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AI4Green Project Participation – Verkotan

Have you heard about Artificial Intelligence for Green Networks (AI4Green) project? Among other things, this project aims at more energy efficient radio access and core networks. Read more about AI4Green project and Verkotan’s participation to the project.

By Eero | on 19.07.2022 at 10:09 GMT+0200. | Modified 08.11.2022 at 18:59 GMT+0200.

AI4Green Project Participation – Verkotan


“AI4GREEN is built around the need to build comprehensive, sophisticated and energy-efficient algorithms and solutions at both radio access and core networks, but also on data centers and storage while keeping in mind the emergence of new architectures and the development of smart grids.” – AI4Green

AI4Green project is important since in the recent years there have been exponential growth in mobile traffic, as well as in new mobile services. In the coming years even more objects are expected to be connected to a network. All these things together will make effective modelling, monitoring, and overall control of network traffic difficult, maybe even impossible. For this reason, effective methods are needed to address the challenges of network design, deployment, and management.

The main objective of the AI4Green project is to achieve about 30-40% improvement in end-to-end energy efficiency compared to current networks. Beside the main objective there are other goals that the project aims to achieve.  Read more about the various goals of the project from AI4Green’s website.

Verkotan & AI4Green

Verkotan has participated in AI4Green project as part of the Finnish consortium. Verkotan’s role has been to test AI based methods for energy efficient network planning and analysis tools of measurement data developed by VTT and the University of Oulu. We have also experimented antenna measurements at 60GHz and studied speeding up possibilities of our Near Field to Far Field transformation computing.

Among other things, we have tested innovations produced during the AI4Green project. For example, we have

  • Tested Ray Tracing software developed by the University of Oulu, which can be used in the design of energy efficient radio networks.
  • Done development work to speed up our Near Field to Far Field software. In addition, visualisation methods over measurement results have been developed. 
  • Tested an AI based “clusterability detection” software designed by the Technical Research Centre of Finland (VTT). Testing was done with real 5G antenna measurement data.
  • Performed antenna measurements for a 60GHz 5G radar device (8×4 MIMO) developed by VTT.

Request More Info

If you need more information, Verkotan is always happy to provide more detailed information. We are always ready to make a proposal about how we can help you to verify the performance of your device in the global environment. Visit our Over-the-Air wireless performance testing and RF exposure testing service pages to find more information about our main services.

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