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IEEE/CIC International Conference
on Communications in China
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We are currently preparing following tutorials: 

T1. Recent Advances in Spectrum Sensing and Machine Learning Techniques for Cognitive Radio Networks

Feifei Gao (Tsinghua University), Qihui Wu (PLA University of Science and Technology)

Cognitive radio (CR) is generally defined as an intelligent wireless communication system that is aware of surrounding environment and reacts by adapting the operation parameters in order to maximize user satisfaction. Till now, however, the development of different functionalities or different frameworks of CR is still far from “intelligent” as it originally claimed. For example, despite its importance, the popular spectrum sensing could only detect the binary “on-off” status of primary user (PU). On the other side, FCC has regulated different protection in DTV band for different powered PU in order to cope with imperfect sensing or learning results. Hence a nature step to make the very basic spectrum sensing more “intelligent” is to recognize the power levels of PU, which is generally ignored in the traditional sensing framework. Besides detecting the “on-off” status of PU or its improved version with the power levels, one should try to gain as much useful knowledge as possible about the surrounding environment. A broad interest hence arises recently in applying the machine learning techniques e.g., interference parameters, link quality, even user behaviors. For example, spectrum geolocation database provides an alternative approach to locate spectrum white spaces or holes, which is well recognized as a technically feasible and commercially viable solution in the near future by regulations (such as FCC and Ofcom) and corporations (such as Google and Microsoft). Technically, there are still a number of research challenges and open issues ahead, e.g., How to derive value from massive or big spectrum data that may be from unreliable, untrustworthy, or even malicious spectrum sensors? How to decrease the delay and locate spectrum white spaces or holes in a real-time manner? How to accomplish intelligent decision-making via game learning under uncertain, dynamic and incomplete (UDI) information constraints? How to design efficient learning algorithms to satisfy dynamic user QoE, etc? Machine learning techniques exhibit the potential to provide effective solutions to many of these technical challenges.

Biography of the instructor(s):

Feifei Gao
Associate Professor Professor, Tsinghua University, Beijing, China

Feifei Gao (S’03–M’09–SM’14) received the B.Eng degree from Xi’an Jiaotong University, China, in 2002, the M. Sc degree from McMaster University, Canada, in 2004, and the Ph.D. degree from National University of Singapore, Singapore, in 2007. He was a Research Fellow with the Institute for Infocomm Research (I2R), A*STAR, Singapore, in 2008 and was an Assistant Professor with the School of Engineering and Science, Jacobs University, Bremen, Germany, from 2009 to 2010. In 2011, he joined the Department of Automation, Tsinghua University, Beijing, China, where he is
currently an Associate Professor.

Prof. Gao has authored and coauthored more than 140 refereed IEEE journal and conference proceeding papers, which have been cited more than 1700 times from Google Scholar. He has served as an editor for IEEE Transactions on Wireless Communications, IEEE Wireless Communications Letters, and China Communications, all indexed by SCI. He has also served as Symposium Co-chairs for IEEE GLOBECOM 2014, IEEE VTC Fall 2014, IEEE ICC 2015 etc., and as Technical Program Committee members for many IEEE International Conferences. Prof. Gao’s current research interests include communication theory, signal processing for communications, optimization theory, and their applications in multiple antenna system, relay networks, Cognitive Radio system.

Qihui Wu
Professor Professor, PLA University of Science and Technology, Nanjing, China

Qihui Wu (SM’13) received his B.S.E., M.S. E and Ph.D. degrees in 1994, 1997, and 2000, respectively, from Institute of Communications Engineering, Nanjing, China. From 2003 to 2005, he was a Postdoctoral Research Associate at Southeast University, Nanjing, China. From 2005 to 2007, he was an Associate Professor with the College of Communications Engineering, PLA University of Science and Technology, Nanjing, China, where he is currently a Full
Professor and PhD supervisor. From March 2011 to September 2011, he was an Advanced Visiting Scholar in Stevens Institute of Technology, Hoboken, USA. Prof. Wu has authored and coauthored over 150 refereed IEEE journal and conference proceeding papers. According to Web of Science (access on 12 Feb. 2014), Prof. Wu’s publications rank Top 5 in the field of cognitive radio. Prof. Wu’s current research interests span the areas of wireless communications, networking, signal processing, game theory, and machine learning, with emphasis on system design of software defined radio, cognitive radio, and internet of things.

T2. Fundamental Design of Small Cell Networks

Tony Q.S. Quek (Singapore University of Technology and Design)

With the increase in data traffic driven by a new generation of wireless devices, data is expected to overwhelm cellular network capacity in the future. Heterogeneous cellular networks are a comprehensive approach to provide high cellular network capacity by overlaying conventional macrocell cellular architecture with heterogeneous architectural features such as small cells. Heterogeneous cellular networks are expected to achieve higher data rates and better coverage by exploiting spatial reuse, while retaining at the same time the seamless connectivity and mobility of cellular networks. Inspired by the attractive features and potential advantages of small cell networks, their development and deployment is gaining momentum in the wireless industry and research communities during the last few years. It has also attracted the attention of standardization bodies such as 3GPP. However, small cell networks also come with their own challenges, and there are significant technical issues that still need to be addressed for successful rollout and operation of these networks, especially for hyper-dense deployment scenarios. In this tutorial, we will introduce some of the main challenges in small cell networks and discuss some recent results related to the fundamental understanding and design of small cell networks. In conclusion, we will provide some discussions of future research topics related to this area and how small cell networks play a role in 5G.

