Network energy efficiency is of critical importance to mobile network operators for economic and ecological reasons. Therefore, reducing network energy consumption is a high priority. Beyond the use of more energy-efficient hardware components, operators increasingly rely on energy-saving features that dynamically adapt network configuration to reduce power consumption during periods of reduced traffic demand. The advent of the O-RAN architecture has brought disaggregation and virtualization, and in order to achieve the highest energy savings gains, we need rigorous measurement, analysis, and modeling of energy consumption at both the component and system levels. However, there remains a lack of publicly-available, quantitative data characterizing the behavior of commercial-grade O-RAN systems.

WINLAB, Open Networking Foundation (ONF), and Open RAN Center for Integration and Deployment (ORCID) have completed a collaboration on energy efficiency testing and modeling of a commercial O-RAN system led by N. K. Shankaranarayanan and Ivan Seskar from WINLAB, Jens Sohn and Akash Gupta from ORCID and Sarat Puthenpura from ONF. We have prepared a white paper (available at http://arxiv.org/abs/2603.04435 ) presenting a detailed energy-efficiency characterization and modeling of a commercial O-RAN system based on comprehensive power and performance measurements, using a network deployment that faithfully replicates a production O-RAN network deployed by a wireless carrier.

The results are drawn from an energy test campaign conducted through a joint collaboration between the ORCID Lab Testing and Evaluation (T&E) Project and the ONF / WINLAB Energy Efficiency Research and Development (R&D) project, both supported by the first round (NOFO-1) of the U.S. National Telecommunications and Information Administration (NTIA) Public Wireless Supply Chain Innovation Fund (PWSCIF) grants. The test environment includes an O-RAN system with an Amazon Web Services-hosted O-CU, a dedicated-server O-DU, and six high-power, multi-band O-RUs representative of commercial macro-cell network deployments.

Our results identify the dominant factors influencing power consumption across the O-RAN stack and quantify energy usage variation under different operational and traffic scenarios. Based on these findings, we provide practical recommendations for lightweight additions to existing equipment test procedures that enable routine energy measurement. These measurements can be used by operators to parameterize power-consumption models, ultimately supporting data-driven energy optimization and more sustainable operation of commercial O-RAN networks.