Harbin Institute of Technology Advanced Communications Technologies Forum 2017

Title：Game theory for Big Data Processing

Date and Time: 11：30—13:00, Auguest 8, 2017

Location：ROOM 1013, BUILDING 2A, NO.2 YIKUANG STREET,

HARBIN, HEILONGJIANG, CHINA

Abstract: Modern communication networks are becoming highly virtualized with two-layer hierarchies, in which controllers at the upper layer with tasks to achieve ask a large number of agents at the lower layer to help realize big data processing. In this talk, we combine optimization approaches and game theory to address the tradeoff and convergence issues for incentive mechanism design in hierarchies. Specifically, we propose a multiple-leader multiple-follower (MLMF) game-based alternating direction method of multipliers (ADMM) that incentivizes the agents to perform the controllers’ tasks in order to satisfy the corresponding objectives for both controllers and agents. Both analytical and simulation results verify that the proposed method reaches a hierarchical social optimum and converges at a linear speed. More importantly, the convergence rate is independent of the network size, which indicates that the MLMF game-based ADMM can be used in a network with a very large size for big data processing.

Biography:

Lingyang Song (S’03-M’06-SM’12) 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 research fellow at the University of Oslo, Norway 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 MIMO, cognitive and cooperative communications, security, and big data. Dr. Song wrote 2 text books, “Wireless Device-to-Device Communications and Networks” and “Full-Duplex Communications and Networks” published by Cambridge University Press, UK. He is the recipient of IEEE Leonard G. Abraham Prize in 2016 and IEEE Asia Pacific (AP) Young Researcher Award in 2012. He is currently on the Editorial Board of IEEE Transactions on Wireless Communications. He is an IEEE distinguished lecturer since 2015.

Harbin Institute of Technology Advanced Communications Technologies Forum 2017

Title：The Deep Learning Vision for Heterogeneous Network Traffic Control: Proposal, Challenges, and Future Perspective

Date and Time: 10：00—11:30, Auguest 8, 2017

Location：ROOM 1013, BUILDING 2A, NO.2 YIKUANG STREET,

HARBIN, HEILONGJIANG, CHINA

Abstract:

Recently, deep learning, an emerging machine learning technique, is garnering a lot of research attention in several computer science areas. However, to the best of our knowledge, its application to improve heterogeneous network traffic control which is an important and challenging area for IoT by its own merit has yet to appear because of the difficult challenge in characterizing the appropriate input and output patterns for a deep learning system to correctly reflect the highly dynamic nature of large-scale heterogeneous networks. In this talk, an appropriate input and output characterizations of heterogeneous network traffic will be introduced and a supervised deep neural network system will be proposed. I will describe how our proposed system works and how it differs from traditional neural networks. Also, preliminary results will be discussed and I will demonstrate the encouraging performance of our proposed deep learning system compared to a benchmark routing strategy (Open Shortest Path First (OSPF)) in terms of significantly better signaling overhead, throughput, and delay.

Biography:

Nei Kato is a full professor and the Director of Research Organization of Electrical Communication(ROEC), Tohoku University, Japan. He has been engaged in research on computer networking, wireless mobile communications, satellite communications, ad hoc & sensor & mesh networks, smart grid, IoT, Big Data, and pattern recognition. He has published more than 350 papers in prestigious peer-reviewed journals and conferences. He is the Editor-in-Chief of IEEE Network Magazine(2015.7-), the Associate Editor-in-Chief of IEEE Internet of Things Journal(2013-), and the Chair of IEEE Communications Society Sendai Chapter. He served as a Member-at-Large on the Board of Governors, IEEE Communications Society(2014-2016), a Vice Chair of Fellow Committee of IEEE Computer Society(2016),  a member of IEEE Computer Society Award Committee(2015-2016) and IEEE Communications Society Award Committee(2015-2017). He has also served as the Chair of Satellite and Space Communications Technical Committee(2010-2012) and Ad Hoc & Sensor Networks Technical Committee(2014-2015) of IEEE Communications Society. His awards include Minoru Ishida Foundation Research Encouragement Prize(2003), Distinguished Contributions to Satellite Communications Award from the IEEE Communications Society, Satellite and Space Communications Technical Committee(2005), the FUNAI information Science Award(2007), the TELCOM System Technology Award from Foundation for Electrical Communications Diffusion(2008), the IEICE Network System Research Award(2009), the IEICE Satellite Communications Research Award(2011), the KDDI Foundation Excellent Research Award(2012), IEICE Communications Society Distinguished Service Award(2012), IEICE Communications Society Best Paper Award(2012), Distinguished Contributions to Disaster-resilient Networks R&D Award from Ministry of Internal Affairs and Communications, Japan(2014), Outstanding Service and Leadership Recognition Award 2016 from IEEE Communications Society Ad Hoc & Sensor Networks Technical Committee, Radio Achievements Award from Ministry of Internal Affairs and Communications, Japan (2016) and Best Paper Awards from IEEE ICC/GLOBECOM/WCNC/VTC. Nei Kato is a Distinguished Lecturer of IEEE Communications Society and Vehicular Technology Society. He is a fellow of IEEE and IEICE.

