A Fundamental Study on Energy Efficient Wireless Communication Networks: Modeling, Algorithms, and Applications

节能无线通信网络的基础研究:建模、算法和应用

基本信息

  • 批准号:
    1610874
  • 负责人:
  • 金额:
    $ 38万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2016
  • 资助国家:
    美国
  • 起止时间:
    2016-08-01 至 2020-07-31
  • 项目状态:
    已结题

项目摘要

The rapid development and wide deployment of wireless networks incur a fast escalation of energy demand, which eagerly calls for energy-efficient networking techniques. At the same time, wireless networks are evolving into complex forms with multi-dimensional resources including communication link, radio, channel, antenna, and transmit power; algorithms with low complexity for energy efficiency optimization are highly demanded. This project targets at a fundamental study on energy-efficient wireless networking through establishment of a uniformed analytical framework, development of efficient and low-complexity algorithms, and application of the generic studies into important scenarios in the fifth generation (5G) cellular systems. This interdisciplinary research will not only provide various training projects to undergraduate and graduate studies, but also inspire students to pursue high-quality research with a creative, open-minded, and cross-disciplinary perspective. This project is going to demonstrate that a uniformed multidimensional optimization framework for energy efficiency optimization can be constructed by the principle of scheduling proper transmission patterns, which are defined by the interference model of the network. With such a uniformed optimization model, low-complexity decomposition techniques are fundamentally related to a maximum weighted transmission pattern (MWTP) problem, under a physical interference model according to the signal-to-interference-plus-noise ratio. Approximation algorithms and associated performance analysis for the MWTP problem (which is NP-hard in general) are critical research issues to be studied. Distributed algorithms for solving the energy efficiency optimization problem further involves decomposition with multi-objective optimization, and innovative Lyapunov function design and associated stability analysis under the physical interference model, which will also be addressed in this project. Energy efficient solutions in a couple of important 5G cellular scenarios will be enabled through innovative modeling and algorithms in the uniformed multidimensional framework, including joint optimization that incorporates massive MIMO interference mitigation with flow constraint at network layer and base station sleeping at system level, formulation and algorithm development for a MWTP problem under the massive MIMO interference model, and modeling of the interplay between massive MIMO and device-to-device communications. In this project, the proposed research seamlessly integrates studies in the areas of optimization, graph theory, dual decomposition, approximation algorithms, and wireless communication and networking. The research outcomes are expected to provide important guidance for the development of the 5G cellular systems.
无线网络的快速发展和广泛部署导致能源需求快速上升,迫切需要节能的网络技术。与此同时,无线网络正在向复杂形态演进,拥有通信链路、无线、信道、天线、发射功率等多维资源;能源效率优化的低复杂度算法的需求量很大。该项目旨在通过建立统一的分析框架、开发高效且低复杂度的算法以及将通用研究应用于第五代(5G)蜂窝系统的重要场景,对节能无线网络进行基础研究。这种跨学科研究不仅将为本科生和研究生提供各种培养项目,还将激发学生以创造性、开放性和跨学科的视角进行高质量的研究。该项目将证明,可以通过调度适当的传输模式(由网络干扰模型定义)的原则来构建用于能源效率优化的统一多维优化框架。通过这种统一的优化模型,在根据信号干扰加噪声比的物理干扰模型下,低复杂度分解技术从根本上与最大加权传输模式(MWTP)问题相关。 MWTP 问题(一般是 NP 难问题)的近似算法和相关性能分析是需要研究的关键研究问题。解决能效优化问题的分布式算法进一步涉及多目标优化分解,以及物理干扰模型下创新的Lyapunov函数设计和相关稳定性分析,这些也将在本项目中得到解决。通过统一多维框架中的创新建模和算法,将在几个重要的 5G 蜂窝场景中实现节能解决方案,包括将大规模 MIMO 干扰抑制与网络层流量约束和系统级基站休眠相结合的联合优化、大规模 MIMO 干扰模型下的 MWTP 问题的制定和算法开发,以及大规模 MIMO 之间相互作用的建模。 MIMO 和设备到设备通信。在该项目中,所提出的研究无缝集成了优化、图论、对偶分解、近似算法以及无线通信和网络领域的研究。 研究成果有望为5G蜂窝系统的发展提供重要指导。

