Artificial Intelligence for Green Networks


The exponential growth of mobile traffic, associated with the emergence of new services and the expected explosion of the number of connected objects will make effective monitoring, modelling, and overall control of network traffic difficult if not impossible. Hence, there is a need for powerful methods to solve the challenges faced in network design, deployment, and management.

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.


The main goal of this project is to achieve an improvement of about 30-40% of the end-to-end energy efficiency compared to current networks.

Explore solutions for accelerating computation facilities that empower Artificial Intelligence (AI) in a distributed or centralized architecture.

Solutions for control procedures that optimize networks sites power consumption and power usage depending on a variety of parameters that could be non-correlated.

Proposal of risk-sensitive optimization for performance management that takes into account the end-to-end path.

Proposal of smart, autonomous and parameter-free base stations (BSs) that learn from the environment and activate the relevant energy saving features when needed with the optimized parameter settings.

Definition of Key Performance Indicators (KPIs) for energy efficiency of network slices and adequate measurement and reporting methods.

Definition of AI-based network multi-objective optimization using data (traffic prediction, resource preallocation, self-healing).

Proposal of AI-based network energy efficiency, spectral efficiency assessment and optimization including the point-of-presence, the access and the core networks.

Study new business services not only for enhancing the connectivity but also to build business models based on AI.

Major visible results

Technico-economical sudy of AI solutions for green networking.

Procedures and solutions for data collection.

Demonstrators for improving the radio access network energy efficiency of 5G networks.

Demonstrator for smart energy management.

A set of contribution to be addressed to the standardization bodies (ETSI, 3GPP, ITU-T).