Energy Efficiency and AI-Powered 5G and Beyond Networks

能源效率和人工智能驱动的 5G 及其他网络

• 批准号: 566589-2021
• 负责人: Cheriet, MohamedM
• 金额: $ 29.14万
• 依托单位: École de technologie supérieure
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=753954
• 关键词: Energy; Efficiency; AI; Powered; 5G

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.

信息和通信技术 (ICT) 行业是一个能源密集型且不断增长的行业（每年增长 9%）。最近推出的下一代无线网络应用，即 5G 及以上 (5GB)，极大地加速了许多经济部门中 ICT 服务的使用，为改善我们的生活质量创造了独特的机会。通过大规模部署能够提供高速服务的天线来实现网络致密化，是满足5GB应用低延迟和高带宽需求的关键解决方案。此类网络的设计和管理高度复杂和动态，同时确保更高水平的能源效率，提出了前所未有的技术挑战。在这个项目中，我们将根据下一代无线电应用的新要求和最小化能耗来设计和优化云边缘结构模型。该模型基于人工智能（AI）编排器，能够自动适应不同类别用户的需求，同时具有生态责任感。服务将通过虚拟网络切片向最终用户提供，虚拟网络切片经过端到端优化。该项目还将通过应用深度学习技术提高硬件层面的能源效率，特别是无线电接入方面。该项目的研究结果将在 ENCQOR（通过魁北克省和安大略省研究与创新走廊的网络服务演进）网络上进行评估和量化，该网络用作知识共享平台。这一成果将有可能在 OpenRAN (O-RAN) 联盟中进行标准化，从而在全球范围内使用。 爱立信将利用这一研究成果来提高其战略性5G产品的效率。加拿大环境与气候变化部 (ECCC) 的分析和建模部门 (AMD) 也将从该项目中受益，以加强其针对 ICT 服务的温室气体建模解决方案，并推荐新的环境政策。我们的初步估计显示，该项目每年有可能在加拿大减少约 353,525 吨二氧化碳当量，或蒙特利尔和多伦多之间的 350 万个往返航班。