Collaborative Research: Energy-Efficient Heterogeneous Network Virtualization with Spectrum-Power Trading

合作研究：具有频谱电力交易的节能异构网络虚拟化

• 批准号: 1731424
• 负责人: Zhu Han
• 金额: $ 20万
• 依托单位: University of Houston
• 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: 2017-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1731424&HistoricalAwards=false
• 关键词: Collaborative; Research; Energy; Efficient; Heterogeneous

To accommodate the significant growth in wireless traffic and services, it is beneficial and important to decouple wireless network infrastructure and type of the services, resulting in network virtualization where different types of services can share the same infrastructure and network utilization. Moreover, wireless network virtualization makes it easy to migrate spectrum power trading to balance traffic flow in heterogeneous networks and effectively reduce network energy consumption. Those facts motivate us to investigate the spectrum-power trading mechanism under the heterogeneous network virtualization frameworks. The proposed research will improve design methodology by providing new perspectives and solution concepts. The unique angles of the proposed cross-layer approaches integrate interdisciplinary and transformative concepts in different areas, including economics, decision theory, optimization, and social science. The results will be publicly available through publications and open source software release, to facilitate technology dissemination. The research can also significantly boost the quality of undergraduate and graduate programs, through curriculum development and engaging students in related research. The outreach activities will encourage high school students, especially female and minority students, to pursue science and engineering careers.With network virtualization, wireless equipment, such as base stations (BSs), might be controlled by individuals instead of by one or a few service providers. As a result, network economy, especially for spectrum-power trading, has to be carefully investigated to implement network virtualization. In this cross disciplinary proposal, the intellectual merits include: 1) The network virtualization framework will be constructed to facilitate the spectrum-power trading. The separation of physical and virtual networks requires the game theoretical analysis due to different interests for different scenarios. 2) The key challenge is the trading strategy, i.e., how to efficiently allocate physical resources to different virtual wireless networks, including BS association, spectrum and power allocation. The problems will be approached through exploiting its special structures and making use of fractional programming theory, duality methods of mixed integer programming, and graph theoretic tools to find the good solutions with low-complexity. 3) The device-to-device (D2D) communications can provide services with low latency and reduced power consumption. Spectrum and power trading will be performed in virtualized D2D networks for further performance improvement. 4) To facilitate network virtualization, spectrum-power trading game theoretical approaches, such as auction theory and contract theory approaches, will be studied. Furthermore, big data scale optimization algorithms will be developed to conduct parallel computing.

为了适应无线业务和服务的显著增长，将无线网络基础设施和服务类型解耦是有益的并且重要的，从而导致网络虚拟化，其中不同类型的服务可以共享相同的基础设施和网络利用率。此外，无线网络虚拟化使得频谱功率交易易于迁移，以平衡异构网络中的流量，有效降低网络能耗。这些事实促使我们研究异构网络虚拟化框架下的频谱功率交易机制。建议的研究将通过提供新的视角和解决方案概念来改进设计方法。所提出的跨层方法的独特角度整合了不同领域的跨学科和变革性概念，包括经济学，决策理论，优化和社会科学。研究结果将通过出版物和开放源码软件的发行向公众公布，以促进技术传播。这项研究还可以通过课程开发和让学生参与相关研究，显着提高本科和研究生课程的质量。外展活动将鼓励高中生，特别是女生和少数民族学生，追求科学和工程事业。随着网络虚拟化，无线设备，如基站（BS），可能由个人控制，而不是由一个或几个服务提供商。因此，网络经济，特别是频谱功率交易，必须仔细研究，以实现网络虚拟化。在这个跨学科的建议，智力的优点包括：1）网络虚拟化框架将被构建，以促进频谱功率交易。物理网络与虚拟网络的分离需要进行博弈论分析，因为不同场景的利益不同。2)关键的挑战是贸易战略，即，如何有效地将物理资源分配给不同的虚拟无线网络，包括BS关联、频谱和功率分配。本文将利用该问题的特殊结构，利用分式规划理论、混合整数规划的对偶方法和图论工具，以较低的复杂度寻求问题的最优解。3)设备到设备（D2D）通信可以提供具有低延迟和降低的功耗的服务。频谱和功率交易将在虚拟化D2D网络中执行，以进一步提高性能。4)为了促进网络虚拟化，将研究频谱功率交易博弈理论方法，例如拍卖理论和契约理论方法。此外，还将开发大数据规模优化算法来进行并行计算。

项目成果

Wireless Resource Scheduling in Virtualized Radio Access Networks Using Stochastic Learning

• DOI: 10.1109/tmc.2017.2742949
• 发表时间: 2018-04
• 期刊: IEEE Transactions on Mobile Computing
• 影响因子: 7.9
• 作者: Xianfu Chen;Zhu Han;Honggang Zhang;G. Xue;Yong Xiao;M. Bennis

Energy Efficient Optimization for Wireless Virtualized Small Cell Networks With Large-Scale Multiple Antenna

• DOI: 10.1109/tcomm.2017.2666182
• 发表时间: 2017-02
• 期刊: IEEE Transactions on Communications
• 影响因子: 8.3
• 作者: Zheng Chang;Zhu Han;T. Ristaniemi

Parallel and Distributed Resource Allocation With Minimum Traffic Disruption for Network Virtualization

• DOI: 10.1109/tcomm.2017.2650994
• 发表时间: 2017-01
• 期刊: IEEE Transactions on Communications
• 影响因子: 8.3
• 作者: H. Nguyen;Yanru Zhang;Zheng Chang;Zhu Han