IEEE ICCC 2013 Keynote Speakers
Hequan Wu
Professor,
Chinese Academy of Engineering
Internet: Big Data and Big Challenges
Recalling computers, mobile terminals, optical fiber communications, mobile communications technology, there are thousands of times performance improvement about 10 to 20 years. Global mobile data traffic and backbone network traffic increase approximately 500 to 1000 times every ten years. The average traffic increment per user of Internet by ten years is also 1000 times. Looking to the future the pace of development does not slow down, the network faces the pressure of big data. Broadbandization is the first reaction for big data. The backbone network, wired and wireless access network are being expanded and upgraded. Big Data accelerates cloud computing applications. The installation of cloud computing nodes to follow the principles of green and widespread deployment of CDN to adapt the video service development will increase lot of new nodes beyond the original network nodes. Because most backbone nodes just forwarding services, from saving energy considerations, services forwarded as far as possible in the optical domain rather than the electrical domain, and if the traffic need exchanged in the electrical domain, MPLS layer is preferred for the exchange of services traffic rather than the IP layer. The arrival of big data era further highlight the role of the MAN, the traditional C / S or P2P architecture will evolve to S2S (server to server). In order to accommodate big data, mobile network on the one hand need densely deploy small cells, on the other hand C-RAN is also cause for great concern, and the group cell and distributed antennas are adopted to improve the user experience from a different perspective. The dynamics of time and position in traffic of big data also gave birth to the SDN. In short, the change on network architecture for big data is opportunities and even more challenges.
Biography: Prof. Wu Hequan graduated from Wuhan Institute of Post and Telecommunications in 1964. He has worked in the China Academy of Post and Telecommunications of the Ministry of Post and Telecommunications since 1964. He was Vice-President and Chief Engineer of China Academy of Telecommunications Technology from 1997 to 2003. He has conducted research and development in optical fiber transmission systems and broadband networks. He takes charge to manage R&D projects on NGI and 3G as well as LTE since 2002. He was elected academician of Chinese Academy of Engineering (CAE) in 1999 and Vice-President of CAE from June 2002 to June 2010. He is currently Vice-Director of the Advisory Committee for State Informatization and the Director of Communications S&T Committee of MIIT. He is also Vice-Director of an Executive Council of China Institute of Communications (CIC) and Chinese Institute of Electronics (CIE) respectively. Prof. Wu has been appointed technical director of the new generation broadband wireless mobile communications network, one of the 16 major projects in the Outline of the National Program for Long- and Medium-term Scientific and Technological Development (2006~2020) of China. He is Director of Experts Committee of China’s Next Generation Internet (CNGI) project, and is head of expert group of three network convergence of the State Council. Prof. Wu is director of expert group of IOT. He is a senior member of IEEE.
Andrea Goldsmith
Professor of Electrical Engineering,
Department of Electrical Engineering,
Stanford University
Enabling the Wireless Cloud through Software-Defined Networking
The wireless industry is at a tipping point. Cellular networks are struggling to keep up with the explosive demand for data. While the upgrade to LTE has boosted cellular performance somewhat, these improvements are not sufficient to meet expected demand given the limited availability of licensed spectrum. Small cells will be the dominant mechanism to boost capacity of cellular networks, but they introduce challenges of their own, including interference management between macro and small cells as well as the need for self-configuration. In addition to addressing the spectrum crunch through small cells, the unlicensed spectrum must also be tapped via WiFi. However, WiFi networks suffer from unmanaged interference, unreliable performance, and poor quality-of-experience for the end user. The solution to all these challenges is software-defined wireless networking, whereby cheap wireless hardware (e.g. small cells and WiFi access points) are extensively deployed, with cloud-based software dynamically optimizing the overall network performance and providing intelligent seamless mobility between WiFi and LTE networks. We will discuss the vision of this wireless cloud, how it is enabled by software-defined wireless networking, and some of the challenges associated with making this vision a reality.
