EAGER: Predictive Micro Mobility Management in mmWave Cellular Networks

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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.