EAGER: Predictive Micro Mobility Management in mmWave Cellular Networks
EAGER: Predictive Micro Mobility Management in mmWave Cellular Networks
批准号:
1837034
负责人:
Tao Shu
金额:
$29.8万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-10-01 至 2022-09-30
中文摘要
由于其巨大的容量优势,毫米波通信已被设想为用于室内(静态)和室外(移动的)应用的5G系统及更高系统的有前途的高容量低延迟解决方案。然而,落后于这一愿景,现有的毫米波通信研究主要集中在静态用户,而移动的用户的情况下,以行人的速度小规模移动,也称为。微移动性-为户外毫米波应用设想的典型场景,已经在很大程度上被忽视。微移动性的挑战源于毫米波通信严重依赖视距(LOS)通信的事实,在用户移动过程中,视距通信可能经常被障碍物阻挡,导致接收信号丢失并导致链路中断。由此产生的间歇性连接显著地破坏了更高层的性能。该项目将通过系统地探索一套基于预测的、跨层的、无缝的、高效的微移动性管理解决方案来解决室外毫米波网络中微移动性的根本挑战,这些解决方案适用于现实的多障碍移动的毫米波环境。研究成果将有助于国家的成功发展?的下一代高速蜂窝通信基础设施,从而将创造一个更强大的驱动力和载体的国家?的经济。该项目还将实施一项全面的教育计划,以扩大其影响,特别强调代表性不足和少数群体。与传统的主动和被动移动性管理方法相比,该项目的新奇在于开发了一类新的预测链路/网络层设计,能够在停电发生之前做出反应,克服了现有方法效率低、延时长的缺点。特别地,将提出中断预测机制,以准确地预测毫米波LOS何时将被阻塞以及阻塞将在现实的多障碍物室外环境中持续多久。利用预测阻塞信息,该项目将提出一个多尺度的即时(JIT)预测停电处理框架。对于短持续时间的中断,将提出跨层预测链路/网络层设计,以隐藏上层中断。对于长时间的中断,JIT的最优停止顺序切换机制将被开发,以最大限度地提高切换效率和服务质量(QoS),同时考虑切换开销和最后期限。奥本大学还将开发一个毫米波测试台,以评估所有提出的解决方案。该奖项反映了NSF的法定使命,并被认为值得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。
英文摘要
Due to its huge capacity benefits, mmWave communication has been envisioned as a promising high-capacity low-latency solution for 5G systems and beyond, for both indoor (static) and outdoor (mobile) applications. Lagging behind this vision, however, existing research on mmWave communication is mainly focused on static users, while the case of mobile users that move in small scale at pedestrian speed, a.k.a. micro mobility - a typical scenario envisioned for outdoor mmWave applications, has been largely ignored. The challenge of micro mobility stems from the fact that mmWave communication heavily relies on line of sight (LOS) communications, which could be frequently blocked by obstacles during the course of user movement, leading to loss of the received signal and causing link outage. The resulting intermittent connection significantly undermines the performance of higher layers. This project will address the fundamental challenge of micro mobility in outdoor mmWave networks by systematically exploring a suite of prediction-based, cross-layer, seamless, and efficient micro mobility management solutions for realistic multi-obstacle mobile mmWave environments. The research outcome will contribute to the successful development of the nation?s next-generation high-speed cellular communication infrastructure, and hence will create a stronger driving force and carrier for the nation?s economy. This project will also carry out a comprehensive education plan to broaden its impact, with a special emphasis on underrepresented and minority groups.In contrast to the conventional proactive and reactive mobility management methods, the novelty of this project lies in the development of a new class of predictive link/network-layer designs that enables reaction to an outage before it happens, overcoming the low-efficiency and long-delay weaknesses of existing methods. In particular, an outage prediction mechanism will be proposed to accurately predict when the mmWave LOS will be blocked and how long the blockage will last in realistic multi-obstacle outdoor environment. Taking advantage of the predicted blockage information, the project will propose a multi-scale just-in-time (JIT) predictive outage handling framework. For outage of short durations, cross-layer predictive link/network-layer designs will be proposed to hide outages from upper layers. For outages of long durations, a JIT optimal-stopping sequential handover mechanism will be developed to maximize the handover efficiency and quality of service (QoS) while accounting for the handover overhead and deadline. A mmWave test-bed will also be developed at Auburn University to evaluate all proposed solutions.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.
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DOI:
10.1109/globecom38437.2019.9014079
发表时间:
2019-12
期刊:
2019 IEEE Global Communications Conference (GLOBECOM)
影响因子:
--
作者:
[Li Sun;Jing Hou;Tao Shu]
通讯作者:
Li Sun;Jing Hou;Tao Shu
Spoofing Detection for Indoor Visible Light Systems with Redundant Orthogonal Encoding
具有冗余正交编码的室内可见光系统的欺骗检测
DOI:
10.1109/icc42927.2021.9500335
发表时间:
2021
期刊:
ICC 2021 - IEEE International Conference on Communications
影响因子:
--
作者:
[Chen, Jian, Shu, Tao]
通讯作者:
Shu, Tao
DOI:
10.1109/tmc.2021.3064809
发表时间:
2022-11
期刊:
IEEE Transactions on Mobile Computing
影响因子:
7.9
作者:
[Xueyang Hu;Tian Liu;Tao Shu]
通讯作者:
Xueyang Hu;Tian Liu;Tao Shu
VL-Watchdog: Visible Light Spoofing Detection With Redundant Orthogonal Coding
VL-Watchdog:采用冗余正交编码的可见光欺骗检测
DOI:
10.1109/jiot.2022.3155600
发表时间:
2022
期刊:
IEEE Internet of Things Journal
影响因子:
10.6
作者:
[Chen, Jian, Shu, Tao]
通讯作者:
Shu, Tao
DOI:
10.1007/978-3-030-37231-6_7
发表时间:
2019-10
期刊:
影响因子:
--
作者:
[Jing Hou;Li Sun;Tao Shu;Husheng Li]
通讯作者:
Jing Hou;Li Sun;Tao Shu;Husheng Li
共 15 条
SaTC: CORE: Small: Building Resilience into LEO Satellite Networks by Exploiting Network Layer Characteristics
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批准号:2308761
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项目类别:Continuing Grant
-
资助金额:$30.0万
-
财政年份:2023
-
负责人:Tao Shu
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依托单位:
CNS Core: Small: Enabling Privacy-Preserving Routing-on-Context in IoT
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批准号:1745254
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资助金额:$12.0万
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依托单位:
NeTS: Small: Collaborative Research: Network Economics for Secondary Spectrum Ecosystems
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批准号:1659965
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项目类别:Standard Grant
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资助金额:$22.91万
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财政年份:2016
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负责人:Tao Shu
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依托单位:
Collaborative Research: EARS: Large-Scale Statistical Learning based Spectrum Sensing and Cognitive Networking
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批准号:1659962
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项目类别:Standard Grant
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资助金额:$13.74万
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财政年份:2016
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负责人:Tao Shu
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依托单位:
NeTS: Small: Collaborative Research: Network Economics for Secondary Spectrum Ecosystems
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批准号:1524931
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项目类别:Standard Grant
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资助金额:$23.25万
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财政年份:2015
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负责人:Tao Shu
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依托单位:
Collaborative Research: EARS: Large-Scale Statistical Learning based Spectrum Sensing and Cognitive Networking
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批准号:1343156
-
项目类别:Standard Grant
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资助金额:$26.23万
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财政年份:2014
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负责人:Tao Shu
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依托单位:
海外基金