With the rapid advances in sensing, communication, and storage technologies, distributed data acquisition is now ubiquitous in many areas of engineering, biological, and social sciences. For example, the large-scale implementation of advanced metering systems in the smart grids enables real time collection of a huge amount of distributed data (voltages, phases, etc), the understanding of which is critical in improving the overall performance of the future power systems. More examples of distributed data include high-resolution videos from a network of surveillance systems, interactions on a social network, and environmental data from sensor networks. Timely and effectively processing of such large amount of distributed, and possibly corrupted and/or online data requires not only novel data processing techniques, but also a deep understanding of the underlying network properties of physical systems, including the network topology, the processing capability of each distributed node, the nature of the data, etc. These sophisticated characteristics bring new challenges for the design and analysis of optimization and resource management algorithms. This symposium aims to bring together researchers and experts in the fields of signal processing, control, optimization, network sciences, and cyber-physical systems to address the emerging challenges related to this topic. Emphasis will be given to theories and applications for distributed signal processing systems, cyber-physical systems as well as advanced distributed control and optimization techniques.
University of Toronto
Interference management is a key challenge for both cellular and device-to-device (D2D) communication networks, in which multiple transmitter and receiver pairs may arbitrarily interfere with each other with full frequency reuse. In this talk, we introduce a distributed spectrum sharing strategy called FPLinQ to alleviate inter-link interference by coordinating link schedule decisions throughout the network. Scheduling in the general setting is a challenging combinatorial optimization problem. In this talk, we devise a fractional programming (FP) approach to derive a reformulation whereby the integer variables are determined analytically in each iterative step. The resulting FPLinQ algorithm enables an iterative and distributed optimization of link schedule with provable convergence. The proposed strategy can be extended to include joint link scheduling and power control. The proposed strategy can further be used for interference aware uplink scheduling and beamforming in cellular networks. As compared to the existing works such as FlashLinQ, ITLinQ and ITLinQ+, a main advantage of the proposed strategy is that it does not require tuning of design parameters; it further shows significant performance advantage as compared to the benchmarks in maximizing the sum rate and the network utility.
Wei Yu (S'97-M'02-SM'08-F’14) received the B.A.Sc. degree in Computer Engineering and Mathematics from the University of Waterloo, Waterloo, Ontario, Canada in 1997 and M.S. and Ph.D. degrees in Electrical Engineering from Stanford University, Stanford, CA, in 1998 and 2002, respectively. Since 2002, he has been with the Electrical and Computer Engineering Department at the University of Toronto, Toronto, Ontario, Canada, where he is now Professor and holds a Canada Research Chair (Tier 1) in Information Theory and Wireless Communications. His main research interests include information theory, optimization, wireless communications and broadband access networks.
Prof. Wei Yu currently serves on the IEEE Information Theory Society Board of Governors (2015-17). He is an IEEE Communications Society Distinguished Lecturer (2015-16). He served as an Associate Editor for IEEE Transactions on Information Theory (2010-2013), as an Editor for IEEE Transactions on Communications (2009-2011), as an Editor (2004-2007) and Area Editor (2017-Present) for IEEE Transactions on Wireless Communications, and as a Guest Editor for a number of special issues for the IEEE Journal on Selected Areas in Communications and the EURASIP Journal on Applied Signal Processing. He was a Technical Program co-chair of the IEEE Communication Theory Workshop in 2014, and a Technical Program Committee co-chair of the Communication Theory Symposium at the IEEE International Conference on Communications (ICC) in 2012. He is the Chair of the Signal Processing for Communications and Networking Technical Committee of the IEEE Signal Processing Society (2017-18) and member (2008-2013). Prof. Wei Yu received a Journal of Communications and Networks Best Paper Award in 2017, a Steacie Memorial Fellowship in 2015, an IEEE Communications Society Best Tutorial Paper Award in 2015, an IEEE ICC Best Paper Award in 2013, an IEEE Signal Processing Society Best Paper Award in 2008, the McCharles Prize for Early Career Research Distinction in 2008, the Early Career Teaching Award from the Faculty of Applied Science and Engineering, University of Toronto in 2007, and an Early Researcher Award from Ontario in 2006. He is recognized as a Highly Cited Researcher.
Prof. Wei Yu is a Fellow of IEEE and a Fellow of Canadian Academy of Engineering. He is a registered Professional Engineer in Ontario.
|Wednesday, November 15|
|14:00 - 15:30|
|RMN-P.1: Distributed Optimization and Resource Management over Networks Posters|
|Thursday, November 16|
|09:40 - 10:30|
|RMN-DST.1: Distinguished Speaker - Wei Yu, University of Toronto|
|11:00 - 12:30|
|RMN-O.1: Distributed Optimization and Resource Management over Networks I|
|14:00 - 15:30|
|RMN-O.2: Distributed Optimization and Resource Management over Networks II|
Submissions are welcome on topics including:
Prospective authors are invited to submit full-length papers (up to 4 pages for technical content, an optional 5th page containing only references) and extended abstracts (up to 2 pages, for paperless industry presentations and Ongoing Work presentations). Manuscripts should be original (not submitted/published anywhere else) and written in accordance with the standard IEEE double-column paper template. Accepted full-length papers will be indexed on IEEE Xplore. Accepted abstracts will not be indexed in IEEE Xplore, however the abstracts and/or the presentations will be included in the IEEE SPS SigPort. Accepted papers and abstracts will be scheduled in lecture and poster sessions. Submission is through the GlobalSIP website at http://2017.ieeeglobalsip.org/Papers.asp.
Notice: The IEEE Signal Processing Society enforces a “no-show” policy. Any accepted paper included in the final program is expected to have at least one author or qualified proxy attend and present the paper at the conference. Authors of the accepted papers included in the final program who do not attend the conference will be subscribed to a “No-Show List”, compiled by the Society. The “no-show” papers will not be published by IEEE on IEEEXplore or other public access forums, but these papers will be distributed as part of the on-site electronic proceedings and the copyright of these papers will belong to the IEEE.
|Paper Submission Deadline||June 2, 2017|
|Review Results Announced||July 17, 2017|
|Camera-Ready Papers Due||August 5, 2017|
Amir Asif, Concordia University
Zhi-Quan Luo, University of Minnesota
Necdet Serhat Aybat, Pennsylvania State University
Mingyi Hong, Iowa State University
Qing Ling, University of Science and Technology of China