Adaptive Intelligent Wireless Networking with Advanced Communication and Machine Learning Techniques
Adaptive Intelligent Wireless Networking with Advanced Communication and Machine Learning Techniques
批准号:
571576-2021
负责人:
Liang, BenB
金额:
$8.64万
依托单位:
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
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31
中文摘要
随着最近5G无线标准化的到来和超5G (B5G)技术的新兴愿景,我们正在见证无线服务和应用的巨大发展。工业物联网、增强现实、移动云计算和移动数据分析等新技术和应用环境正在创造新的服务需求,这些需求强调了无线基础设施的容量和灵活性。未来无线系统的最佳运行需要内置智能,以适应不断变化的干扰模式、容量需求、延迟限制、安全要求和网络规模。在与加拿大爱立信公司的合作中,我们提出了一个新的研究伙伴关系,以开发自适应智能无线网络所需的理论和实际设计。我们的长期目标是了解下一代无线系统的新复杂性和动态如何影响其操作和用户体验,以及如何将人工智能和自主适应集成到这些系统中以管理其复杂性和动态。在这个项目的短期内,我们专注于为5G和B5G网络开发先进的通信和机器学习技术。拟议的合作伙伴关系将使一个独特的合作项目成为可能,该项目将汇集爱立信世界领先的工程专业知识和多伦多大学的大量研究能力。我们将在设计未来的自适应智能无线网络中解决一系列具有挑战性的开放性问题。该项目将有利于爱立信加拿大公司及其在加拿大的技术和业务合作伙伴,改善他们的创新组合、系统设计、客户基础和盈利能力。它还将有助于我们对如何在加拿大建立有效和强大的通信系统的基本理解。
英文摘要
With the recent arrival of 5G wireless standardization and the emerging visions of beyond-5G (B5G) technologies, we are witnessing dramatic developments in wireless services and applications. New technologies and application environments, such as industrial Internet of Things, augmented reality, mobile cloud computing, and mobile data analytics, are creating service demands that stress the capacity and flexibility of the wireless infrastructure. Optimal operation of future wireless systems requires built-in intelligence that adapts to the constantly changing interference patterns, capacity demand, latency constraints, security requirements, and network scale. In collaboration with Ericsson Canada, we propose a new research partnership to develop the needed theories and practical designs of adaptive intelligent wireless networks. Our long-term objective is to understand how the new complexity and dynamics in next-generation wireless systems impact their operation and user experience, and how to integrate artificial intelligence and autonomous adaptation into these systems to manage their complexity and dynamics. In the shorter term of this project, we focus on developing advanced communication and machine learning techniques for 5G and B5G networks.The proposed partnership will enable a unique collaborative project that brings together world-leading engineering expertise from Ericsson and substantial research capacity from the University of Toronto. We will tackle a range of challenging open problems in designing future adaptive intelligent wireless networks. This project will benefit Ericsson Canada and its technology and business partners in Canada, improving their innovation portfolio, system design, customer base, and profitability. It will also contribute to our fundamental understanding on how to build efficient and robust communication systems in Canada.
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会议论文
Dynamic Network Traffic Identification with Scalable and Resilient Machine Learning
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批准号:576922-2022
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项目类别:Alliance Grants
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资助金额:$2.19万
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财政年份:2022
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负责人:Liang, BenB
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依托单位:
国内基金
海外基金
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项目类别:外国学者研究基金项目
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资助金额:--
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批准年份:2024
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负责人:USHARANI HAREESH GOVINDARA JAN
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依托单位: