If you are a network operator dealing with skyrocketing electricity bills for base stations — this project developed AI-based procedures that adapt energy consumption based on user patterns to lower overall power use.
AI-Driven Energy Saving Technology for Next-Generation Mobile Networks
Imagine if your phone network could automatically dim its lights and power down parts of its brain when fewer people are using it, without slowing down your connection. This project uses AI to predict when and where data is needed, adjusting the hardware and signals in real-time to stop wasting electricity. It's like having a smart thermostat for the entire cellular grid.
What needed solving
Mobile networks face a conflict between the need for more data capacity and the rising energy costs and environmental impact of powering base stations.
What was built
An AI-driven 'Intelligent Plane' for O-RAN architectures and energy-optimized power amplifier controlling schemes.
Who needs this
Who can put this to work
If you are a hardware vendor dealing with inefficient power amplifiers — this project developed radio-unit controlling schemes and hardware acceleration engines that reduce power consumption compared to generic compute platforms.
If you are a city infrastructure provider dealing with the high cost of installing new base stations for more capacity — this project developed cell-free architectures and Reconfigurable Intelligent Surfaces to distribute radio power more efficiently.
Quick answers
How much does this technology cost to implement?
Based on available project data, specific pricing or implementation costs are not provided.
Can this be scaled to a national network?
The project uses O-RAN as a baseline architecture, which is designed for disaggregation and virtualisation, suggesting it is built for scalable network environments.
Who owns the IP and how is it licensed?
Based on available project data, the licensing terms and IP ownership among the 12 partners are not specified.
How does this integrate with existing 5G hardware?
It leverages the O-RAN standard and its interfaces to allow data and AI models to be exchanged between network functions.
What is the timeline for commercial availability?
The project period runs from 2023-01-01 to 2025-06-30, indicating the research and demonstration phase concludes in mid-2025.
Who built it
The consortium is heavily weighted toward commercial application, with a 75% industry ratio consisting of 9 industrial partners, including 3 SMEs. This strong industrial presence, spanning 6 countries, suggests the project is focused on practical market viability rather than purely academic research.
Contact ACCELLERAN in Belgium for partnership inquiries.
Talk to the team behind this work.
Contact us to connect with the BeGREEN consortium for O-RAN energy efficiency licensing.