Collaborative Research: CNS core: Medium: True-Time-Delay based MIMO System and Testbed for Low-Latency Wideband Beam and Interference Management in Millimeter Wave Networks

合作研究: CNS 核心:中:基于真实时延的 MIMO 系统和毫米波网络中低延迟宽带波束和干扰管理的测试台

基本信息

  • 批准号:
    1955672
  • 负责人:
  • 金额:
    $ 55万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-10-01 至 2024-09-30
  • 项目状态:
    已结题

项目摘要

Given the shortage of spectrum below 6GHz, millimeter wave (mmW) frequencies have played an important role in the emerging 5G networks and this trend is expected to continue in the next generations. Due to unfavorable propagation conditions and attenuation at high frequencies, mmW networks require the densification of base stations and radios equipped with a large number of antennas to compensate path loss via directional gain using narrow beams. The cost and power consumption of radios with antenna arrays present a significant challenge, and their architecture is of fundamental importance and influence on the entire networking stack. State-of-the-art approaches based on phased antenna array architecture are faced with several fundamental problems when radio bandwidth and the number of antennas increases including prohibitive latency in initial connectivity and link management, distortion in the directionality of the beams, reduced beamforming gain, and ability to suppress the interference in dense deployments. This project aims to develop and demonstrate a novel adaptive true-time-delay (TTD) based array for wideband mmW networks and overcome challenges of phased antenna arrays. The approach involves co-design and optimization of tunable radio frequency (RF) circuits, antenna array system, signal processing, and network protocols for low latency access, wideband beamforming gain, and interference management. The research work will pursue four key thrusts: Thrust 1 will develop TTD array-based fast beam training and spatial interference detection and estimation for mmW networks with large modulated bandwidth. The objective is to reduce the overhead in initial access due to beam training by exploiting frequency-dependent antenna weight vectors in TTD arrays through signal processing and develop a low latency protocol design for simultaneous beam training and interference estimation in dense mmW networks. Thrust 2 will focus on the data communication design using TTD arrays to facilitate multiple-input multiple-output (MIMO) multiplexing and suppress interference from co-channel base stations and users. The main challenge is to achieve high beamforming gain over a wide modulated bandwidth together with effective nulling of wideband interferers. Thrust 3 will develop an experimental testbed for the evaluation of signal processing algorithms and protocols from Thrusts 1 and 2. It will involve the integration of widely reconfigurable delay compensating circuits and custom mmW front-end at 28GHz into a 16-element TTD antenna array. Thrust 4 will experimentally validate TTD array-based beam training, squint-free wideband beamforming and interference nulling, and wideband MIMO communications using the testbed developed in Thrust 3.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
鉴于6GHz以下频谱的短缺,毫米波(mmW)频率在新兴的5G网络中发挥了重要作用,预计这一趋势将在下一代中继续下去。由于不利的传播条件和高频处的衰减,mmW网络需要配备有大量天线的基站和无线电的致密化,以使用窄波束经由定向增益来补偿路径损耗。具有天线阵列的无线电的成本和功耗是一个重大挑战,其架构对整个网络堆栈具有根本的重要性和影响。当无线电带宽和天线数量增加时,基于相控天线阵列架构的现有技术方法面临几个基本问题,包括初始连接和链路管理中的禁止延迟、波束方向性的失真、降低的波束成形增益以及在密集部署中抑制干扰的能力。该项目旨在开发和演示一种新的基于宽带毫米波网络的自适应真时延(TTD)阵列,并克服相控天线阵列的挑战。该方法涉及可调谐射频(RF)电路、天线阵列系统、信号处理和网络协议的协同设计和优化,以实现低延迟接入、宽带波束成形增益和干扰管理。 研究工作将追求四个关键目标:目标1将为具有大调制带宽的毫米波网络开发基于TTD阵列的快速波束训练和空间干扰检测与估计。目标是通过信号处理利用TTD阵列中的频率相关天线权重向量来减少由于波束训练而导致的初始接入中的开销,并开发用于密集mmW网络中的同时波束训练和干扰估计的低延迟协议设计。第二目标将重点关注使用TTD阵列的数据通信设计,以促进多输入多输出(MIMO)复用并抑制来自同频基站和用户的干扰。主要的挑战是在宽调制带宽上实现高波束形成增益以及宽带干扰器的有效调零。Thrust 3将开发一个实验测试平台,用于评估Thrust 1和Thrust 2的信号处理算法和协议。它将涉及广泛可重构的延迟补偿电路和28GHz的定制毫米波前端集成到16单元TTD天线阵列中。推力4将使用推力3中开发的测试平台对基于TTD阵列的波束训练、无斜视宽带波束形成和干扰归零以及宽带MIMO通信进行实验验证。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(13)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Joint Millimeter-Wave AoD and AoA Estimation Using one OFDM Symbol and Frequency-Dependent Beams
使用一个 OFDM 符号和频率相关波束的联合毫米波 AoD 和 AoA 估计
  • DOI:
    10.1109/icassp49357.2023.10094643
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Boljanovic, Veljko;Cabric, Danijela
  • 通讯作者:
    Cabric, Danijela
Multi-Mode Spatial Signal Processor With Rainbow-Like Fast Beam Training and Wideband Communications Using True-Time-Delay Arrays
  • DOI:
    10.1109/jssc.2022.3178798
  • 发表时间:
    2022-06-08
  • 期刊:
  • 影响因子:
    5.4
  • 作者:
    Lin, Chung-Ching;Puglisi, Chase;Gupta, Subhanshu
  • 通讯作者:
    Gupta, Subhanshu
Fast Beam Training With True-Time-Delay Arrays in Wideband Millimeter-Wave Systems
  • DOI:
    10.1109/tcsi.2021.3054428
  • 发表时间:
    2021-04
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Veljko Boljanovic;Han Yan;Chung-Ching Lin;Soumen Mohapatra;D. Heo;Subhanshu Gupta;D. Cabric
  • 通讯作者:
    Veljko Boljanovic;Han Yan;Chung-Ching Lin;Soumen Mohapatra;D. Heo;Subhanshu Gupta;D. Cabric
A 4-Element 800MHz-BW 29mW True-Time-Delay Spatial Signal Processor Enabling Fast Beam-Training with Data Communications
4 元件 800MHz-BW 29mW 实时延迟空间信号处理器,通过数据通信实现快速波束训练
3D Rainbow Beam Design for Fast Beam Training with True-Time-Delay Arrays in Wideband Millimeter-Wave Systems
宽带毫米波系统中使用真延时阵列进行快速波束训练的 3D 彩虹波束设计
  • DOI:
    10.1109/ieeeconf53345.2021.9723402
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Wadaskar, Aditya;Boljanovic, Veljko;Yan, Han;Cabric, Danijela
  • 通讯作者:
    Cabric, Danijela
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Danijela Cabric其他文献

