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Generalized Geometric Water-filling and Its Applications in
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alk title: Generalized Geometric Water-filling and Its Applications in Green Communications and Load Balancing for Smart Grid
时间:July 25, 2016. 10:30-11:30
地点:滨江楼A302
主讲人:Prof. Lian Zhao, Professor, Ryerson University (Canada)
Abstract:?
Water-filling, a well-known optimization algorithm, has been used for power allocation in communication systems to maximize system throughput. The problems with the conventional approach include solving non-linear equation set and no closed form solutions. The proposed geometric water-filling (GWF) approach provides closed-form and exact optimal solution and shed more insights to the problems and solutions.
Energy harvesting is often regarded as one of the techniques for green communications. ?The problem of power allocation with energy harvesting is then to maximize the throughput taking into account the fact that channel conditions and energy arrivals are time varying. For this target problem, we recursively apply the proposed GWF algorithm as a functional block to sequentially solve the power allocation problem. This algorithm is referred as Recursive-GWF (RGWF). The proposed RGWF is further extended to solving the minimization of the transmission completion time by inserting a condition check if the pre-set information amount being achieved.
In recent years, water-filling has also been applied in Smart Grid to solve load balancing and flatten the overall demand/load problems. ?We consider that the users are grouped into different groups. Each user has individual peak power constraint and each group has group peak power constraint due to different restrictions of the power loads used by the users and the groups. It will be shown that the optimal elastic power allocation to minimize the overall load fluctuation has the form of water-filling solution. We decompose the three dimension allocation problems into two dimension problems to gain tractability and provide optimal solutions efficiently.
All the proposed algorithms possess scalability feature and provide exact optimal solutions based on non-derivative methods, as the implementation of the proposed algorithms invokes neither derivative nor gradient operations.


Lian Zhao obtained her Ph.D. degree in Wireless Communication from University of Waterloo in 2002, joined the Department of Electrical and Computer Engineering, Ryerson University as an assistant professor in 2003, an associate professor in 2007, and a professor in 2013. Her research interests are in the area of wireless communications, radio resource management for complicated communication systems, load balancing in smart grid.
Dr. Zhao contributed over 100 peer-reviewed journal and conference papers. She received Canada Foundation for Innovation (CFI) New Opportunity Research Award in 2005; Ryerson Faculty Merit Award in 2005 and 2007; Faculty Research Excellence Award in 2010, 2012, and 2014; Best Paper Award from IEEE Chinacom in 2011, and Best Paper Award from 2013 International Conference on Wireless Communications and Signal Processing, 2015 TOP 15 Editor for her Outstanding Contributions to IEEE Transaction on Vehicular Technology.
Dr. Zhao is a committee member for NSERC (Natural Science and Engineering Research Council of Canada) Evaluation Group and an Editor for IEEE Transaction on Vehicular Technology. She served as workshop co-chair for IEEE/CIC ICCC 2015, local arrangement co-chair for IEEE Infocom 2014, symposium co-chair for IEEE Globecom 2013. She is an IEEE senior member and a registered professional engineer in the province of Ontario.