Harbin Institute of Technology Advanced Communications Technologies Forum 2017

Title：Connected Vehicles for Modern Transportation Systems

Date and Time: 8：30—10:00, Auguest 8, 2017

Location：ROOM 1013, BUILDING 2A, NO.2 YIKUANG STREET,

HARBIN, HEILONGJIANG, CHINA

Abstract:Modern society depends on faster, safer, and environment friendly transportation system. Vehicular communications network in terms of vehicle to vehicle, vehicle to infrastructure, vehicle to pedestrian, vehicle to cloud, and vehicle to sensor, provides a solution to modern transportation. In this talk, we first introduce the all connected vehicles. We then present the challenges and scientific research issues. of vehicular communications network. As examples, we show how to utilize mobility characteristics of vehicles to derive the achievable asymptotic throughput capacity in VANETs, and how to develop the charging strategies based on mobility of electric vehicles to improve the electricity utility, in order to approach load capacities of charging stations in VANET-enhanced smart grid. We conclude the talk by discuss the future autonomous driving.

Biography:

Xuemin (Sherman) Shen is a University Professor  and Associate Chair for Graduate Studies, Department of Electrical and Computer Engineering, University of Waterloo, Canada. Dr. Shen’s research focuses on wireless resource management, wireless network security, wireless body area networks, smart grid and vehicular ad hoc and sensor networks. He is the Editor-in-Chief of IEEE IoT Journal. He serves as the General Chair for Mobihoc’15, the Technical Program Committee Chair for IEEE GC’16, IEEE Infocom’14, IEEE VTC’10, the Symposia Chair for IEEE ICC’10, the Technical Program Committee Chair for IEEE Globecom’07, the Chair for IEEE Communications Society Technical Committee on Wireless Communications. Dr. Shen was an elected member of IEEE ComSoc BoG, the chair of IEEE ComSoc Distinguish Lecturer selection committee, and a member of IEEE ComSoc Fellow evaluation committee. Dr. Shen received the Excellent Graduate Supervision Award in 2006, and the Premier’s Research Excellence Award (PREA) in 2003 from the Province of Ontario, Canada. Dr. Shen is a registered Professional Engineer of Ontario, Canada, an IEEE Fellow, an Engineering Institute of Canada Fellow, a Canadian Academy of Engineering Fellow, a Royal Society of Canada Fellow, and a Distinguished Lecturer of IEEE Vehicular Technology Society and Communications Society.

Title：Human-Like Driving: Empirical Decision-Making System for Autonomous Vehicles

Date and Time: 15：30—17:00, July 31, 2017

Location：ROOM 1013, BUILDING 2A, NO.2 YIKUANG STREET,

HARBIN, HEILONGJIANG, CHINA

Abstract:

Autonomous vehicle, as an emerging and rapidly growing field, has received extensive attention for its futuristic driving experiences. Although the rise of depth sensor technologies and machine learning methods have given a huge boost to self-driving research, existing autonomous driving vehicles do meet with several avoidable accidents during their road testing. The major cause is the misunderstanding between self-driving systems and human drivers. To solve this problem, we propose a human-like driving system in the paper to give autonomous vehicles the ability to make decisions like a human. In our method, a Convolutional Neural Network (CNN) model is used to detect, recognize and abstract the information in the input road scene, which is captured by the on-board sensors. And then a decision-making system calculates the specific commands to control the vehicles based on the abstractions. The most significant advantage in our work is that the proposed method can well adapt to real-life road conditions, in which a massive number of human drivers exist. In addition, we build our perception system only on the depth information, and avoid the unstable RGB data. Simulations demonstrate that our approach is robust and efficient, and outperforms the state-of-the-art in several related tasks.

