Collaborative Research: SWIFT: SMALL: Learning-Efficient Spectrum Access for No-Sensing Devices in Shared Spectrum

合作研究:SWIFT:SMALL:共享频谱中无感知设备的学习高效频谱访问

基本信息

  • 批准号:
    2030026
  • 负责人:
  • 金额:
    $ 22万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-09-15 至 2024-08-31
  • 项目状态:
    已结题

项目摘要

This project develops a novel online learning based framework for distributed low-cost devices to efficiently and effectively access the shared spectrum without spectrum sensing. It specifically focuses on no-sensing devices that do not have the powerful radio-frequency (RF) components to enable wideband spectrum sensing, and addresses the cross-technology spectrum access problem in a decentralized setting. A pertinent application the proposed solution addresses is the dynamic spectrum access of Internet-of-Things (IoT) devices that are deployed in either unlicensed or lightly licensed spectrum, in which the distributed IoT devices need to coexist with other active systems. The no-sensing spectrum access and sharing framework has the potential to revolutionize the operation and management of modern and future wireless networks, considerably enhance the spectrum utilization efficiency, and dramatically alleviate the constantly increasing pressure on the limited radio spectrum. The cross disciplinary nature of the research would naturally translate into case studies and projects in a number of undergraduate and graduate level courses taught by the PIs in areas of communications, machine learning, and networking.This project aims to develop a suite of online learning based spectrum access algorithms for no-sensing devices to coexist with other active systems. The first study focuses on improving the learning efficiency by introducing the best arm identification framework and proposing meta-learning and good channel identification algorithms. The second thrust is devoted to designing spectrum access mechanisms that can seamlessly integrate hybrid automatic repeat request (HARQ). Novel algorithms will be designed to learn the optimal sequence of channels for possible retransmissions, and enhanced for fine-grained control that captures the coding level behavior of HARQ. The last thread of investigation considers multi-user multi-technology coexistence and will develop implicit-communication based distributed spectrum access algorithms. Finally, a thorough validation of the algorithms and spectrum access schemes will be performed using a lab testbed and real-world datasets.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.
该项目开发了一种新颖的基于在线学习的框架,用于分布式低成本设备,无需频谱感知即可高效地访问共享频谱。它特别关注那些不具备强大的射频(RF)组件来实现宽带频谱感知的无感知设备,并解决分散环境中的跨技术频谱访问问题。所提出的解决方案解决的一个相关应用是部署在未经许可或轻度许可频谱中的物联网 (IoT) 设备的动态频谱访问,其中分布式物联网设备需要与其他活动系统共存。无感知频谱接入和共享框架有可能彻底改变现代和未来无线网络的运营和管理,显着提高频谱利用效率,并极大地缓解有限无线电频谱不断增加的压力。这项研究的跨学科性质自然会转化为 PI 在通信、机器学习和网络领域教授的许多本科和研究生课程中的案例研究和项目。该项目旨在开发一套基于在线学习的频谱访问算法,使无感设备与其他有源系统共存。第一项研究的重点是通过引入最好的手臂识别框架并提出元学习和良好的通道识别算法来提高学习效率。第二个重点是设计能够无缝集成混合自动重复请求(HARQ)的频谱访问机制。新的算法将被设计来学习可能的重传的最佳信道序列,并增强捕获 HARQ 编码级行为的细粒度控制。最后一个研究线索考虑多用户多技术共存,并将开发基于隐式通信的分布式频谱接入算法。最后,将使用实验室测试台和真实数据集对算法和频谱访问方案进行彻底验证。该奖项反映了 NSF 的法定使命,并通过使用基金会的智力优点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

期刊论文数量(13)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Cascading Bandits with Two-Level Feedback
具有两级反馈的级联 Bandits
Joint User Association and Wireless Scheduling with Smaller Time-Scale Rate Adaptation
联合用户关联和较小时标速率自适应的无线调度
Near-optimal Conservative Exploration in Reinforcement Learning under Episode-wise Constraints
  • DOI:
    10.48550/arxiv.2306.06265
  • 发表时间:
    2023-06
  • 期刊:
  • 影响因子:
    2.4
  • 作者:
    Donghao Li;Ruiquan Huang;Cong Shen;Jing Yang
  • 通讯作者:
    Donghao Li;Ruiquan Huang;Cong Shen;Jing Yang
Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization
  • DOI:
  • 发表时间:
    2021-10
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Chengshuai Shi;Wei Xiong;Cong Shen;Jing Yang
  • 通讯作者:
    Chengshuai Shi;Wei Xiong;Cong Shen;Jing Yang
Reward Teaching for Federated Multi-armed Bandits
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Jing Yang其他文献

