Design and Analysis of Power Consumption Models for Open-RAN Architectures

2025-05-30

AI Summary

This paper addresses the energy-efficiency bottleneck in centralized Open Radio Access Network (O-RAN) architectures by developing a hardware-aware, end-to-end transaction-level power model. It systematically quantifies how deploying baseband processing across different functional splits—Radio Unit (RU), O-DU, and O-CU—affects end-to-end energy consumption. Methodologically, it is the first to rigorously expose how low-fanout constraints drive processing centralization, decomposes power consumption across fronthaul, midhaul, and backhaul data paths, and models the nonlinear trade-off between transmission and processing energy. Key contributions include: (i) empirical validation that centralizing baseband processing toward higher-layer nodes reduces total system power; (ii) discovery that doubling RU fanout increases fronthaul bandwidth and associated transmission energy by over 40%; and (iii) quantification of a nonlinear positive correlation between network sharing depth and transmission energy. The work establishes a reproducible evaluation framework for cross-layer hardware–software co-optimization of O-RAN energy efficiency.

Technology Category

• Machine Learning: Hardware-aware ML
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Distributed Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

The open radio access network (O-RAN) Alliance developed an architecture and specifications for open and disaggregated cellular networks including many elements that are being widely adopted and implemented in both commercial and research networks. In this paper, we develop transaction-based power consumption models of a centralized O-RAN architecture based on commercial hardware and considering the full end-to-end data path from the radio unit to the data center. We focus on recent fanout limitations and early baseband processing requirements related to current implementations of O-RAN and assess the power consumption impact when baseband processing is employed at different centralization points in the network. Additionally, we explore how greater fanout and sharing deeper into the network impact the balance of processing and transmission. Low processing fanout restrictions motivate greater centralization of the processing. At the same time, allowing for more open radio units per open distributed unit will quickly increase the transmission capacity requirements and related energy use.

Problem

• Modeling power consumption in O-RAN architectures with commercial hardware
• Assessing power impact of baseband processing centralization points
• Exploring fanout effects on processing-transmission balance and energy use

Innovation

• Transaction-based power consumption models for O-RAN
• Assessing power impact of baseband processing centralization
• Exploring fanout effects on processing-transmission balance