Biography: Mianxiong Dong received B.S., M.S. and Ph.D. in Computer Science and Engineering from The University of Aizu, Japan. He is currently an Associate Professor in the Department of Information and Electronic Engineering at the Muroran Institute of Technology, Japan. Prior to joining Muroran-IT, he was a Researcher at the National Institute of Information and Communications Technology (NICT), Japan. He was a JSPS Research Fellow with School of Computer Science and Engineering, The University of Aizu, Japan and was a visiting scholar with BBCR group at University of Waterloo, Canada supported by JSPS Excellent Young Researcher Overseas Visit Program from April 2010 to August 2011. Dr. Dong was selected as a Foreigner Research Fellow (a total of 3 recipients all over Japan) by NEC C&C Foundation in 2011. His research interests include Wireless Networks, Cloud Computing, and Cyber-physical Systems. He has received best paper awards from IEEE HPCC 2008, IEEE ICESS 2008, ICA3PP 2014, GPC 2015, IEEE DASC 2015 and IEEE VTC 2016-Fall. Dr. Dong serves as an Editor for IEEE Communications Surveys and Tutorials, IEEE Network, IEEE Wireless Communications Letters, IEEE Cloud Computing, IEEE Access, and Cyber-Physical Systems (Taylor & Francis), as well as a leading guest editor for ACM Transactions on Multimedia Computing, Communications and Applications (TOMM), IEEE Transactions on Emerging Topics in Computing (TETC), IEEE Transactions on Computational Social Systems (TCSS), Peer-to-Peer Networking and Applications (Springer) and Sensors, as well as a guest editor for Concurrency and Computation: Practice and Experience (Wiley), IEEE Access, Peer-to-Peer Networking and Applications (Springer), IEICE Transactions on Information and Systems, and International Journal of Distributed Sensor Networks. He has been serving as the Vice Chair of IEEE Communications Society Asia/Pacific Region Meetings and Conference Committee, Program Chair of IEEE SmartCity 2015 and Symposium Chair of IEEE GLOBECOM 2016, 2017. Dr. Dong was a research scientist with A3 Foresight Program (2011-2016) funded by Japan Society for the Promotion of Sciences (JSPS), NSFC of China, and NRF of Korea. He is the recipient of IEEE TCSC Early Career Award 2016.

Title：Eyes in the Dark: Distributed Scene Understanding for Disaster Management

Date and Time: 13：30—15:30, July 31, 2017

Location：ROOM 1013, BUILDING 2A, NO.2 YIKUANG STREET,

HARBIN, HEILONGJIANG, CHINA

Abstract:

Robotic is a great substitute for human to explore the dangerous areas, and will also be a great help for disaster management. Although the rise of depth sensor technologies gives a huge boost to robotic vision research, traditional approaches cannot be applied to disaster-handling robots directly due to some limitations. In this paper, we focus on the 3D robotic perception, and propose a view-invariant Convolutional Neural Network (CNN) Model for scene understanding in disaster scenarios. The proposed system is highly distributed and parallel, which is of great help to improve the efficiency of network training. In our system, two individual CNNs are used to, respectively, propose objects from input data and classify their categories. We attempt to overcome the difficulties and restrictions caused by disasters using several specially-designed multi-task loss functions. The most significant advantage in our work is that the proposed method can learn a view-invariant feature with no requirement on RGB data, which is essential for harsh, disordered and changeable environments. Additionally, an effective optimization algorithm to accelerate the learning process is also included in our work. Simulations demonstrate that our approach is robust and efficient, and outperforms the state-of-the-art in several related tasks.

Biography: Kaoru Ota was born in Aizu-Wakamatsu, Japan. She received M.S. degree in Computer Science from Oklahoma State University, USA in 2008, B.S. and Ph.D. degrees in Computer Science and Engineering from The University of Aizu, Japan in 2006, 2012, respectively. She is currently an Assistant Professor with Department of Information and Electronic Engineering, Muroran Institute of Technology, Japan. From March 2010 to March 2011, she was a visiting scholar at University of Waterloo, Canada. Also she was a Japan Society of the Promotion of Science (JSPS) research fellow with Kato-Nishiyama Lab at Graduate School of Information Sciences at Tohoku University, Japan from April 2012 to April 2013. Her research interests include Wireless Networks, Cloud Computing, and Cyber-physical Systems. Dr. Ota has received best paper awards from ICA3PP 2014, GPC 2015, IEEE DASC 2015, IEEE VTC 2016-Fall and FCST 2017. She is an editor of IEEE Transactions on Vehicular Technology (TVT), IEEE Communications Letters, Peer-to-Peer Networking and Applications (Springer), Ad Hoc & Sensor Wireless Networks, International Journal of Embedded Systems (Inderscience) and Smart Technologies for Emergency Response & Disaster Management (IGI Global), as well as a guest editor of ACM Transactions on Multimedia Computing, Communications and Applications (leading), IEEE Communications Magazine, IEEE Network, etc. Also she was a guest editor of IEEE Wireless Communications (2015), IEICE Transactions on Information and Systems (2014), and Ad Hoc & Sensor Wireless Networks (Old City Publishing) (2014). She was a research scientist with A3 Foresight Program (2011-2016) funded by Japan Society for the Promotion of Sciences (JSPS), NSFC of China, and NRF of Korea.

