SpecEES: Toward Spectral and Energy Efficient Cross-Layer Designs for Millimeter-Wave-Based Massive MIMO Networks

SpecEES:面向基于毫米波的大规模 MIMO 网络的频谱和节能跨层设计

基本信息

  • 批准号:
    2140277
  • 负责人:
  • 金额:
    $ 55万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-06-01 至 2023-08-31
  • 项目状态:
    已结题

项目摘要

Millimeter-wave (mmWave) and Massive MIMO (M-MIMO) technologies have strong potential to impact future 5G wireless networks and support data rates 50 times greater than the current 4G LTE wireless communications. As such, 5G multi-Gigabit wireless networks are poised to enable a myriad of applications for (e.g., Internet-of-Things, virtual/augmented reality, etc.). However, the highly directional propagation of mmWave signals and the special mmWave hardware requirements introduce fundamental technical challenges for mmWave-based M-MIMO network systems that may require a clean-slate of hardware and software beamforming architectures. In light of these challenges, the goal of this research program is to advance knowledge in both hardware design and theoretical foundations of mmWave and M-MIMO wireless networks. By exploring new hardware-software technologies for mmWave M-MIMO wireless networks, this research program is envisioned to serve a critical need in mmWave communications, signal processing, networking, and control research communities. In terms of broader impacts, the PIs plan to incorporate findings into graduate courses and develop new special topic courses on the fundamentals of mmWave and M-MIMO communication networks. Engagement of undergrad and high school students is also planned with the aim to provide hands-on experience in RF components, communications, networking, control, and signal processing techniques.The proposed research address foundational problems in mmWave large antenna arrays and communication networks, with potential breakthroughs in both theory and practice to enable the success of on future multi-Gigabit wireless communications and associated networking applications. This research program spans broad areas of communications and signal processing to establish a network-level understanding of mmWave M-MIMO networks through a unified research program, which includes the development and exploration of: i) tractable theoretical models, ii) theoretical performance bounds and capacity limits, and iii) low-complexity algorithms. The novelty of this project lies in the joint beam training and scheduling algorithms through the introduction of novel algorithms in the radio-frequency front-end, and in the exploitation of subarray clustering to increase throughput and reduce energy consumption. The PIs' efforts are organized around three interdependent research thrusts: i) Transceiver and beamforming architectures that offer large agility in frequency tuning and high performance at several metrics, ii) Spectral-efficiency optimization algorithms based on mmWave-based subarray clustering, and iii) Energy-efficiency scheduling algorithms based on mmWave-based subarray clustering. In addition to theoretical studies, the PIs plan to validate the analytical techniques and models via extensive simulations, trace-driven emulations, and field tests.
毫米波(mmWave)和大规模MIMO(M-MIMO)技术具有影响未来5G无线网络的强大潜力,并支持比当前4G LTE无线通信高50倍的数据速率。因此,5G多千兆位无线网络有望实现无数应用(例如,物联网、虚拟/增强现实等)。然而,毫米波信号的高度定向传播和特殊的毫米波硬件要求为基于毫米波的M-MIMO网络系统带来了基本的技术挑战,这些系统可能需要一个全新的硬件和软件波束成形架构。鉴于这些挑战,该研究计划的目标是推进毫米波和M-MIMO无线网络的硬件设计和理论基础方面的知识。通过探索毫米波M-MIMO无线网络的新硬件-软件技术,该研究计划旨在满足毫米波通信,信号处理,网络和控制研究社区的关键需求。 在更广泛的影响方面,PI计划将研究结果纳入研究生课程,并开发关于毫米波和M-MIMO通信网络基础的新专题课程。本科生和高中生的参与也计划,目的是提供在射频组件,通信,网络,控制和信号处理技术的实践经验。拟议的研究解决毫米波大型天线阵列和通信网络的基础问题,在理论和实践上都有潜在的突破,使未来的多媒体技术能够取得成功,千兆位无线通信和相关的网络应用。该研究计划涵盖通信和信号处理的广泛领域,通过统一的研究计划建立对毫米波M-MIMO网络的网络级理解,其中包括开发和探索:i)易于处理的理论模型,ii)理论性能界限和容量限制,以及iii)低复杂度算法。 该项目的新奇在于通过在射频前端引入新的算法来联合波束训练和调度算法,以及利用子阵列聚类来增加吞吐量和降低能耗。PI的工作围绕三个相互依存的研究重点进行组织:i)收发器和波束成形架构,在频率调谐方面提供了很大的灵活性,并在多个指标上实现了高性能,ii)基于毫米波子阵列集群的频谱效率优化算法,以及iii)基于毫米波子阵列集群的能效调度算法。除了理论研究,PI计划通过广泛的模拟,跟踪驱动的仿真和现场测试来验证分析技术和模型。