Upregulation of flotillin-1 promotes invasion and metastasis by activating TGF-β signaling in nasopharyngeal carcinoma
ïotillin-1 的上调通过激活 TGF-β 信号传导促进鼻咽癌的侵袭和转移
  • DOI:
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Sumei Cao;Yanmei Cui;Huiming Xiao;Miaoqing Mai;Chanjuan Wang;Shanghang Xie;Jing Yang;Shu Wu;Jun Li;Libing Song;Xiang Guo;Chuyong Lin
  • 通讯作者:
    Chuyong Lin
Separation of gallium and aluminum from HCl solution by microemusion
微乳液法从HCl溶液中分离镓和铝
Hydrogen Bonding Character Between the Glycine and BF4
甘氨酸与BF4之间的氢键特征
  • DOI:
    10.1088/1674-0068/22/05/517-522
  • 发表时间:
    2009
  • 期刊:
  • 影响因子:
    1
  • 作者:
    Qin He;Jing Yang;Xiangying Meng
  • 通讯作者:
    Xiangying Meng
Prediction of the crystal size distribution for reactive crystallization of barium carbonate under growth and nucleation mechanisms
生长和成核机制下碳酸钡反应结晶的晶体尺寸分布的预测
  • DOI:
    10.1021/acs.cgd.8b01067
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    3.8
  • 作者:
    Wei Zhang;Fengzhen Zhang;Liping Ma;Jie Yang;Jing Yang;Huaping Xiang
  • 通讯作者:
    Huaping Xiang
A Chinese Han pedigree with Huntington disease mimicking spinocerebellar ataxia
一个患有类似脊髓小脑共济失调的亨廷顿病的中国汉族家系
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    4.4
  • 作者:
    Chengyuan Mao;Yun Su;Huiyun Wang;Liyuan Fan;Huimin Zheng;Tai Wang;Xinwei Li;Shuo Zhang;Zhengwei Hu;Haiyang Luo;Jing Yang;Changhe Shi;Yuming Xu
  • 通讯作者:
    Yuming Xu

Jing Yang的其他文献

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{{ truncateString('Jing Yang', 18)}}的其他基金

Collaborative Research: Optimized Testing Strategies for Fighting Pandemics: Fundamental Limits and Efficient Algorithms
合作研究:抗击流行病的优化测试策略:基本限制和高效算法
  • 批准号:
    2133170
  • 财政年份:
    2022
  • 资助金额:
    $ 22万
  • 项目类别:
    Standard Grant
Collaborative Research: CNS Core: Small: Timely Computing and Learning over Communication Networks
合作研究:CNS 核心:小型:通过通信网络进行及时计算和学习
  • 批准号:
    2114542
  • 财政年份:
    2021
  • 资助金额:
    $ 22万
  • 项目类别:
    Standard Grant
Collaborative Research: MLWiNS: Dino-RL: A Domain Knowledge Enriched Reinforcement Learning Framework for Wireless Network Optimization
合作研究:MLWiNS:Dino-RL:用于无线网络优化的领域知识丰富的强化学习框架
  • 批准号:
    2003131
  • 财政年份:
    2020
  • 资助金额:
    $ 22万
  • 项目类别:
    Standard Grant
CNS Core: Medium: When Next Generation Wireless Networks Meet Machine Learning
CNS 核心:中:当下一代无线网络遇到机器学习时
  • 批准号:
    1956276
  • 财政年份:
    2020
  • 资助金额:
    $ 22万
  • 项目类别:
    Standard Grant
Development of a 3D human in vitro model of pancreatic beta cell health
开发胰腺 β 细胞健康的 3D 人体体外模型
  • 批准号:
    EP/N510099/1
  • 财政年份:
    2017
  • 资助金额:
    $ 22万
  • 项目类别:
    Research Grant
CAREER: When Energy Harvesting Meets "Big Data": Designing Smart Energy Harvesting Wireless Sensor Networks
职业:当能量收集遇到“大数据”:设计智能能量收集无线传感器网络
  • 批准号:
    1650299
  • 财政年份:
    2016
  • 资助金额:
    $ 22万
  • 项目类别:
    Standard Grant
SI2-SSE: Collaborative Research: TrajAnalytics: A Cloud-Based Visual Analytics Software System to Advance Transportation Studies Using Emerging Urban Trajectory Data
SI2-SSE:合作研究:TrajAnalytics:基于云的视觉分析软件系统,利用新兴城市轨迹数据推进交通研究
  • 批准号:
    1535081
  • 财政年份:
    2015
  • 资助金额:
    $ 22万
  • 项目类别:
    Standard Grant
CAREER: When Energy Harvesting Meets "Big Data": Designing Smart Energy Harvesting Wireless Sensor Networks
职业:当能量收集遇到“大数据”:设计智能能量收集无线传感器网络
  • 批准号:
    1454471
  • 财政年份:
    2015
  • 资助金额:
    $ 22万
  • 项目类别:
    Standard Grant
EAGER: Collaborative Research: Visualizing Event Dynamics with Narrative Animation
EAGER:协作研究:用叙事动画可视化事件动态
  • 批准号:
    1352893
  • 财政年份:
    2013
  • 资助金额:
    $ 22万
  • 项目类别:
    Standard Grant
EAGER: Link Free Graph Visualization for Exploring Large Complex Graphs
EAGER:用于探索大型复杂图的链接自由图可视化
  • 批准号:
    0946400
  • 财政年份:
    2009
  • 资助金额:
    $ 22万
  • 项目类别:
    Standard Grant

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合作研究:SWIFT-SAT:确保弹性主动/被动共存的集成测试台 (INTERACT):基于端到端学习的辐射计干扰缓解
  • 批准号:
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合作研究:SWIFT-SAT:DASS:地面通信网络与 100 GHz 以上地球探测卫星系统之间的动态可调频谱共享
  • 批准号:
    2332722
  • 财政年份:
    2024
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    $ 22万
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    Standard Grant
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合作研究:SWIFT-SAT:DASS:地面通信网络与 100 GHz 以上地球探测卫星系统之间的动态可调频谱共享
  • 批准号:
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  • 批准号:
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  • 批准号:
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