Collaborative Research: IMR: MM-1A: MapQ: Mapping Quality of Coverage in Mobile Broadband Networks using Latent Gaussian Process Models

合作研究:IMR:MM-1A:MapQ:使用潜在高斯过程模型映射移动宽带网络的覆盖质量

基本信息

  • 批准号:
    2220388
  • 负责人:
  • 金额:
    $ 18.98万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-10-01 至 2025-09-30
  • 项目状态:
    未结题

项目摘要

About 85% of people in the United States own a smartphone and use it to access the Internet on a regular basis, checking e-mail, using video conferencing applications, communicating with a doctor’s office, or searching for an answer to an urgent question. Sometimes these applications work well, and other times they do not. When they do not work well, the problem is often with the mobile broadband cellular network in the place and at the time of use. Unfortunately no one knows completely and accurately where high quality access exists, nor where regions of limited or no access are present. Accurate maps of coverage quality would enable resources to be directed to areas of greatest need, allow long term tracking of progress on the digital divide, and form a building block for new applications that can adapt to network quality. This project aims to create accurate and complete maps of cellular coverage quality by bringing together multiple measurement datasets and creating guidance for new measurements. This collaborative project brings together experts in statistical modeling, machine learning, and mobile networking from Georgia Institute of Technology and University of California, Santa Barbara. The project has two thrusts. The first focuses on creating mathematical models to predict cellular network quality using latent Gaussian processes in novel ways to combine measurement datasets collected with different methodologies. One set of models will consider how coverage quality varies over geographic space; the other will consider how it varies over time. The second thrust focuses on using the predicted coverage quality maps in two key ways, to use the models to create a Quality of Coverage metric that provides useful information to network users, and to use the models to guide in future measurement campaigns so that regions that are not well understood get prioritized. The United States Federal Government and other government and non-government organizations have allocated funding to broaden Internet access. However, because no one accurately knows where high quality access exists (or does not), it is difficult to target investments to communities of highest need. If successful, this work will be able to inform local, state, and federal governments about where investment should be made to ensure all Americans have access to high quality mobile Internet. As a result, residents of these communities will benefit from the educational, economic, and medical benefits that Internet access enables. https://sites.gatech.edu/mapping-broadband/ - this site will contain products of the project, including datasets, models, algorithms, and publications resulting from the work. The website and repository will be maintained for at least five years, from 2022 to 2027.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
大约85%的美国人拥有智能手机,并定期使用它访问互联网,查看电子邮件,使用视频会议应用程序,与医生办公室沟通,或搜索紧急问题的答案。有时这些应用程序工作得很好,有时则不然。当它们不能很好地工作时,问题往往是在使用的地方和时间的移动的宽带蜂窝网络。不幸的是,没有人完全准确地知道哪里有高质量的接入,也没有人知道哪里有接入有限或没有接入的区域。准确的覆盖质量地图将使资源能够用于最需要的领域,允许长期跟踪数字鸿沟的进展情况,并为能够适应网络质量的新应用程序提供基础。该项目旨在通过汇集多个测量数据集并为新的测量提供指导,创建准确和完整的蜂窝覆盖质量地图。这个合作项目汇集了来自格鲁吉亚理工学院和加州大学圣巴巴拉的统计建模、机器学习和移动的网络方面的专家。该项目有两个重点。第一个重点是创建数学模型,以预测蜂窝网络质量使用潜在的高斯过程中的新方法,以联合收割机测量数据集收集与不同的方法。一组模型将考虑覆盖质量如何随地理空间变化;另一组将考虑它如何随时间变化。第二个重点是以两种关键方式使用预测的覆盖质量地图,使用模型来创建覆盖质量度量,为网络用户提供有用的信息,并使用模型来指导未来的测量活动,以便不太了解的区域优先考虑。美国联邦政府和其他政府及非政府组织已拨款扩大因特网的使用。然而,由于没有人确切地知道哪里存在(或不存在)高质量的接入,因此很难将投资针对最需要的社区。如果成功,这项工作将能够告知地方,州和联邦政府应该在哪里投资,以确保所有美国人都能获得高质量的移动的互联网。因此,这些社区的居民将受益于互联网接入带来的教育、经济和医疗方面的好处。 https://sites.gatech.edu/mapping-broadband/该网站将包含项目的产品,包括数据集,模型,算法和工作产生的出版物。该网站和存储库将至少维护五年,从2022年到2027年。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

