Collaborative Research: Multi-Input Multi-Output (MIMO) Aware Cooperative Dynamic Spectrum Access

协作研究:多输入多输出(MIMO)感知协作动态频谱接入

基本信息

项目摘要

The objective of this project is to develop a Multi-Input Multi-Output (MIMO) aware cooperative Dynamic Spectrum Access framework, termed McDysa, which enables multiple primary users and multiple secondary users to cooperate in dynamic spectrum sharing. By exploiting the underlying cognitive radio and MIMO techniques, McDysa is expected to achieve significant gains on spectrum efficiency while providing substantial enhancements to physical layer security as well. The technical merit and impact of this project are both fundamental and applied, including new problems, algorithms, and methodologies. The McDysa architecture considers multiple simultaneous primary- and secondary-user transmissions by exploiting MIMO techniques. A number of problems studied in the project may foster the development of novel techniques and methodologies toward MIMO-aware dynamic spectrum access. Examples include the novel problem of MIMO-enabled relay selection, insightful analysis of McDysa transmission capacity, and the consideration of secrecy capacity enhancement via friendly jamming. As many of the methodologies in McDysa leverage knowledge from other domains such as game theory, the research outcomes of this project may also motivate advancements of the corresponding domain-specific research. The broader impact of this project also extends to education. The project contains a detailed plan for disseminating the research results and for outreaching to students from underrepresented groups via various channels established in the past years. It also includes a plan for integrating undergraduate and graduate education with research through curriculum development and student involvement. Specifically, the testbed validation of McDysa can offer undergraduate and graduate students valuable hands-on experience, and is therefore an excellent educational vehicle to broaden the participation of students, especially those from underrepresented groups, in computer science research. Technically, this project defines novel problems and develops new performance-optimization techniques in the following three thrusts that are critical to MIMO-aware cooperative dynamic spectrum access: (i) Relay selection and resource sharing, which focuses on developing novel centralized and distributed relay selection and resource management algorithms based on game theory to enable multiple MIMO-empowered primary and secondary users to cooperate for joint optimization. (ii) Achievable transmission capacity analysis, which investigates the achievable transmission capacity of secondary networks and secrecy capacity of the primary network, and the usage of beamforming optimization to maximize such capacities. (iii) Secrecy capacity enhancement, which studies the usage of two friendly jamming mechanisms, cooperative jamming and artificial interference, in the design of novel beamforming techniques and interference signals for nulling the interference at the receivers, in order to enhance the secrecy capacity of the primary network. Besides the three thrusts, this project also includes the design and validation of a testbed that supports a number of experimental tasks for validating the effectiveness of approaches and methodologies developed in the project. This project also has strong societal impact as the rigorously proven solutions developed in the project can serve as guidelines and backbone for promoting and establishing more flexible spectrum access policies and regulations.
该项目的目标是开发一个多输入多输出(MIMO)感知的协作动态频谱接入框架,称为McDysa,它使多个主用户和多个次用户在动态频谱共享中进行协作。通过利用底层的认知无线电和MIMO技术,McDysa预计将在频谱效率上实现显著提高,同时还将大幅增强物理层安全性。这个项目的技术价值和影响是基础性的和应用性的,包括新的问题,算法和方法。McDysa架构通过利用MIMO技术来考虑多个同时的主用户和次用户传输。本计画所研究的许多问题可能会促进MIMO动态频谱存取的新技术与方法的发展。例子包括MIMO使能中继选择的新问题,McDysa传输容量的深入分析,并考虑通过友好干扰的保密能力增强。 由于McDysa中的许多方法利用了博弈论等其他领域的知识,因此该项目的研究成果也可能推动相应领域特定研究的进步。该项目的更广泛影响还延伸到教育领域。该项目载有一项详细计划,通过过去几年建立的各种渠道,传播研究成果,并向代表性不足群体的学生进行外展。它还包括一项通过课程开发和学生参与将本科生和研究生教育与研究相结合的计划。具体来说,McDysa的测试平台验证可以为本科生和研究生提供宝贵的实践经验,因此是一个很好的教育工具,以扩大学生的参与,特别是那些来自代表性不足的群体,在计算机科学研究。 从技术上讲,该项目定义了新的问题,并在以下三个方面开发了新的性能优化技术,这三个方面对MIMO感知的合作动态频谱接入至关重要:(i)中继选择和资源共享,其重点是基于博弈论开发新颖的集中式和分布式中继选择和资源管理算法,以使多个MIMO授权的主用户和次用户能够合作进行联合优化。(ii)可扩展传输容量分析,其调查次级网络的可实现传输容量和初级网络的保密容量,以及使用波束成形优化来最大化这些容量。(iii)保密容量增强,研究在设计新的波束形成技术和干扰信号时使用两种友好的干扰机制,即合作干扰和人工干扰,以在接收机处使干扰为零,从而增强主网络的保密容量。除了这三个重点之外,该项目还包括一个测试平台的设计和验证,该平台支持一些实验任务,以验证项目中开发的方法和方法的有效性。该项目还具有强大的社会影响力,因为在该项目中开发的经过严格验证的解决方案可以作为促进和建立更灵活的频谱接入政策和法规的指导方针和支柱。