Biography of the instructor(s):

Tony Q.S. Quek

Assistant Professor ,Singapore University of Technology and Design, Singapore

Tony Q.S. Quek received the B.E. and M.E. degrees in Electrical and Electronics Engineering from Tokyo Institute of Technology, Tokyo, Japan, respectively. At Massachusetts Institute of Technology, he earned the Ph.D. in Electrical Engineering and Computer Science. Currently, he is an Assistant Professor with the Singapore University of Technology and Design. He is also a scientist at the Institute for Infocomm Research, A*STAR. He has been actively involved in organizing and chairing a number of international conferences and workshops. He is serving as the TPC co-chair for the IEEE CIT in 2014, the IEEE ICCS in 2014, the PHY & Fundamentals Track for IEEE WCNC in 2015, and the Communication Theory Symposium for IEEE ICC in 2015. He is currently an Executive Editorial Committee Member for the IEEE Transactions on Wireless Communications, an Editor for the IEEE Transactions on Communications and the IEEE Wireless Communications Letters. He was Guest Editor for the IEEE Communications Magazine (Special Issue on Heterogeneous and Small Cell Networks) in 2013 and the IEEE Signal Processing Magazine (Special Issue on Signal Processing for 5G Evolution) in 2014. Dr. Quek was honored with the 2008 Philip Yeo Prize for Outstanding Achievement in Research, the IEEE Globecom 2010 Best Paper Award, the 2011 JSPS Invited Fellow for Research in Japan, the CAS Fellowship for Young International Scientists in 2011, the 2012 IEEE William R. Bennett Prize, and the 2013 IEEE SPAWC Best Student Paper Award. He is a senior member of the IEEE.

T3. Full-Duplex Wireless Communication and Networks: Key Technologies and Applications

Lingyang Song (Peking University), Zhu Han (University of Houston)

Almost all currently deployed radios for wireless communications are half-duplex, which transmit and receive signals in two separate/orthogonal channels. With the recent development of full duplex (FD) communication, where a mobile node can send and receive at the same time and the same frequency band, another avenue has opened up for increasing the capacity theoretically twice as high spectral efficiency as a half-duplex radio. Possible applications of FD radios include wireless base stations, wireless relays and personal-area wireless devices.

The tutorial will provide a systematic overview of the foundation and recent development of this promising FD technology, in particular from physical-layer signal processing and radio resource utilization point of view. Then we will illustrate possible applications, and summarize the current state of the art of the theory, key strategies and techniques. To achieve above goals, there are three aspects for this tutorial. First, we will provide literature for the current state of art for the FD hardware in Physical layer. Then, we will illustrate how such FD paradigm will affect the design of other layers. Finally, we study how this will change the perspectives of different networks such as femtocell networks, cognitive radio networks, etc.

Biography of the instructor(s):

Lingyang Song
Professor Professor, Peking University, Beijing, China

Lingyang Song received his PhD from the University of York, UK, in 2007, where he received the K. M. Stott Prize for excellent research. He worked as a
postdoctoral research fellow at the University of Oslo, Norway, and Harvard University, until rejoining Philips Research UK in March 2008. In May 2009, he
joined the School of Electronics Engineering and Computer Science, Peking University, China, as a full professor. His main research interests include
cooperative communications, cognitive radio, physical layer security, and wireless ad hoc/sensor networks. He is co-inventor of a number of patents (standard contributions), and published extensively. He received five paper awards. He is currently on the Editorial Board of IEEE Transactions of Wireless Communications. He was a guest editor of Wireless Communications and Mobile Computing (Wiley Publication), Special Issues on “Emerging Techniques for Wireless Vehicular Communications” and “Innovative Communications for a Better Future”, and a guest editor of Elsevier Computer Communications, Special Issue on “Adaptive Multicarrier Communications and Networks”, a guest editor of EURASIP Journal on Wireless Communications and Networking, Special Issue on “OFDMA Architectures, Protocols, and Application”. Dr. Song is a senior member of IEEE.

