CCSS: Collaborative Research: Smart-Grid Powered Green Communications in Heterogeneous Networks

CCSS:协作研究:异构网络中智能电网驱动的绿色通信

基本信息

  • 批准号:
    1508993
  • 负责人:
  • 金额:
    $ 20.4万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2015
  • 资助国家:
    美国
  • 起止时间:
    2015-07-01 至 2020-06-30
  • 项目状态:
    已结题

项目摘要

Both the current wireless communication networks and the electricity grid infrastructure are on the verge of a major paradigm shift. The traditional cellular architecture is evolving into heterogeneous networks (HetNets) consisting of densely deployed macro/micro/pico-cell base stations (BSs). In such HetNets, coordinated transmissions are advocated to perform energy-efficient green communications. At the same time, the current power network infrastructure is also migrating toward a so-termed smart grid that promises unprecedented levels of monitorability and controllability. It is expected that all future communication systems will be powered by a smart grid. Integration of smart-grid technologies into system designs then holds the key to fully exploiting the potential of green communications in next-generation HetNets. This highlights the clear need for fundamental understanding and systematic exploration of smart-grid powered green communications in HetNet deployments.To this end, the present project is centered on transformative analytical and algorithmic tools for smart-grid powered green communications. The vision is to establish a comprehensive framework based on state-of-the-art optimization approaches to jointly design green HetNets along with critically relevant smart grid operations. By cross-fertilizing ideas between these two fields, the ultimate goal is to set forth a unified treatment for modeling, analyzing, and designing resource management schemes for smart-grid powered HetNets. The engineering outcome of the proposed research is a suite of protocols for distributed, real-time implementation of basestation activation, coordinated beamforming in HetNets, as well as renewable energy harvesting and storage, demand response, and unit commitment operations for smart grids. Creating energy-efficient, distributed, real-time algorithms will greatly enhance the performance of emerging wireless cellular networks while reducing carbon emissions and enhancing the green communication solution to climate change and global warming. This project also addresses the broader impacts of improving undergraduate STEM education, increasing participation of under-represented minorities, and promoting a scientifically literate public.
当前的无线通信网络和电网基础设施都处于重大范式转变的边缘。传统的蜂窝架构正在演进为由密集部署的宏/微/微微小区基站 (BS) 组成的异构网络 (HetNet)。在此类异构网络中,提倡协调传输以进行节能的绿色通信。与此同时,当前的电力网络基础设施也正在向所谓的智能电网迁移,该电网有望实现前所未有的可监测性和可控性。预计未来所有通信系统都将由智能电网供电。将智能电网技术集成到系统设计中是充分挖掘下一代异构网络中绿色通信潜力的关键。这凸显了对 HetNet 部署中智能电网驱动的绿色通信的基本理解和系统探索的明确需求。为此,本项目的重点是智能电网驱动的绿色通信的变革性分析和算法工具。愿景是建立一个基于最先进优化方法的综合框架,共同设计绿色异构网络以及关键相关的智能电网运营。通过这两个领域之间的交叉融合,最终目标是为智能电网驱动的异构网络的建模、分析和设计资源管理方案提出统一的处理方法。拟议研究的工程成果是一套协议,用于分布式、实时实施基站激活、HetNet 中的协调波束成形,以及可再生能源收集和存储、需求响应和智能电网的单元承诺操作。创建节能、分布式、实时算法将极大地提高新兴无线蜂窝网络的性能,同时减少碳排放并增强针对气候变化和全球变暖的绿色通信解决方案。该项目还解决了改善本科 STEM 教育、增加代表性不足的少数群体的参与以及提高公众的科学素养等更广泛的影响。

项目成果

期刊论文数量(57)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Learning Graph Processes with Multiple Dynamical Models
Bandit Online Learning with Unknown Delays
  • DOI:
  • 发表时间:
    2018-07
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Bingcong Li;Tianyi Chen;G. Giannakis
  • 通讯作者:
    Bingcong Li;Tianyi Chen;G. Giannakis
Bandit Convex Optimization for Scalable and Dynamic IoT Management
  • DOI:
    10.1109/jiot.2018.2839563
  • 发表时间:
    2017-07
  • 期刊:
  • 影响因子:
    10.6
  • 作者:
    Tianyi Chen;G. Giannakis
  • 通讯作者:
    Tianyi Chen;G. Giannakis
Fast LAV Estimation via Composite Optimization
通过复合优化快速估计 LAV
  • DOI:
    10.1109/pesgm40551.2019.8974046
  • 发表时间:
    2019
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Wang, Gang;Giannakis, Gerogios B.;Chen, Jie
  • 通讯作者:
    Chen, Jie
Real-Time Energy Management in Microgrids With Reduced Battery Capacity Requirements
微电网中的实时能源管理,降低电池容量要求
  • DOI:
    10.1109/tsg.2017.2783894
  • 发表时间:
    2019-03
  • 期刊:
  • 影响因子:
    9.6
  • 作者:
    Bingcong Li;Tianyi Chen;Xin Wang;Georgios B. Giannakis
  • 通讯作者:
    Georgios B. Giannakis
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Georgios Giannakis其他文献