Title：Joint Optimization of Computation and Communication Power in Multi-user Massive MIMO Systems

Date and Time: 9:00AM, July 21, 2017

Location：ROOM 1013, BUILDING 2A, NO.2 YIKUANG STREET,

HARBIN, HEILONGJIANG, CHINA

Abstract:

With the growing interest in the deployment of massive multiple-input-multiple-output (MIMO) systems and millimeter wave technology for fifth generation (5G) wireless systems, the computation power to the total power consumption ratio is expected to increase rapidly due to high data traffic processing at the baseband unit. Therefore in this paper, a joint optimization problem of computation and communication power is formulated for multi-user massive MIMO systems with partially-connected structures of radio frequency (RF) transmission systems. To optimize the energy efficiency of multi-user massive MIMO systems, an upper bound on energy efficiency is derived. Considering the constraints on partially-connected structures, a suboptimal solution consisting of baseband and RF precoding matrices is proposed to approach the upper bound on energy efficiency of multi-user massive MIMO systems. Furthermore, an oPtimized Hybrid precOding with computation and commuNication powEr (PHONE) algorithm is developed to realize the joint optimization of computation and communication power. Simulation results indicate that the proposed algorithm improves energy and cost efficiencies and the maximum power saving is achieved by 52.44% for multi-user massive MIMO systems with partially-connected structures.

Xiaohu Ge received the Ph.D. degree in communication and information engineering from Huazhong University of Science and Technology (HUST), Wuhan, China, in 2003. He is currently a Full Professor with the School of Electronic Information and Communications, HUST. He is an Adjunct Professor with the Faculty of Engineering and Information Technology, The University of Technology Sydney (UTS), Sydney, N.S.W., Australia. He is the founding director of China International Joint Research Center of Green Communications and networking. He has authored more than 150 papers in refereed journals and conference proceedings and has been granted about 15 patents in China. His research interests include mobile communications, traffic modeling in wireless networks, green communications, and interference modeling in wireless communications. He is leading several projects funded by NSFC, China MOST, and industries. He is taking part in several international joint projects, such as the EU FP7-PEOPLE-IRSES: project acronym WiNDOW (grant no. 318992) and project acronym CROWN (grant no. 610524). Dr. Ge is an IET Fellow. He has been actively involved in organizing more the ten international conferences since 2005. He served as the General Chair for the 2015 IEEE International Conference on Green Computing and Communications (IEEE GreenCom). He serves as an Editor for the IEEE Transactions on Green Communications and Networking.

At 2:00 pm on September 2 of 2014, the 2014 annual meeting of IEEE Communication Society Harbin Chapter was held at conference room #1011 of building 2A in Science Park of Harbin Institute of Technology (HIT). The meeting was presided over by the Chair of Harbin Chapter, Professor Weixiao Meng from School of Electronics and Information Engineering, HIT. Prof. Weixiao Meng introduced the composition and development of IEEE Communications Society Harbin Chapter as well as its work situation in the past three years, and noticed the activity plan in next year. During the conference, more than 40 attending members voted on the volunteer positions of chapter chair, vice chair and secretary, etc. Professor Weixiao Meng was elected as the chapter chair again, vice chairman was vacant, and Dr. Shuai Han, the teacher from School of Electronics and Information Engineering, HIT was elected as the secretary. The meeting also invited IEEE Fellow, international famous scholar, distinguished Professor, Hsiao-Hwa Chen as the conference honored guest. Prof. Chen gave a lecture for the conference. He explained the IEEE organization and operating principle, and the basic situation of IEEE ComSoc (IEEE Communications Society) as well as its meetings、journals and prizes, etc, and how to improve themselves in the ComSoc volunteer activities. Then attending members interacted with Prof. Chen through the form of question and answer. Finally, conference gave exquisite gifts with chapter logo to all attending members. The gifts were funded by ComSoc, designed and produced by Harbin Chapter.