项目成果

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Dechang Chen其他文献

Oblique Derivative Problems for Nonlinear Parabolic Equations of Second Order in High Dimensional Domains
高维域二阶非线性抛物型方程的斜导问题
  • DOI:
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    0
  • 作者:
    G. Wen;Yan;Dechang Chen
  • 通讯作者:
    Dechang Chen
An integrated system for class prediction using gene expression profiling
使用基因表达谱进行类别预测的集成系统
An Algorithm That Integrates Any Combination and Number of Prognostic Factors and Calculates Survival: A Lung Cancer Demonstration
  • DOI:
    10.1378/chest.10560
  • 发表时间:
    2010-10-01
  • 期刊:
  • 影响因子:
  • 作者:
    Donald E. Henson;Arnold M. Schwartz;Dechang Chen;Roshni Patel;Xiuzhen Cheng;Joyce Hsiao
  • 通讯作者:
    Joyce Hsiao
Correction: Class Prediction and Feature Selection with Linear Optimization for Metagenomic Count Data
修正:宏基因组计数数据的类别预测和特征选择与线性优化
  • DOI:
  • 发表时间:
    2014
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Zhenqiu Liu;Dechang Chen;Li Sheng;Amy Y. Liu
  • 通讯作者:
    Amy Y. Liu
Using Machine Learning to Expand the Ann Arbor Staging System for Hodgkin and Non-Hodgkin Lymphoma
使用机器学习扩展安娜堡霍奇金和非霍奇金淋巴瘤分期系统
  • DOI:
    10.3390/biomedinformatics3030035
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Huan Wang;Zhenqiu Liu;Julie Yang;Li Sheng;Dechang Chen
  • 通讯作者:
    Dechang Chen

Dechang Chen的其他文献

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{{ truncateString('Dechang Chen', 18)}}的其他基金

NeTS: Medium: Collaborative Research: Opportunistic and Compressive Sensing in Wireless Sensor Networks
NeTS:媒介:协作研究:无线传感器网络中的机会和压缩感知
  • 批准号:
    0964060
  • 财政年份:
    2010
  • 资助金额:
    $ 14.94万
  • 项目类别:
    Continuing Grant
Collaborative Research: NEDG: Throughput Optimization in Wireless Mesh Networks
合作研究:NEDG:无线网状网络的吞吐量优化
  • 批准号:
    0831939
  • 财政年份:
    2008
  • 资助金额:
    $ 14.94万
  • 项目类别:
    Standard Grant
Numerical Computing and Optimization in Developing Cancer Prognostic Systems
开发癌症预后系统中的数值计算和优化
  • 批准号:
    0729080
  • 财政年份:
    2007
  • 资助金额:
    $ 14.94万
  • 项目类别:
    Standard Grant
SD Class Prediction by Gene Expression Profiles
通过基因表达谱进行 SD 类别预测
  • 批准号:
    0311252
  • 财政年份:
    2003
  • 资助金额:
    $ 14.94万
  • 项目类别:
    Standard Grant

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