Zhu Han
Associate Professor, University of Houston, Texas, USA

Zhu Han received the B.S. degree in electronic engineering from Tsinghua University, in 1997, and the M.S. and Ph.D. degrees in electrical engineering
from the University of Maryland, College Park, in 1999 and 2003, respectively. From 2000 to 2002, he was an R&D Engineer of JDSU, Germantown, Maryland.
From 2003 to 2006, he was a Research Associate at the University of Maryland. From 2006 to 2008, he was an assistant professor in Boise State University,
Idaho. Currently, he is an Assistant Professor in Electrical and Computer Engineering Department at University of Houston, Texas. His research interests include wireless resource allocation and management, wireless communications and networking, game theory, wireless multimedia, and security. Dr. Han is an NSF CAREER award recipient 2010. Dr. Han is an Associate Editor of IEEE Transactions on Wireless Communications since 2010. Dr. Han was the MAC
Symposium vice chair of IEEE Wireless Communications and Networking Conference, 2008. Dr. Han was the Guest Editor for Special Issue on Cooperative Networking Challenges and Applications (IEEE Journal on Selected Areas in Communications) Fairness of Radio Resource Management Techniques in Wireless Networks (EURASIP Journal on Wireless Communications and Networking), and Special Issue on Game Theory (EURASIP Journal on Advances in Signal Processing). Dr. Han is the winner of the 2011 IEEE Communications Society Fred W. Ellersick Prize. Dr. Han is the coauthor for the several papers that won the best paper awards in IEEE Conferences. Dr. Han is an IEEE Fellow since 2014.

T4-1. Advanced Multi-Carrier waveforms towards 5G: from OFDM to its alternatives

Pierre Siohan (Orange Labs), Hao Lin (Orange Labs, B-COM)


OFDM has become an essential technological component in the beginning of the nineties due to its nice features. And it has been adopted in various wired and wireless standards, including leading applications: ADSL, DVB-T, WiFi, Wimax, LTE, etc. However, OFDM leaves room to some potential improvements, particularly with respect to its poor frequency localization. The aim of this tutorial is to provide an overview of the large set of OFDM variants covering the most recent achievements in the related domain. Moreover this tutorial provides a comparison among these candidates from different aspects. For each scheme, we point out the advantages/disadvantages as well as the potential use cases towards 5G mobile system. Most of these alternatives are actively under development in the well-known leading European projects towards 5G, e.g., METIS and 5GNOW.

Biography of the instructor(s):

Pierre Siohan
Orange Labs, Rennes, France

Pierre Siohan (M'94,-SM'99) received the PhD degree from the École Nationale Supérieure des Télécommunications (ENST), Paris, France, in 1989. In 1977 he joined the Centre Commun d’Études de Télédiffusion et Télécommunications (CCETT), Rennes, where his activities were first concerned with the communication theory and its application to the design of broadcasting systems. Between 1984 and 1997, he was in charge of the CCETT Mathematical and Signal Processing Group. Since September 1997, he has been an Expert Member in the R&D division of France Télécom working in the Broadband Wireless Access Laboratory. From September 2001 to September 2003, he took a two-year sabbatical leave, being directeur de recherche with the Institut National de Recherche en Informatique et Automatique (INRIA), Rennes. His current research interests are in the areas of signal processing for communication systems, including wireless and wired systems.

Hao Lin
Orange Labs and B-COM, Rennes, France

Hao Lin (IEEE, M’06) received his Ph.D. degree in communication and electronics from the Ecole Nationale Supérieure des Télécommunications de Paris, France, in 2009. Since 2010, he has been with Orange Labs (Rennes) as a researcher focusing on the physical layer design for wireless communications. From 2012, he has been actively involving in METIS project, a leading European project towards 5G, where he is responsible of the research group for new waveforms, channel coding and advanced transceiver design. Dr. Hao Lin is also a research scientist at B<>COM, a technological research center newly created in 2012, where his main research interests include defining the innovative technologies for 5G mobile systems.

T4-2. Swarm Intelligence: Fundamental Principles and Optimization Approaches

Zhongshan Zhang (University of Science and Technology Beijing)


Inspired by swarm intelligence observed in social species, the artificial self-organized networking (SON) systems are expected to exhibit some intelligent features (e.g., flexibility, robustness, decentralized control, and self-evolution, etc.) that may have made social species so successful in the biosphere. Self-organized networks with swarm intelligence as one possible solution have attracted a lot of attention from both academia and industry. In this tutorial, we first different aspects of bio-inspired mechanisms and examine various algorithms (e.g., pulse-coupled oscillators (PCO)-based synchronization, ant- and/or bee-inspired cooperation and division of labor, immune systems inspired network security and Ant Colony Optimization (ACO)-based multipath routing) that have been applied to artificial SON systems. Then, we give some open research issues in detail.

Biography of the instructor(s):

Zhongshan Zhang
Professor, University of Science and Technology Beijing, Beijing, China

Zhongshan Zhang received the B.E. and M.S. degrees in computer science from the Beijing University of Posts and Telecommunications (BUPT) in 1998 and
2001, respectively, and received Ph.D. degree in electrical engineering in 2004 from BUPT. From Aug. 2004 he joined DoCoMo Beijing Laboratories as an associate researcher, and was promoted to be a researcher in Dec. 2005. From Feb. 2006, he joined University of Alberta, Edmonton, AB, Canada, as a postdoctoral fellow. From Apr. 2009, he joined the Department of Research and Innovation (R&I), Alcatel-Lucent, Shanghai, as a Research Scientist. From Aug. 2010 to Jul. 2011, he worked in NEC China Laboratories, as a Senior Researcher. He is currently a professor of the School of Computer and Communication Engineering in the University of Science and Technology Beijing (USTB). His main research interests include statistical signal processing, self-organized networking, cognitive radio, and cooperative communications.






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