CAREER: Towards Context-Aware, Self-Organizing Wireless Small Cell Networks

职业:迈向情境感知、自组织无线小型蜂窝网络

基本信息

  • 批准号:
    1253731
  • 负责人:
  • 金额:
    $ 44.32万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2013
  • 资助国家:
    美国
  • 起止时间:
    2013-01-01 至 2014-10-31
  • 项目状态:
    已结题

项目摘要

Providing seamless, high quality wireless service anytime and anywhere requires substantial structural changes in today's macro-cellular networks. One such change, introducing small cell base stations, is seen as a highly promising solution. However, it requires meeting fundamental challenges: 1) nodes? self-organization, 2) network heterogeneity, and 3) high sensitivity of resource allocation to the system parameters. The proposed research addresses these challenges by exploring a dimension that has often been overlooked: the user's context. To achieve this goal, first, machine learning techniques are proposed to extract context from three dimensions: device, geo-location, and social metrics. Then, context-aware resource management schemes are developed by advancing novel techniques from matching theory - a powerful tool from economics and game theory. Subsequently, the learned context is leveraged to devise cooperative small cell models using new tools from coalitional game theory. Comprehensive evaluation is done via testbed implementation and software simulations. The developed analytical tools will lay the foundations of context-aware, self-organizing small cell networks and will impact multiple disciplines such as communications, game theory, and social sciences. The generated results will provide fresh ideas for developing new small cell products. The research is fully integrated into the educational plan via incorporation in new and existing courses as well as training students via mentoring, participation in testbed development, and internships at industrial labs. A developed small cell educational tool will foster this integration via new hands-on activities and demonstrations to the community. Specialized outreach activities will contribute to increasing the participation of minority high school students in science and engineering.
随时随地提供无缝、高质量的无线服务需要对当今的宏蜂窝网络进行重大的结构改变。其中一项变化是引入小型蜂窝基站,这被视为一个非常有希望的解决方案。然而,它需要应对根本的挑战:1)节点?自组织,2)网络异构性,3)资源分配对系统参数的高度敏感性。这项拟议的研究通过探索一个经常被忽视的维度来应对这些挑战:用户的情境。为了实现这一目标,首先,提出了从设备、地理位置和社交指标三个维度提取上下文的机器学习技术。然后,利用匹配理论这一经济学和博弈论的有力工具,提出了上下文感知的资源管理方案。随后,利用从联盟博弈论中学到的新工具,利用所学的背景来设计合作小细胞模型。通过试验台实现和软件仿真进行了综合评估。开发的分析工具将为情景感知、自组织的小蜂窝网络奠定基础,并将影响通信、博弈论和社会科学等多个学科。所产生的结果将为开发新的小型蜂窝产品提供新的思路。通过纳入新的和现有的课程,以及通过指导、参与试验台开发和在工业实验室实习来培训学生,这项研究完全融入了教育计划。一个开发的小细胞教育工具将通过新的实践活动和社区示范来促进这种融合。专门的外联活动将有助于增加少数族裔高中生对科学和工程的参与。

项目成果

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Walid Saad其他文献

Joint User Grouping, Version Selection and Bandwidth Allocation for Live Video Multicasting
直播视频组播的联合用户分组、版本选择和带宽分配
  • DOI:
    10.1109/tcomm.2021.3115480
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    8.3
  • 作者:
    Zhilong Zhang;Minyin Zeng;Danpu Liu;Walid Saad;Shuguang Cui;H. Vincent Poor
  • 通讯作者:
    H. Vincent Poor
Sensing Aided Channel Estimation in Wideband Millimeter-Wave MIMO Systems
宽带毫米波 MIMO 系统中的传感辅助信道估计
Investigation of genes that may contribute to disease tropism in Leishmania species
研究可能有助于利什曼原虫物种向病性的基因
  • DOI:
  • 发表时间:
    2007
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Walid Saad
  • 通讯作者:
    Walid Saad
Computer Vision-Based Localization With Visible Light Communications
基于计算机视觉的可见光通信定位
  • DOI:
    10.1109/twc.2021.3109146
  • 发表时间:
    2022-03
  • 期刊:
  • 影响因子:
    10.4
  • 作者:
    Lin Bai;Yang Yang;Mingzhe Chen;Chunyan Feng;Caili Guo;Walid Saad;Shuguang Cui
  • 通讯作者:
    Shuguang Cui
Pilot Optimization and Channel Estimation Scheme for Semantic Communication: A Framework for Edge Intelligence
语义通信的导频优化和信道估​​计方案:边缘智能框架

