Proactive User-Centric Networking for Next Generation Wireless Communications

面向下一代无线通信的主动、以用户为中心的网络

基本信息

  • 批准号:
    538476-2018
  • 负责人:
  • 金额:
    $ 13.94万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Collaborative Research and Development Grants
  • 财政年份:
    2021
  • 资助国家:
    加拿大
  • 起止时间:
    2021-01-01 至 2022-12-31
  • 项目状态:
    已结题

项目摘要

The next-generation communication systems are envisioned to revolutionize throughout every aspect of human society by providing anywhere and anytime connectivity to not only mobile communication users, but also almost all physical things. New network architecture, operation, and optimization solutions based on artificial intelligence (AI) technologies represent a worldwide mobile network evolution paradigm, to support the exponential growth of wireless data traffic and new wireless use cases and services. In this project, we will investigate and develop cost-effective network deployment strategies, adaptive network protocols, and proactive resource management mechanisms for next-generation wireless communication systems, leveraging advanced tools in machine learning and big data informatics. The research aims at engineering solutions for flexible deployment of wireless network resources, adaptive to the predicted data traffic and service demands, and for facilitating network self-learning, self-diagnosing, and self-healing, to make the network more responsive and less erroneous, while reducing human involvement in the network management. The realization of network intelligence will be an essential step for developing more efficient, scalable, fully programmable, and automated wireless networks, to achieve agile customized services at low cost. The global market for AI in telecommunication will propel vigorously at a compound annual growth rate of over forty percent. As a result, the race towards developing innovative AI-based next-generation wireless communication systems will undoubtedly be undertaken by research groups worldwide. This project will generate new ideas and techniques that will provide significant benefits to Canadian users, and will foster a vital competitive edge to Canadian ICT industries in the international market place. Five PhD students and five postdoctoral fellows, together with nine co-op students, will participate in the project to develop the latest innovations in wireless communication systems, emerging as expert additions to the Canadian high technology industry labor force.
下一代通信系统不仅为移动通信用户,而且为几乎所有物理事物提供随时随地的连接,从而在人类社会的各个方面发生革命性的变化。基于人工智能(AI)技术的新网络架构、运营和优化解决方案代表了全球移动网络发展模式,以支持无线数据流量和新的无线用例和服务的指数增长。在这个项目中,我们将利用机器学习和大数据信息学的先进工具,研究和开发下一代无线通信系统的经济高效的网络部署策略、自适应网络协议和主动资源管理机制。研究的目的是提供工程解决方案,以灵活地部署无线网络资源,适应预测的数据流量和服务需求,促进网络自我学习、自我诊断和自我修复,使网络更具响应性和更少的错误,同时减少人工参与网络管理。网络智能化的实现将是开发更高效、更可扩展、完全可编程和自动化的无线网络,以低成本实现灵活的定制服务的关键一步。全球电信人工智能市场将以40%以上的复合年增长率蓬勃发展。因此,开发基于人工智能的创新下一代无线通信系统的竞赛无疑将由世界各地的研究小组进行。该项目将产生新的想法和技术,将为加拿大用户带来重大利益,并将促进加拿大信息和通信技术产业在国际市场上的重要竞争优势。五名博士生和五名博士后研究员,以及九名合作社学生,将参与该项目,开发无线通信系统的最新创新,成为加拿大高科技行业劳动力的专家补充。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Shen, Xuemin其他文献

LncRNA IFITM4P promotes immune escape by up-regulating PD-L1 via dual mechanism in oral carcinogenesis.
  • DOI:
    10.1016/j.ymthe.2022.01.003
  • 发表时间:
    2022-04-06
  • 期刊:
  • 影响因子:
    12.4
  • 作者:
    Shi, Linjun;Yang, Yuquan;Li, Mengying;Li, Chenxi;Zhou, Zengtong;Tang, Guoyao;Wu, Lan;Yao, Yilin;Shen, Xuemin;Hou, Zhaoyuan;Jia, Hao
  • 通讯作者:
    Jia, Hao
Deep Reinforcement Learning Based Resource Management for Multi-Access Edge Computing in Vehicular Networks
On Physical Layer Security: Weighted Fractional Fourier Transform Based User Cooperation
论物理层安全:基于加权分数阶傅立叶变换的用户协作
HC-MAC: A hardware-constrained cognitive MAC for efficient spectrum management
A Secure Handshake Scheme with Symptoms-Matching for mHealthcare Social Network
  • DOI:
    10.1007/s11036-010-0274-2
  • 发表时间:
    2011-12-01
  • 期刊:
  • 影响因子:
    3.8
  • 作者:
    Lu, Rongxing;Lin, Xiaodong;Shen, Xuemin
  • 通讯作者:
    Shen, Xuemin

Shen, Xuemin的其他文献

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{{ truncateString('Shen, Xuemin', 18)}}的其他基金

Proactive User-Centric Networking for Next Generation Wireless Communications
面向下一代无线通信的主动、以用户为中心的网络
  • 批准号:
    538476-2018
  • 财政年份:
    2020
  • 资助金额:
    $ 13.94万
  • 项目类别:
    Collaborative Research and Development Grants
Smart Communication Networks with Machine Learning
具有机器学习功能的智能通信网络
  • 批准号:
    RGPIN-2019-04070
  • 财政年份:
    2019
  • 资助金额:
    $ 13.94万
  • 项目类别:
    Discovery Grants Program - Individual
Proactive User-Centric Networking for Next Generation Wireless Communications
面向下一代无线通信的主动、以用户为中心的网络
  • 批准号:
    538476-2018
  • 财政年份:
    2019
  • 资助金额:
    $ 13.94万
  • 项目类别:
    Collaborative Research and Development Grants
Cost-Effective Vehicular Communication Networking
经济高效的车载通信网络
  • 批准号:
    RGPIN-2014-03806
  • 财政年份:
    2018
  • 资助金额:
    $ 13.94万
  • 项目类别:
    Discovery Grants Program - Individual
Cost-Effective Vehicular Communication Networking
经济高效的车载通信网络
  • 批准号:
    RGPIN-2014-03806
  • 财政年份:
    2017
  • 资助金额:
    $ 13.94万
  • 项目类别:
    Discovery Grants Program - Individual
Cost-Effective Vehicular Communication Networking
经济高效的车载通信网络
  • 批准号:
    RGPIN-2014-03806
  • 财政年份:
    2016
  • 资助金额:
    $ 13.94万
  • 项目类别:
    Discovery Grants Program - Individual
Cost-Effective Vehicular Communication Networking
经济高效的车载通信网络
  • 批准号:
    RGPIN-2014-03806
  • 财政年份:
    2015
  • 资助金额:
    $ 13.94万
  • 项目类别:
    Discovery Grants Program - Individual
Cost-Effective Vehicular Communication Networking
经济高效的车载通信网络
  • 批准号:
    RGPIN-2014-03806
  • 财政年份:
    2014
  • 资助金额:
    $ 13.94万
  • 项目类别:
    Discovery Grants Program - Individual

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