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Elizabeth Belding其他文献

A practical framework for 802.11 MIMO rate adaptation
  • DOI:
    10.1016/j.comnet.2015.03.015
  • 发表时间:
    2015-06-04
  • 期刊:
  • 影响因子:
  • 作者:
    Lara Deek;Eduard Garcia-Villegas;Elizabeth Belding;Sung-Ju Lee;Kevin Almeroth
  • 通讯作者:
    Kevin Almeroth
A user-driven free speech application for anonymous and verified online, public group discourse
用户驱动的自由言论应用程序,用于匿名和经过验证的在线公共团体讨论
  • DOI:
    10.1186/s13174-018-0093-4
  • 发表时间:
    2018
  • 期刊:
  • 影响因子:
    3.5
  • 作者:
    Michael Nekrasov;Danny Iland;Miriam J. Metzger;Lisa Parks;Elizabeth Belding
  • 通讯作者:
    Elizabeth Belding

Elizabeth Belding的其他文献

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{{ truncateString('Elizabeth Belding', 18)}}的其他基金

HSI Implementation and Evaluation Project: Integrated Networking, Scholarship, and Peer Mentoring of Freshmen Engineers for Increased Academic Success and Graduation Rates
HSI 实施和评估项目:新生工程师的综合网络、奖学金和同伴指导,以提高学业成功率和毕业率
  • 批准号:
    2345377
  • 财政年份:
    2024
  • 资助金额:
    $ 18.98万
  • 项目类别:
    Standard Grant
IMR: MM-1A: ADDRESS: Augment, Denoise and Debias cRowdsourced mEasurements for Statistical Synthesis of internet access characterization
IMR:MM-1A:地址:互联网接入特征统计综合的增强、降噪和去偏众包测量
  • 批准号:
    2220417
  • 财政年份:
    2022
  • 资助金额:
    $ 18.98万
  • 项目类别:
    Standard Grant
RAPID: Neighborhood-level U.S. Internet Accessibility Assessment through Dataset Aggregation and Statistical and Predictive Modeling
RAPID:通过数据集聚合以及统计和预测建模进行美国社区级互联网可访问性评估
  • 批准号:
    2033946
  • 财政年份:
    2020
  • 资助金额:
    $ 18.98万
  • 项目类别:
    Standard Grant
SCC: PuebloConnect: Expanding Internet Access and Content Relevance in Tribal Communities
SCC:PuebloConnect:扩大部落社区的互联网访问和内容相关性
  • 批准号:
    1831698
  • 财政年份:
    2018
  • 资助金额:
    $ 18.98万
  • 项目类别:
    Standard Grant
NSF Student Travel Grant for 2017 ACM Workshop on Mobile Computing Systems and Applications (HotMobile)
NSF 学生旅费补助金用于 2017 年 ACM 移动计算系统和应用研讨会 (HotMobile)
  • 批准号:
    1722536
  • 财政年份:
    2017
  • 资助金额:
    $ 18.98万
  • 项目类别:
    Standard Grant
EAGER: Collaborative Research: A Multi-Network Architecture for Expanding Internet Participation and Community-Building on Native American Reservations
EAGER:协作研究:用于扩大美洲原住民保留地的互联网参与和社区建设的多网络架构
  • 批准号:
    1637265
  • 财政年份:
    2016
  • 资助金额:
    $ 18.98万
  • 项目类别:
    Standard Grant
NeTS: Medium: Collaborative Research: TribalNet: Expanding Internet Accessibility and Participation on Native American Reservations
NeTS:媒介:协作研究:TribalNet:扩大美洲原住民保留地的互联网可访问性和参与度
  • 批准号:
    1563436
  • 财政年份:
    2016
  • 资助金额:
    $ 18.98万
  • 项目类别:
    Standard Grant
NetSE:Medium:VillageNet: Intelligent Wireless Networks for Rural Areas
NetSE:Medium:VillageNet:农村地区智能无线网络
  • 批准号:
    1064821
  • 财政年份:
    2011
  • 资助金额:
    $ 18.98万
  • 项目类别:
    Standard Grant
GOALI: Intelligent Channel Management in 802.11n Networks
GOALI:802.11n 网络中的智能通道管理
  • 批准号:
    1032981
  • 财政年份:
    2010
  • 资助金额:
    $ 18.98万
  • 项目类别:
    Standard Grant
CRI: Collaborative Research: WORKIT: A Universal Wireless Open Research KIT
CRI:协作研究:WORKIT:通用无线开放研究套件
  • 批准号:
    0454329
  • 财政年份:
    2005
  • 资助金额:
    $ 18.98万
  • 项目类别:
    Continuing Grant

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