ECO-RAN: Energy Consumption Optimization in Radio Access Networks

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A new Danish R&D project will help accelerate green and sustainable transition in mobile telecommunication. The project headed by 2operate in collaboration with mobile infrastructure owner TT-Netværket P/S and Aalborg University, and partly funded by CLEAN a leading Danish cleantech cluster, is focused on building and live testing a fully automated optimization system to minimize the energy usage in mobile radio access networks (RAN).

Energy optimisation and commitments to reduce CO2 emissions as part of a greener company profile has become a hot topic around the world. Energy consumption by base stations is the main contributor to high mobile network operations costs; and in particular Radio Access Networks caters for the majority of base station power consumption.

As RAN costs are expected to increase even further with the launch of 5G and more 4G bands, there is a significant financial gain optimizing energy consumption, but also a growing interest in contributing and investing in energy solutions leading the way to the long-term EU strategy for a climate-neutral economy by 2050.

The project named ECO-RAN will exploit the possibilities of developing a self-learning and self-configuring solution that continuously adapts the most optimal power saving profile for a mobile network without compromising on the performance and network quality for any given time.

By applying AI and machine learning algorithms ECO-RAN will exploit complex business rules and advanced functionality by predicting traffic forecasts for which network elements to be deactivated due to low traffic demand.

As a spin-off to forecasting and prediction the project will also verify how the optimization algorithms may help to identify areas for improvement of quality of service by optimization of neighbouring cells and deployment of new network equipment.