Biography: Andrea Goldsmith is a professor of Electrical Engineering at Stanford University, and was previously an assistant professor of Electrical Engineering at Caltech. She co-founded Accelera, Inc., which develops wireless network virtualization technology, and Quantenna Communications Inc., which develops silicon for advanced WiFi systems. She has previously held industry positions at Maxim Technologies, Memorylink Corporation, and AT&T Bell Laboratories. Dr. Goldsmith is a Fellow of the IEEE and of Stanford, and she has received several awards for her work, including the IEEE Communications Society and Information Theory Society joint paper award, the National Academy of Engineering Gilbreth Lecture Award, the IEEE Wireless Communications Technical Committee Recognition Award, the Alfred P. Sloan Fellowship, and the Silicon Valley/San Jose Business Journal’s Women of Influence Award. She is author of the book ``Wireless Communications'' and co-author of the books "MIMO Wireless Communications'' and “Principles of Cognitive Radio,” all published by Cambridge University Press. She received the B.S., M.S. and Ph.D. degrees in Electrical Engineering from U.C. Berkeley.
Dr. Goldsmith has served as associate editor for the IEEE Transactions on Information Theory and as editor for the Journal on Foundations and Trends in Communications and Information Theory and in Networks. She previously served as an editor for the IEEE Transactions on Communications and for the IEEE Wireless Communications Magazine. Dr. Goldsmith participates actively in committees and conference organization for the IEEE Information Theory and Communications Societies and has served on the Board of Governors for both societies. She is a Distinguished Lecturer for both societies, served as the President of the IEEE Information Theory Society in 2009, founded and chaired the student committee of the IEEE Information Theory society, and currently chairs the Emerging Technology Committee and is a member of the Strategic Planning Committee in the IEEE Communications Society. At Stanford she received the inaugural University Postdoc Mentoring Award, served as Chair of its Faculty Senate, and currently serves on its Faculty Senate and on its Budget Group.
Yuguang Fang
Professor,
Department of Electrical
and Computer Engineering, University of Florida
How to Effectively Utilize the Harvested Resource in Cognitive Radio Networks
Cognitive radios are designed to sense the unused spectrum and opportunistically utilize such resource to support communications services without affecting the services of the incumbent spectrum users. Unfortunately, most research focuses on either cognitive radio design or spectrum sensing for mostly one-hop communications, leading to schemes only of theoretical research. In this talk, the speaker will present a novel network architecture which can enable spectrum harvesting and more effective use of the harvested spectrum. Besides, this network architecture can be used to identify the “hidden” network capability and provides more effective service provisioning. Finally, when this architecture is integrated with cellular systems, the non-cognitive cellular devices can also take advantage of this architecture and the system capacity of cellular systems can be enhanced.
Biography: Dr. Fang received the BS/MS degree in Mathematics from Qufu Normal University, Qufu, Shandong, China in 1987, a Ph.D degree in Systems and Control Engineering from Department of Systems, Control and Industrial Engineering at Case Western Reserve University, Cleveland, Ohio, in January 1994, and a Ph.D degree in Electrical Engineering from Department of Electrical and Computer Engineering at Boston University, Massachusetts, in May 1997.
From 1987 to 1988, he held research and teaching position in both Department of Mathematics and the Institute of Automation at Qufu Normal University. From September 1989 to December 1993, he was a teaching/research assistant in Department of Systems, Control and Industrial Engineering at Case Western Reserve University, where he held a research associate position from January 1994 to May 1994. He held a post-doctoral position in Department of Electrical and Computer Engineering at Boston University from June 1994 to August 1995. From September 1995 to May 1997, he was a research assistant in Department of Electrical and Computer Engineering at Boston University. From June 1997 to July 1998, he was a Visiting Assistant Professor in Department of Electrical Engineering at the University of Texas at Dallas. From July 1998 to May 2000, he was an Assistant Professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology, Newark, New Jersey. In May 2000, he joined the Department of Electrical and Computer Engineering at University of Florida, Gainesville, Florida, where he got early promotion to Associate Professor with tenure in August 2003, and to Full Professor in August 2005. He holds a University of Florida Research Foundation Professorship from 2006 to 2009. His research interests span many areas including wireless networks, mobile computing, mobile communications, wireless security, automatic control, and neural networks. He has published over 200 papers in refereed professional journals and conferences. He received the National Science Foundation Faculty Early Career Award in 2001 and the Office of Naval Research Young Investigator Award in 2002. He also received the 2001 CAST Academic Award.
