EAGER: Predictive Micro Mobility Management in mmWave Cellular Networks

由于其巨大的容量优势，毫米波通信已被设想为5G系统及更高级别的大容量低延迟解决方案，适用于室内(静态)和室外(移动)应用。然而，与这一愿景相比，现有的毫米波通信研究主要集中在静态用户，而移动用户以行人的速度以小范围移动的情况下，也称为。微移动性--户外毫米波应用的典型场景--在很大程度上被忽视了。微移动性的挑战源于这样一个事实，即毫米波通信严重依赖视距(LOS)通信，而视距通信在用户移动过程中可能经常被障碍物阻塞，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极大地破坏了更高层的性能。该项目将通过系统地探索一套适用于现实多障碍移动毫米波环境的基于预测的、跨层的、无缝的和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。该研究成果将为国家-S下一代高速蜂窝通信基础设施的成功发展做出贡献，从而为国家-S经济创造更强大的动力和载体。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。与传统的主动式和反应式移动性管理方法不同，该项目的新颖性在于开发了一类新的预测性链路/网络层设计，使在中断发生之前能够做出反应，克服了现有方法效率低和延迟长的弱点。特别是，在现实的多障碍室外环境中，将提出一种停机预测机制，以准确预测毫米波视距何时被阻塞以及阻塞持续多长时间。利用预测的阻塞信息，该项目将提出一个多尺度的即时(JIT)预测性停电处理框架。对于短持续时间的中断，将提出跨层预测链路/网络层设计，以隐藏上层的中断。对于长持续时间的中断，将开发一种JIT最优停止顺序切换机制来最大化切换效率和服务质量(Qos)，同时考虑切换开销和截止时间。奥本大学还将开发一个毫米波试验台，以评估所有建议的解决方案。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.