项目成果

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Yu Cheng其他文献

Theory-screened MOF-based single-atom catalysts for facile and effective therapy of biofilm-induced periodontitis
理论筛选的基于 MOF 的单原子催化剂可轻松有效地治疗生物膜引起的牙周炎
  • DOI:
    10.1016/j.cej.2021.133279
  • 发表时间:
    2021-11
  • 期刊:
  • 影响因子:
    15.1
  • 作者:
    Yi Yu;Yu Cheng;Lei Tan;Xiangmei Liu;Zhaoyang Li;Yufeng Zheng;Tao Wu;Zhenduo Cui;Shengli Zhu;Shuilin Wu
  • 通讯作者:
    Shuilin Wu
Object tracking in the complex environment based on SIFT
基于SIFT的复杂环境目标跟踪
A new model for Double Diffusion + Turbulence
双扩散湍流的新模型
  • DOI:
    10.1029/2007gl032580
  • 发表时间:
    2008
  • 期刊:
  • 影响因子:
    5.2
  • 作者:
    V. Canuto;Yu Cheng;A. Howard
  • 通讯作者:
    A. Howard
A supervisory hierarchical control approach for text to 2D scene generation
用于文本到 2D 场景生成的监督分层控制方法
Immune landscape of advanced gastric cancer tumor microenvironment identifes immunotherapeutic relevant gene signature
晚期胃癌肿瘤微环境的免疫景观识别免疫治疗相关基因特征
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    3.8
  • 作者:
    Simeng Zhang;Mengzhu Lv;Yu Cheng;Shuo Wang;Ce L;Xiujuan Qu
  • 通讯作者:
    Xiujuan Qu

Yu Cheng的其他文献

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{{ truncateString('Yu Cheng', 18)}}的其他基金

AF: Small: Faster Algorithms for High-Dimensional Robust Statistics
AF:小:用于高维稳健统计的更快算法
  • 批准号:
    2122628
  • 财政年份:
    2022
  • 资助金额:
    $ 38万
  • 项目类别:
    Standard Grant
AF: Small: Faster Algorithms for High-Dimensional Robust Statistics
AF:小:用于高维稳健统计的更快算法
  • 批准号:
    2307106
  • 财政年份:
    2022
  • 资助金额:
    $ 38万
  • 项目类别:
    Standard Grant
CNS Core: Small: Application-Oriented Scheduling for Optimizing Information Freshness in Wireless Networks
CNS 核心:小型:面向应用的调度,用于优化无线网络中的信息新鲜度
  • 批准号:
    2008092
  • 财政年份:
    2020
  • 资助金额:
    $ 38万
  • 项目类别:
    Standard Grant
Dynamic Multivariate Normative Comparison and Risk Screening for Alzheimer's Disease Progression
阿尔茨海默病进展的动态多变量规范比较和风险筛查
  • 批准号:
    1916001
  • 财政年份:
    2019
  • 资助金额:
    $ 38万
  • 项目类别:
    Standard Grant
NeTS: Small: Machine Learning Meets Wireless Network Optimization: Exploring the Latent Knowledge
NeTS:小型:机器学习遇见无线网络优化:探索潜在知识
  • 批准号:
    1816908
  • 财政年份:
    2018
  • 资助金额:
    $ 38万
  • 项目类别:
    Standard Grant
NSF Student Travel Grant for 2016 IEEE Global Communications Conference (IEEE GLOBECOM)
2016 年 IEEE 全球通信会议 (IEEE GLOBECOM) 的 NSF 学生旅费补助
  • 批准号:
    1643335
  • 财政年份:
    2016
  • 资助金额:
    $ 38万
  • 项目类别:
    Standard Grant
NeTS: Small: Collaborative Research: Towards Reliable, Energy-Efficient, and Secure Vehicular Networks
NetS:小型:协作研究:迈向可靠、节能和安全的车辆网络
  • 批准号:
    1320736
  • 财政年份:
    2014
  • 资助金额:
    $ 38万
  • 项目类别:
    Standard Grant
Association, Regression and Diagnostic Accuracy Analyses of Competing Risks Data
竞争风险数据的关联、回归和诊断准确性分析
  • 批准号:
    1207711
  • 财政年份:
    2012
  • 资助金额:
    $ 38万
  • 项目类别:
    Standard Grant
TC: Small: Real-Time Intrusion Detection for VoIP over IEEE 802.11 Based Wireless Networks: An Analytical Approach for Guaranteed Performance
TC:小型:基于 IEEE 802.11 的无线网络的 VoIP 实时入侵检测:保证性能的分析方法
  • 批准号:
    1117687
  • 财政年份:
    2012
  • 资助金额:
    $ 38万
  • 项目类别:
    Continuing Grant
CAREER: Exploring the Underexplored: A Fundamental Study of Optimal Resource Allocation and Low-Complexity Algorithms in Multi-Radio Multi-Channel Wireless Networks
职业:探索未开发领域:多无线电多通道无线网络中最优资源分配和低复杂度算法的基础研究
  • 批准号:
    1053777
  • 财政年份:
    2011
  • 资助金额:
    $ 38万
  • 项目类别:
    Continuing Grant

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