Dynamic Resource Control and Optimization for Data-Intensive Wireless Network Systems
|Event Date:||June 13, 2017|
|Speaker:||Dr. Jia (Kevin) Liu|
|Speaker Affiliation:||Ohio State University
Department of Electrical & Computer Engineering
|Type:||CNSIP Research Area Seminar
|Contact Name:||Professor Xiaojun Lin
|School or Program:||Electrical and Computer Engineering
Due to the proliferation of smart mobile devices and Internet-of-Things (IoT), recent years have witnessed an explosive growth of mobile data demands. As a result, today's wireless network infrastructures are being stretched to their capacity limits. The quest for an ever-increasing wireless network capacity has attracted tremendous research interests to develop 5G wireless networking, which is envisioned to be the backbone of future IoT. However, the emerging IoT applications also introduce much more stringent performance requirements on throughput, latency, and convergence speed in controlling 5G wireless networks.
To address these new challenges in 5G wireless networking and IoT, in this talk, we will present two of our recent and inter-related work on stochastic network resource control and optimization. In the first part, we introduce a new stochastic network optimization framework based on a low-complexity heavy-ball algorithm to achieve throughput-optimality with low delay and fast convergence, which are critical in IoT. We further show that the proposed heavy-ball scheme offers an elegant three-way performance control that unifies throughput, delay, and convergence. In the second part of this talk, we focus on bridging the gap between IoT network optimization and the advances in the 5G physical layers. Specifically, we consider hybrid beamforming optimization for millimeter-wave (mmWave) Massive MIMO (M-MIMO) from a network perspective. We show that the physical features of mmWave antenna array imply efficient network optimization design for hybrid beamforming optimization. We also characterize the impact of channel state information accuracy on throughput and delay in mmWave M-MIMO networks. Collectively, our findings advance the understanding of optimization algorithmic designs for future IoT and 5G wireless networks.
Jia (Kevin) Liu received his Ph.D. degree in the Bradley Dept. of Electrical and Computer Engineering at Virginia Tech, Blacksburg, VA in 2010. He is currently a Research Assistant Professor in the Dept. of Electrical and Computer Engineering at the Ohio State University. He will join the Dept. of Computer Science at Iowa State University in Fall 2017 as a tenure-track Assistant Professor. His research areas include theoretical foundations of control and optimization for network systems, distributed algorithms design, and Internet-of-things security. Dr. Liu is a senior member of IEEE. His work has received numerous awards at top venues, including IEEE INFOCOM 2016 Best Paper Award, IEEE INFOCOM 2013 Best Paper Runner-up Award, IEEE INFOCOM 2011 Best Paper Runner-up Award, and IEEE ICC 2008 Best Paper Award. He is a recipient of the Chinese Government Award for Outstanding Ph.D. Students Abroad in 2008. His research has been funded by NSF, AFOSR, AFRL, and ONR.