Towards the deep convergence of communication and computing in RAN: Scenarios, architecture, key technologies, challenges and future trends

Abstract

To accommodate the diversified emerging use cases in 5G, radio access networks (RAN) is required to be more flexible, open, and versatile. It is evolving towards cloudification, intelligence and openness. By embedding computing capabilities within RAN, it helps to transform RAN into a natural cost effective radio edge computing platform, offering great opportunity to further enhance RAN agility for diversified services and improve users' quality of experience (QoE). In this article, a logical architecture enabling deep convergence of communication and computing in RAN is proposed based on O-RAN. The scenarios and potential benefits of sharing RAN computing resources are first analyzed. Then, the requirements, design principles and logical architecture are introduced. Involved key technologies are also discussed, including heterogeneous computing infrastructure, unified computing and communication task modeling, joint communication and computing orchestration and RAN computing data routing. Followed by that, a VR use case is studied to illustrate the superiority of the joint communication and computing optimization. Finally, challenges and future trends are highlighted to provide some insights on the potential future work for researchers in this field.