Georgios Giannakis的其他文献

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{{ truncateString('Georgios Giannakis', 18)}}的其他基金

Collaborative Research: ECCS-CCSS Core: Resonant-Beam based Optical-Wireless Communication
合作研究:ECCS-CCSS核心:基于谐振光束的光无线通信
  • 批准号:
    2332173
  • 财政年份:
    2024
  • 资助金额:
    $ 20.4万
  • 项目类别:
    Standard Grant
Collaborative Research: CIF: Medium: Robust Learning over Graphs
协作研究:CIF:媒介:图上的鲁棒学习
  • 批准号:
    2312547
  • 财政年份:
    2023
  • 资助金额:
    $ 20.4万
  • 项目类别:
    Continuing Grant
IMR: MM-1C: Learning-driven Models for 5G Internet Measurements
IMR:MM-1C:5G 互联网测量的学习驱动模型
  • 批准号:
    2220292
  • 财政年份:
    2022
  • 资助金额:
    $ 20.4万
  • 项目类别:
    Standard Grant
Collaborative Research: SWIFT: Cognitive-IoV with Simultaneous Sensing and Communications via Dynamic RF Front End
合作研究:SWIFT:通过动态射频前端实现同步传感和通信的认知车联网
  • 批准号:
    2128593
  • 财政年份:
    2021
  • 资助金额:
    $ 20.4万
  • 项目类别:
    Standard Grant
CCSS: Online Learning for IoT Monitoring and Management
CCSS:物联网监控和管理在线学习
  • 批准号:
    2126052
  • 财政年份:
    2021
  • 资助金额:
    $ 20.4万
  • 项目类别:
    Standard Grant
Hybrid mmWave mMIMO Transceiver Design for Doubly-Selective Channels
适用于双选通道的混合毫米波 mMIMO 收发器设计
  • 批准号:
    2102312
  • 财政年份:
    2020
  • 资助金额:
    $ 20.4万
  • 项目类别:
    Standard Grant
CPS: Medium: Collaborative Research: Collective Intelligence for Proactive Autonomous Driving (CI-PAD)
CPS:中:协作研究:主动自动驾驶集体智慧 (CI-PAD)
  • 批准号:
    2103256
  • 财政年份:
    2020
  • 资助金额:
    $ 20.4万
  • 项目类别:
    Standard Grant
CIF: Medium: Adaptive Diffusions for Scalable and Robust Learning over Graphs
CIF:中:用于图上可扩展和鲁棒学习的自适应扩散
  • 批准号:
    1901134
  • 财政年份:
    2019
  • 资助金额:
    $ 20.4万
  • 项目类别:
    Standard Grant
CCSS: Collaborative Research: Learn-and-Adapt to Manage Dynamic Cyber-Physical Networks
CCSS:协作研究:学习和适应管理动态信息物理网络
  • 批准号:
    1711471
  • 财政年份:
    2017
  • 资助金额:
    $ 20.4万
  • 项目类别:
    Standard Grant
EAGER-DynamicData: Judicious Censoring, Random Sketching, and Efficient Validate for Learning Patterns from Dynamically-Changing and Large-Scale Data Sets
EAGER-DynamicData:明智的审查、随机草图和高效验证,用于从动态变化的大规模数据集中学习模式
  • 批准号:
    1500713
  • 财政年份:
    2015
  • 资助金额:
    $ 20.4万
  • 项目类别:
    Standard Grant

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  • 批准号:
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相似海外基金

Collaborative Research: ECCS-CCSS Core: Resonant-Beam based Optical-Wireless Communication
合作研究:ECCS-CCSS核心:基于谐振光束的光无线通信
  • 批准号:
    2332172
  • 财政年份:
    2024
  • 资助金额:
    $ 20.4万
  • 项目类别:
    Standard Grant
Collaborative Research: ECCS-CCSS Core: Resonant-Beam based Optical-Wireless Communication
合作研究:ECCS-CCSS核心:基于谐振光束的光无线通信
  • 批准号:
    2332173
  • 财政年份:
    2024
  • 资助金额:
    $ 20.4万
  • 项目类别:
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Collaborative Research: CCSS: Continuous Facial Sensing and 3D Reconstruction via Single-ear Wearable Biosensors
合作研究:CCSS:通过单耳可穿戴生物传感器进行连续面部传感和 3D 重建
  • 批准号:
    2401415
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Collaborative Research: CCSS: When RFID Meets AI for Occluded Body Skeletal Posture Capture in Smart Healthcare
合作研究:CCSS:当 RFID 与人工智能相遇,用于智能医疗保健中闭塞的身体骨骼姿势捕获
  • 批准号:
    2245607
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    2023
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    $ 20.4万
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    Standard Grant
Collaborative Research: CCSS: Hierarchical Federated Learning over Highly-Dense and Overlapping NextG Wireless Deployments: Orchestrating Resources for Performance
协作研究:CCSS:高密度和重叠的 NextG 无线部署的分层联合学习:编排资源以提高性能
  • 批准号:
    2319780
  • 财政年份:
    2023
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    $ 20.4万
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