项目成果

期刊论文数量(37)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Decentralized Learning for Overparameterized Problems: A Multi-Agent Kernel Approximation Approach," in Proc. ICLR, Virtual Event, April 2022
针对过度参数化问题的去中心化学习:多代理核逼近方法,”Proc. ICLR,虚拟活动,2022 年 4 月
  • DOI:
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Khanduri, P.;Yang, H.;Hong, M.;Liu, J.;Wai, H.;Liu, S.
  • 通讯作者:
    Liu, S.
DIAMOND: Taming Sample and Communication Complexities in Decentralized Bilevel Optimization
  • DOI:
    10.1109/infocom53939.2023.10228853
  • 发表时间:
    2022-12
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Pei-Yuan Qiu;Yining Li;Zhuqing Liu;Prashant Khanduri;Jia Liu;N. Shroff;E. Bentley;K. Turck
  • 通讯作者:
    Pei-Yuan Qiu;Yining Li;Zhuqing Liu;Prashant Khanduri;Jia Liu;N. Shroff;E. Bentley;K. Turck
Finite-Time Convergence and Sample Complexity of Multi-Agent Actor-Critic Reinforcement Learning with Average Reward
平均奖励的多智能体行为批评强化学习的有限时间收敛和样本复杂度
  • DOI:
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Hairi, F.;Liu, J. Lu
  • 通讯作者:
    Liu, J. Lu
A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization
  • DOI:
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Songtao Lu;Siliang Zeng;Xiaodong Cui;M. Squillante;L. Horesh;Brian Kingsbury;Jia Liu;Mingyi Hong
  • 通讯作者:
    Songtao Lu;Siliang Zeng;Xiaodong Cui;M. Squillante;L. Horesh;Brian Kingsbury;Jia Liu;Mingyi Hong
Anarchic Federated Learning
  • DOI:
  • 发表时间:
    2021-08
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Haibo Yang;Xin Zhang;Prashant Khanduri;Jia Liu
  • 通讯作者:
    Haibo Yang;Xin Zhang;Prashant Khanduri;Jia Liu
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Jia Liu其他文献

span style=font-family:quot;Times New Romanquot;,quot;serifquot;;font-size:12pt;Polymer-derived yttrium silicate coatings on 2D C/SiC composites/span
二维 C/SiC 复合材料上聚合物衍生的硅酸钇涂层
[Clinical study on combination of acupuncture, cupping and medicine for treatment of fibromyalgia syndrome].
针、拔罐、药物联合治疗纤维肌痛综合征的临床研究[J].
kNN Research based on Multi-Source Query Points on Road Networks
基于路网多源查询点的kNN研究
Electrochemical and Plasmonic Photochemical Oxidation Processes of para-Aminothiophenol on a Nanostructured Gold Electrode
纳米结构金电极上对氨基苯硫酚的电化学和等离子体光化学氧化过程
  • DOI:
    10.1021/acs.jpcc.1c05928
  • 发表时间:
    2021-11
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Hui-Yuan Peng;De-Yin Wu;Yuan-Hui Xiao;Huan-Huan Yu;Jia-Zheng Wang;Jian-De Lin;Rajkumar Devasenathipathy;Jia Liu;Pei-Hang Zou;Meng Zhang;Jian-Zhang Zhou;Zhong-Qun Tian
  • 通讯作者:
    Zhong-Qun Tian
Indirect Effects of Fluid Intelligence on Creative Aptitude Through Openness to Experience
流体智力通过开放体验对创造性能力的间接影响
  • DOI:
    10.1007/s12144-017-9633-5
  • 发表时间:
    2019-04
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Xiqin Liu;Ling Liu;Zhencai Chen;Yiying Song;Jia Liu
  • 通讯作者:
    Jia Liu

