management. As a result, this study covers a thorough analysis of resource management plans in CRAN, optimization, and AI taxonomy, and how AI integration might enhance existing resource management.

Keywords

• sixth generation of wireless network
• cloud radio access networks
• resource management
• machine learning
• federated learning