Radio Access Network (RAN) disaggregation is emerging as a key trend in beyond 5G, as it offers new opportunities for more flexible deployments and intelligent network management. A relevant problem in disaggregated RAN is the functional split selection, which dynamically decides which baseband (BB) functions of a base station are kept close to the radio units and which ones are centralized. In this context, this paper firstly presents an architectural framework for supporting this concept relying on the O-RAN architecture. Then, the paper analyzes how the functional split can be optimized to adapt to the different load conditions while minimizing energy costs.
Resource Management in RIS-Assisted Rate Splitting Multiple Access for Next Generation (xG) Wireless Communications: Models, State-of-the-Art, and Future Directions
LLM-Empowered Agentic AI for QoE-Aware Network Slicing Management in Industrial IoT
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications（北京邮电大学网络与交换技术国家重点实验室）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算与数据科学学院）；Department of Electrical and Electronic Engineering, University of Hong Kong（香港大学电子电气工程学系）；School of Electrical and Computer Engineering, University of Sydney（悉尼大学电气与计算机工程学院）
Towards Scalable O-RAN Resource Management: Graph-Augmented Proximal Policy Optimization
Nantes University, École Centrale Nantes, IMT Atlantique, CNRS, INRIA, LS2N, UMR 6004, Nantes, France（南特大学、中央理工学院南特校区、IMT阿蒂安特、CNRS、INRIA、LS2N、UMR 6004、法国南特）；SnT, SIGCOM, University of Luxembourg, Luxembourg（SnT、SIGCOM、卢森堡大学、卢森堡）