Editorial for Crowncom 2013 Special Issue
  • DOI:
    10.1007/s11036-014-0530-y
  • 发表时间:
    2014-08-08
  • 期刊:
  • 影响因子:
    2.000
  • 作者:
    Xiuzhen Cheng;Danijela Cabric
  • 通讯作者:
    Danijela Cabric
mmRAPID
毫米快速

Danijela Cabric的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Danijela Cabric', 18)}}的其他基金

Collaborative Research: FuSe: Collaborative Optically Disaggregated Arrays of Extreme-MIMO Radio Units (CODAeMIMO)
合作研究:FuSe:Extreme-MIMO 无线电单元的协作光学分解阵列 (CODAeMIMO)
  • 批准号:
    2328947
  • 财政年份:
    2023
  • 资助金额:
    $ 55万
  • 项目类别:
    Continuing Grant
NSF-AoF: CNS Core: Small: Machine Learning Based Physical Layer and Mobility Management Solutions Towards 6G
NSF-AoF:CNS 核心:小型:面向 6G 的基于机器学习的物理层和移动管理解决方案
  • 批准号:
    2224322
  • 财政年份:
    2022
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
Circuits and Systems Design for UAV Swarm Enabled Communications
无人机群通信的电路和系统设计
  • 批准号:
    1929874
  • 财政年份:
    2019
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
NeTS: Small: Coordinated Beam Discovery, Association, and Handover in Ultra-Dense Millimeter Wave Cellular Networks
NeTS:小型:超密集毫米波蜂窝网络中的协调波束发现、关联和切换
  • 批准号:
    1718742
  • 财政年份:
    2017
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
NeTS: Small: Dynamic Spectrum Access by Learning Primary Network Topology
NeTS:小型:通过学习主网络拓扑进行动态频谱访问
  • 批准号:
    1527026
  • 财政年份:
    2015
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
CAREER: Cognitive Co-Existence in Heterogeneous Wireless Networks
职业:异构无线网络中的认知共存
  • 批准号:
    1149981
  • 财政年份:
    2012
  • 资助金额:
    $ 55万
  • 项目类别:
    Continuing Grant
NeTS: Small:Spatio-Temporal Spectrum Sensing
NetS:小型:时空频谱传感
  • 批准号:
    1117600
  • 财政年份:
    2011
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant

