Trade body Next Generation Mobile Networks Alliance (NGMN) outlined a roadmap for MNOs and the wider telecoms industry to reduce energy consumption across networks, highlighting the role AI and machine learning (ML) can play to boost efficiency in the sector.

In its latest publication dubbed Green Future Networks: A Roadmap to Energy Efficient Networks, NGMN outlined 16 different energy savings techniques and solutions, currently used or under development in the industry. The “comprehensive” roadmap aims to enhance energy saving methods for MNOs, and each of its techniques are claimed to be supported by real-world data.

NGMN argues energy consumption can be reduced through process optimisation, engineering and operational improvements, as well as the deployment of the latest technologies. Its recommendations are part of a wider Green Future Networks programme, addressing short-term solutions that MNOs could deploy.

Coming to AI, the trade body explained the use of the technology and ML can be used to better plan and manage networks, as well as predict traffic, and represents a key new addition to the identified solutions.

As well as helping to estimate energy consumption, AI algorithms can also apparently help MNOs make improved energy saving decisions and highlights the importance of identifying low energy efficiency sites.

Laurent Leboucher, Orange Group CTO and NGMN board member, said finding ways to reduce energy consumption and meet climate goals “is of utmost importance to the industry”.

“The solutions span multiple domains: better network planning and engineering, imporoved network management, the application of AI and ML and the development and use of new technologies.”

In addition to the energy saving tips, NGMN also called on MNOs to share wireless and RAN infrastructure and utilise network resources to limit energy consumption and carbon emissions.

Standards development bodies were also urged to enhance interworking between networks and energy supplies as a method to reduce carbon footprints and costs, while maintaining service availability.