Provisioning of Next Generation Wireless Networks: A Large-Scale Optimization
Approach
Monday, March 3, 2014 - 8:45am - 9:45am
KEC 1007
Mingyi Hong
Research Assistant Professor
Department of Electrical and Computer Engineering
University of Minnesota
Abstract:
To cope with the growing demand for wireless data and to extend service
coverage, the next generation wireless networks will increasingly rely on the
use of low power micro/pico base stations and relays. These access nodes will
be densely deployed to form small cells in order to provide hotspot coverage
and traffic off-loading. However, due to frequency sharing and limited
infrastructural resource, interference and network congestion become major
performance limiting factors.
In the first part of the talk, we discuss several recent advances in joint
interference management and network provisioning for future cellular networks.
We show that proper provisioning of such network involves careful design of
various aspects such as physical layer signal processing as well as higher
layer base station clustering, network traffic flow control etc. We provide a
general cross-layer formulation of the problem which can include all these
aspects of the design into consideration. The resulting problems are usually
nonconvex, nonsmooth, and of very large sizes, hence are very difficult to deal
with. We then discuss a family of algorithms based on successive convex
approximation (SCA) that is able to effectively solve such large-scale network
provisioning problems.
In the second part of this talk, we extend the above SCA approach and present a
general framework, referred to as the block successive upper-bound minimization
method of multipliers (BSUM-M), which is able to deal with a wide range of
large-scale engineering problems well beyond wireless communication/signal
processing. The algorithm is simple, flexible, massively parallelizable, and
can deal with problems with millions or billions of variables in a highly
efficient manner. We discuss different properties of BSUM-M, and show how
specializations of such framework can be used to address key issues arising in
emerging applications such as machine learning and smart energy systems.
Speaker Biography:
Mingyi Hong is a research Assistant Professor with the Department of Electrical and Computer Engineering, University of Minnesota. He received his B.E. degree in Communications Engineering from Zhejiang University, China, his M.S. degree in Electrical Engineering from Stony Brook University (SBU) and Ph.D. degree in Systems Engineering from University of Virginia (UVa) in 2005, 2007 and 2011, respectively. His current research is focused on the design and analysis of next generation wireless networks. He is also interested in the theory of modern large-scale optimization and its applications in signal processing, big data analytics and management of smart energy systems.
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