Dr. Fang has actively engaged in many professional activities. He is an IEEE Fellow (2008) and a member of the ACM. He is an Editor for IEEE Transactions on Communications, an Editor for IEEE Transactions on Wireless Communications, an Editor for IEEE Transactions on Mobile Computing, an Editor for ACM Wireless Networks, and an Editor for IEEE Wireless Communications. He was an Editor for IEEE Journal on Selected Areas in Communications: Wireless Communications Series, an Area Editor for ACM Mobile Computing and Communications Review, an Editor for Wiley International Journal on Wireless Communications and Mobile Computing, and Feature Editor for Scanning the Literature in IEEE Personal Communications. He has also actively involved with many professional conferences such as ACM Mobihoc'08, ACM MobiCom'02 (Committee Co-Chair for Student Travel Award), MobiCom'01, IEEE INFOCOM'08, INFOCOM'07, INFOCOM'06, INFOCOM'05 (Vice-Chair for Technical Program Committee), INFOCOM'04, INFOCOM'03, INFOCOM'00, INFOCOM'98, IEEE WCNC'04, WCNC'02, WCNC'00 (Technical Program Vice-Chair), WCNC'99, IEEE Globecom'04 (Symposium Co-Chair), Globecom'02, and International Conference on Computer Communications and Networking (IC3N) (Technical Program Vice-Chair).
Chengshan XiaoProfessor,
Department of Electrical & Computer Engineering,
Missouri University of Science and Technology
Maximizing Achievable Data Rate for Finite Alphabet Signaling
Finite alphabet signaling refers to commonly used discrete-constellation modulations in practical communication systems, such as PAM, PSK or QAM. In this talk, we will target at how to increase data rate or throughput via linear precoding in wireless systems and networks such as multiple-input multiple-output (MIMO) systems, multiple access channels, broadcast channels, wiretap channels, and cognitive radio networks. We will present backgrounds, theoretical results, hardware implementation, and experimental results for maximizing the mutual information-based achievable data rate or throughput. Our results demonstrate that linear precoding for finite alphabet signaling can be radically different from the linear precoding (or power allocation) for Gaussian signaling. Our examples show that the finite-alphabet signaling-based approach provides not only higher achievable data rate but also lower coded bit error rate than the approaches that design linear precoders with Gaussian input assumption.
Biography: Chengshan Xiao received the B.S. degree in electronic engineering from the University of Electronic Science and Technology of China, Chengdu, China, in 1987, the M.S. degree in electronic engineering from Tsinghua University, Beijing, China, in 1989, and the Ph.D. degree in electrical engineering from the University of Sydney, Sydney, Australia, in 1997.
From 1989 to 1993, he was with the Department of Electronic Engineering, Tsinghua University, where he was on the research staff and then promoted to a Lecturer. From 1997 to 1999, he was a Senior Member of Scientific Staff, Nortel, Ottawa, Canada. From 1999 to 2000, he was a Faculty Member with the University of Alberta, Edmonton, AB, Canada. From 2000 to 2007, he was with the University of Missouri, Columbia, where he was an Assistant Professor and then an Associate Professor. He is currently a Professor with the Department of Electrical and Computer Engineering, Missouri University of Science and Technology, Rolla (formerly University of Missouri, Rolla). His current research interests include wireless communications, signal processing, and underwater acoustic communications. He is the holder of three U.S. patents. His invented algorithms have been implemented into Nortel’s base station radios after successful technical field trials and network integration.
Dr. Xiao is the Editor-in-Chief of the IEEE Transactions on Wireless Communications, a Fellow of the IEEE, a Member of the Fellow Evaluation Committee of IEEE Communications Society (ComSoc), a Member at Large of IEEE ComSoc Board of Governors, a Distinguished Lecturer of IEEE ComSoc, and a Distinguished Lecturer of the IEEE Vehicular Technology Society. Previously, he served as the founding Area Editor for Transmission Technology of the IEEE Transactions on Wireless Communications; an Associate Editor of the IEEE Transactions on Vehicular Technology, the IEEE Transactions on Circuits and Systems-I, and the international journal of Multidimensional Systems and Signal Processing. He was the Technical Program Chair of the 2010 IEEE International Conference on Communications (ICC), the Lead Co-chair of the 2008 IEEE ICC Wireless Communications Symposium, and a Phy/MAC Program Co-chair of the 2007 IEEE Wireless Communications and Networking Conference. He served as the founding Chair of the IEEE Technical Committee on Wireless Communications, and the Vice-Chair of the IEEE Technical Committee on Personal Communications.
Hequan Wu