Jia Liu的其他文献

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{{ truncateString('Jia Liu', 18)}}的其他基金

RAPID: DRL AI: A Career-Driven AI Educational Program in Smart Manufacturing for Underserved High-school Students in the Alabama Black Belt Region
RAPID:DRL AI:针对阿拉巴马州黑带地区服务不足的高中生的智能制造领域职业驱动型人工智能教育计划
  • 批准号:
    2338987
  • 财政年份:
    2023
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
CAREER: Manufacturing USA: Deep Learning to Understand Fatigue Performance and Processing Relationship of Complex Parts by Additive Manufacturing for High-consequence Applications
职业:美国制造:通过深度学习了解复杂零件的疲劳性能和加工关系,通过增材制造实现高后果应用
  • 批准号:
    2239307
  • 财政年份:
    2023
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
ERASE-PFAS: Exploring efficient pilot-scale treatment of per- and polyfluoroalkyl substances and comingled chlorinated solvents in groundwater using magnetic nanomaterials
ERASE-PFAS:探索使用磁性纳米材料对地下水中的全氟烷基物质和多氟烷基物质以及混合氯化溶剂进行有效的中试规模处理
  • 批准号:
    2305729
  • 财政年份:
    2023
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
Preparing to Care for a Culturally and Linguistically Diverse UK Patient Population: How Healthcare Students Develop Their Cultural Competence
准备照顾文化和语言多样化的英国患者群体:医疗保健学生如何发展他们的文化能力
  • 批准号:
    ES/W004860/1
  • 财政年份:
    2021
  • 资助金额:
    $ 55万
  • 项目类别:
    Fellowship
FMSG: Cyber: Federated Deep Learning for Future Ubiquitous Distributed Additive Manufacturing
FMSG:网络:面向未来无处不在的分布式增材制造的联合深度学习
  • 批准号:
    2134689
  • 财政年份:
    2021
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
CPS: Medium: An AI-enabled Cyber-Physical-Biological System for Cardiac Organoid Maturation
CPS:中:用于心脏类器官成熟的人工智能网络物理生物系统
  • 批准号:
    2038603
  • 财政年份:
    2020
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
CAREER: Computing-Aware Network Optimization for Efficient Distributed Data Analytics at the Wireless Edge
职业:计算感知网络优化,用于无线边缘的高效分布式数据分析
  • 批准号:
    2110259
  • 财政年份:
    2020
  • 资助金额:
    $ 55万
  • 项目类别:
    Continuing Grant
NeTS: Small: Toward Optimal, Efficient, and Holistic Networking Design for Massive-MIMO Wireless Networks
NeTS:小型:面向大规模 MIMO 无线网络的优化、高效和整体网络设计
  • 批准号:
    2102233
  • 财政年份:
    2020
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
CAREER: Computing-Aware Network Optimization for Efficient Distributed Data Analytics at the Wireless Edge
职业:计算感知网络优化,用于无线边缘的高效分布式数据分析
  • 批准号:
    1943226
  • 财政年份:
    2020
  • 资助金额:
    $ 55万
  • 项目类别:
    Continuing Grant
CIF: Small: Taming Convergence and Delay in Stochastic Network Optimization with Hessian Information
CIF:小:利用 Hessian 信息驯服随机网络优化中的收敛和延迟
  • 批准号:
    2110252
  • 财政年份:
    2020
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant

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