Dynamic Resource Allocation and Energy Optimization in 5G O-RAN: Real-World Insights and Testbed Evaluations

The energy efficiency of 5G Radio Access Networks (RANs) has become a critical area of research due to the growing energy demands of the 5G disaggregated architectures and the increasing environmental concerns surrounding mobile networks. In this paper, we address the fundamental challenge of optimizing energy consumption in Open RAN (O-RAN) 5G networks by dynamically scaling Central Unit (CU) components based on traffic demands. In particular, by leveraging a real-world testbed environment, we empirically analyze the relationship between data volume, architectural configurations, and energy usage. Our study identifies key tuning parameters for energy management and optimization, showcasing the impact of dynamic resource allocation on energy consumption. Experimental results demonstrate that our implementation of a dynamic CU allocation policy can achieve energy savings of up to 60% compared to static configurations, without compromising Quality of Service (QoS).