Energy Efficiency and AI-Powered 5G and Beyond Networks

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The information and communication technologies (ICT) sector is an energy intensive and growing sector (with an increase of 9% annually). Recently introduced applications of the next-generation radio networks, namely 5G-and-beyond (5GB), have dramatically accelerated the use of ICT services in many economic sectors, creating a unique opportunity to improve our quality of life. Network densification through the massive deployment of antennas capable of offering high-speed services is the key solution to meeting the low latency and high bandwidth requirements of 5GB applications. The design and management of such networks, which are highly complex and dynamic while ensuring a higher level of energy efficiency, pose unprecedented technical challenges. In this project, we will design and optimize a cloud-edge fabric model with respect to new requirements of next-generation radio applications and minimized energy consumption. Based on an artificial intelligence (AI) orchestrator, this model will be able to automatically adapt to the requirements of different classes of users while being eco-responsible. Services will be provided to end users through virtual network slices, which are optimized from end to end. This project will also increase energy efficiency at the hardware level, particularly in radio access, by applying deep learning techniques. The findings of the project will be assessed and quantified on the ENCQOR (Evolution of Networked Services through a Corridor in Quebec and Ontario for Research and Innovation) network, used as a platform for knowledge sharing. This outcome will have the potential to be standardized in OpenRAN (O-RAN) alliance and hence be used worldwide. Ericsson will use this research results to improve the efficiency of their strategic 5G products. The Analysis and Modelling Division (AMD) of the Environment and Climate Change Canada (ECCC) will also benefit from this project to strengthen their GHG modeling solutions for ICT services, and to recommend new environmental policies. Our preliminary estimation shows the project has the potential to reduce approximately 353,525 tons of CO2e per year in Canada, or 3.5 million round-trip flights between Montreal and Toronto.