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Grant: Alliance Grants

École de technologie supérieure

$200,000.00

Energy Efficiency and AI-Powered 5G and Beyond Networks

EF 2024-25

Résumé
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.
Programme
Alliance Grants
Emplacement
Quebec, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
566589-2021
Name nom
Cheriet, Mohamed M
Department département
Génie des systèmes
Organization id
53
Institution établissement
École de technologie supérieure
Province en
Québec
Province fr
Québec
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2021
Award amount
200000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
804
Area of application group en
Information and communication services
Area of application group fr
Services d'information et de télécommunications
Area of application en
Communication systems and services (planning, organization, services)
Area of application fr
Systèmes et services de communications (planification, organisation et services)
Research subject code
2700
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Information technology
Research subject fr
Technologie de l'information
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Energy Efficiency and AI-Powered 5G and Beyond Networks
Keywords
5g; artificial intelligence; cloud computing; energy efficiency; machine learning; network slicing; next generation radio; optimization; o-ran; sustainability
Application summary
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.