Walid Saad的其他文献

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{{ truncateString('Walid Saad', 18)}}的其他基金

Collaborative Research: NeTS: JUNO3: Towards an Internet of Federated Digital Twins (IoFDT) for Society 5.0: Fundamentals and Experimentation
合作研究:NetS:JUNO3:迈向社会 5.0 的联合数字孪生 (IoFDT) 互联网:基础知识和实验
  • 批准号:
    2210254
  • 财政年份:
    2022
  • 资助金额:
    $ 44.32万
  • 项目类别:
    Standard Grant
NSF-AoF: Vision-Guided Wireless Communication Systems
NSF-AoF:视觉引导无线通信系统
  • 批准号:
    2225511
  • 财政年份:
    2022
  • 资助金额:
    $ 44.32万
  • 项目类别:
    Standard Grant
Collaborative Research: CNS Core: Small: Hierarchical Federated Learning Over Wireless Edge Networks: Performance Analysis and Optimization
协作研究:CNS 核心:小型:无线边缘网络的分层联邦学习:性能分析和优化
  • 批准号:
    2114267
  • 财政年份:
    2021
  • 资助金额:
    $ 44.32万
  • 项目类别:
    Standard Grant
SII Planning: ARIES: Center for Agile, RelIablE, Scalable Spectrum
SII 规划:ARIES:敏捷、可靠、可扩展频谱中心
  • 批准号:
    2037870
  • 财政年份:
    2020
  • 资助金额:
    $ 44.32万
  • 项目类别:
    Standard Grant
EAGER: Collaborative Research: Modernizing Cities via Smart Garden Alleys with Application in Makassar City
EAGER:合作研究:通过智能花园巷实现城市现代化并在望加锡市应用
  • 批准号:
    2025377
  • 财政年份:
    2020
  • 资助金额:
    $ 44.32万
  • 项目类别:
    Standard Grant
Collaborative Research: CNS Core: Small: Extended Reality over Wireless Cellular Networks: Quality-of-Experience Analysis and Optimization
合作研究:CNS 核心:小型:无线蜂窝网络上的扩展现实:体验质量分析和优化
  • 批准号:
    2007635
  • 财政年份:
    2020
  • 资助金额:
    $ 44.32万
  • 项目类别:
    Standard Grant
CNS Core: Small: Collaborative: Towards Surge-Resilient Hybrid RF/VLC Networks
CNS 核心:小型:协作:迈向抗浪涌混合 RF/VLC 网络
  • 批准号:
    1909372
  • 财政年份:
    2019
  • 资助金额:
    $ 44.32万
  • 项目类别:
    Standard Grant
ICE-T: RC: Towards Highly Reliable Low Latency Broadband (HRLLBB) Communications over Wireless Heterogeneous Networks
ICE-T:RC:通过无线异构网络实现高度可靠的低延迟宽带 (HRLLBB) 通信
  • 批准号:
    1836802
  • 财政年份:
    2018
  • 资助金额:
    $ 44.32万
  • 项目类别:
    Standard Grant
CRISP Type 1/Collaborative Research: A Human-Centered Computational Framework for Urban and Community Design of Resilient Coastal Cities
CRISP 类型 1/协作研究:以人为本的弹性沿海城市城市和社区设计计算框架
  • 批准号:
    1638283
  • 财政年份:
    2017
  • 资助金额:
    $ 44.32万
  • 项目类别:
    Standard Grant
BIGDATA: Collaborative Research: IA: Big Data Analytics for Optimized Planning of Smart, Sustainable, and Connected Communities
BIGDATA:协作研究:IA:用于智能、可持续和互联社区优化规划的大数据分析
  • 批准号:
    1633363
  • 财政年份:
    2016
  • 资助金额:
    $ 44.32万
  • 项目类别:
    Standard Grant

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