SpecEES: Collaborative Research: Energy Efficient Dynamic Spectrum Access in Uncoordinated Networks

SpecEES：协作研究：不协调网络中的节能动态频谱接入

• 批准号: 1731237
• 负责人: Biao Chen
• 金额: $ 27.5万
• 依托单位: Syracuse University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-01 至 2021-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1731237&HistoricalAwards=false
• 关键词: SpecEES; Collaborative; Research; Energy; Efficient

With its focus on energy efficient dynamic spectrum access where the users are treated as equals and there is minimal coordination across the users, this project addresses challenges for enabling next-generation wireless communications and networking in a dynamic spectrum environment. The results from the project should greatly enhance access to broadband wireless services in traditionally under-serviced communities. The spectrum-sensing and spectrum-sharing techniques developed should prove to be equally applicable in a slew of applications involving energy-constrained ad hoc networks such as those encountered in disaster relief operations and in a variety of applications relevant to national security. The involvement of undergraduate students in this project, especially in software radio experiment, is expected to foster their long-term interest in Science, Technology, Engineering and Math (STEM)-related fields.This research project is focused on both spectral efficiency and energy efficiency for a class of dynamic spectrum access applications that have been much less well studied: an uncoordinated wide-band system where the users are treated as equals, i.e., there is no primary/secondary distinction. The project will develop the spectrum management framework as well as enabling technologies for such applications, ranging from multi-channel spectrum sensing using quickest change detection to novel spectrum access schemes for spectral/energy efficient and fair spectrum usage in the absence of user coordination. Experimental studies are an integral part of the proposed research, and the project leverages existing software radio capabilities developed at Syracuse University. This study of spectrum access with equally privileged users without coordination also fills an important gap in dynamic spectrum access. Given the generality of the models considered, this research can be expected to make fundamental contributions to the theories of quickest change detection and random access.

该项目专注于节能的动态频谱接入，其中用户被平等对待，用户之间的协调最小，该项目解决了在动态频谱环境中实现下一代无线通信和网络的挑战。该项目的成果将大大提高传统上服务不足的社区获得宽带无线服务的机会。开发的频谱感知和频谱共享技术应被证明同样适用于一系列涉及能量受限的自组织网络的应用，例如在救灾行动中遇到的应用和与国家安全相关的各种应用。本科生的参与，特别是在软件无线电实验，预计将培养他们对科学，技术，工程和数学（STEM）相关领域的长期兴趣。该研究项目的重点是频谱效率和能源效率的一类动态频谱接入应用，一直没有得到很好的研究：不协调的宽带系统，其中用户被平等对待，即，没有主要/次要的区别。该项目将开发频谱管理框架以及这些应用的支持技术，从使用最快变化检测的多信道频谱感知到在没有用户协调的情况下实现频谱/能源效率和公平频谱使用的新型频谱接入方案。实验研究是拟议研究的一个组成部分，该项目利用了锡拉丘兹大学开发的现有软件无线电功能。本研究的频谱接入与同等特权的用户没有协调，也填补了一个重要的空白，动态频谱接入。考虑到模型的一般性，本研究有望对最快变化检测和随机访问理论做出基本贡献。

项目成果

Asymptotically Optimal One- and Two-Sample Testing With Kernels

• DOI: 10.1109/tit.2021.3059267
• 发表时间: 2019-08
• 期刊: IEEE Transactions on Information Theory
• 影响因子: 2.5
• 作者: Shengyu Zhu;Biao Chen;Zhitang Chen;Pengfei Yang

On Exponentially Consistency of Linkage-Based Hierarchical Clustering Algorithm Using Kolmogrov-Smirnov Distance

基于Kolmogrov-Smirnov距离的基于链接的层次聚类算法的指数一致性

• DOI: 10.1109/icassp40776.2020.9053708
• 发表时间: 2020
• 期刊: and Signal Processing
• 作者: Wang, Tiexing;Liu, Yang;Chen, Biao
• 通讯作者: Chen, Biao

Robust Kullback-Leibler Divergence and Universal Hypothesis Testing for Continuous Distributions

• DOI: 10.1109/tit.2018.2879057
• 发表时间: 2017-11
• 期刊: IEEE Transactions on Information Theory
• 影响因子: 2.5
• 作者: Pengfei Yang;Biao Chen

K-Medoids Clustering of Data Sequences With Composite Distributions

• DOI: 10.1109/tsp.2019.2901370
• 发表时间: 2018-07
• 期刊: IEEE Transactions on Signal Processing
• 影响因子: 5.4
• 作者: Tiexing Wang;Qunwei Li;Donald J. Bucci;Yingbin Liang;Biao Chen;P. Varshney

Universal Hypothesis Testing with Kernels: Asymptotically Optimal Tests for Goodness of Fit

• 发表时间: 2018-02
• 期刊: ArXiv
• 作者: Shengyu Zhu;Biao Chen;Pengfei Yang;Zhitang Chen