相似国自然基金

Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 批准年份:
    2024
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
Cell Research
  • 批准号:
    31224802
  • 批准年份:
    2012
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research
  • 批准号:
    31024804
  • 批准年份:
    2010
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research (细胞研究)
  • 批准号:
    30824808
  • 批准年份:
    2008
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Research on the Rapid Growth Mechanism of KDP Crystal
  • 批准号:
    10774081
  • 批准年份:
    2007
  • 资助金额:
    45.0 万元
  • 项目类别:
    面上项目

相似海外基金

Collaborative Research: CNS Core: Medium: Reconfigurable Kernel Datapaths with Adaptive Optimizations
协作研究:CNS 核心:中:具有自适应优化的可重构内核数据路径
  • 批准号:
    2345339
  • 财政年份:
    2023
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
Collaborative Research: CNS Core: Small: A Compilation System for Mapping Deep Learning Models to Tensorized Instructions (DELITE)
合作研究:CNS Core:Small:将深度学习模型映射到张量化指令的编译系统(DELITE)
  • 批准号:
    2230945
  • 财政年份:
    2023
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
Collaborative Research: NSF-AoF: CNS Core: Small: Towards Scalable and Al-based Solutions for Beyond-5G Radio Access Networks
合作研究:NSF-AoF:CNS 核心:小型:面向超 5G 无线接入网络的可扩展和基于人工智能的解决方案
  • 批准号:
    2225578
  • 财政年份:
    2023
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
Collaborative Research: CNS Core: Medium: Movement of Computation and Data in Splitkernel-disaggregated, Data-intensive Systems
合作研究:CNS 核心:媒介:Splitkernel 分解的数据密集型系统中的计算和数据移动
  • 批准号:
    2406598
  • 财政年份:
    2023
  • 资助金额:
    $ 55万
  • 项目类别:
    Continuing Grant
Collaborative Research: CNS Core: Small: SmartSight: an AI-Based Computing Platform to Assist Blind and Visually Impaired People
合作研究:中枢神经系统核心:小型:SmartSight:基于人工智能的计算平台,帮助盲人和视障人士
  • 批准号:
    2418188
  • 财政年份:
    2023
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
Collaborative Research: CNS Core: Small: Creating An Extensible Internet Through Interposition
合作研究:CNS核心:小:通过介入创建可扩展的互联网
  • 批准号:
    2242503
  • 财政年份:
    2023
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
Collaborative Research: CNS Core: Small: Adaptive Smart Surfaces for Wireless Channel Morphing to Enable Full Multiplexing and Multi-user Gains
合作研究:CNS 核心:小型:用于无线信道变形的自适应智能表面,以实现完全复用和多用户增益
  • 批准号:
    2343959
  • 财政年份:
    2023
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
Collaborative Research: CNS Core: Small: Efficient Ways to Enlarge Practical DNA Storage Capacity by Integrating Bio-Computer Technologies
合作研究:中枢神经系统核心:小型:通过集成生物计算机技术扩大实用 DNA 存储容量的有效方法
  • 批准号:
    2343863
  • 财政年份:
    2023
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
Collaborative Research: CNS Core: Small: A Compilation System for Mapping Deep Learning Models to Tensorized Instructions (DELITE)
合作研究:CNS Core:Small:将深度学习模型映射到张量化指令的编译系统(DELITE)
  • 批准号:
    2341378
  • 财政年份:
    2023
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
Collaborative Research: CISE-MSI: RCBP-RF: CNS: ESD4CDaT - Efficient System Design for Cancer Detection and Treatment
合作研究:CISE-MSI:RCBP-RF:CNS:ESD4CDaT - 癌症检测和治疗的高效系统设计
  • 批准号:
    2318573
  • 财政年份:
    2023
  • 资助金额:
    $ 55万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了