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EAI International Conference on Machine Learning and Intelligent Communications

August 5–6, 2017 | Weihai, People's Republic of China

Title: Intelligent Ultra Dense Networks: Principles and Technologies


Haijun Zhang, Full Professor

University of Science and Technology Beijing, China.


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Haijun Zhang (M'13, SM'17) is currently a Full Professor in University of Science and Technology Beijing, China. He was a Postdoctoral Research Fellow in Department of Electrical and Computer Engineering, the University of British Columbia (UBC), Vancouver Campus, Canada. He received his Ph.D. degree in Beijing University of Posts Telecommunications (BUPT). From 2011 to 2012, he visited Centre for Telecommunications Research, King's College London, London, UK, as a Visiting Research Associate. Dr. Zhang has published more than 80 papers and authored 2 books. He serves as Editor of IEEE 5G Tech Focus, Journal of Network and Computer Applications, Wireless Networks, Telecommunication Systems, and KSII Transactions on Internet and Information Systems, and serves/served as a leading Guest Editor for IEEE Communications Magazine, IEEE Transactions on Emerging Topics in Computing and ACM/Springer Mobile Networks & Applications. He serves/served as General Co-Chair of 5GWN'17 and GameNets'16, Track Chair of ScalCom2015, Symposium Chair of the GameNets'14, and Co-Chair of Workshop on 5G Ultra Dense Networks in ICC 2017, Co-Chair of Workshop on 5G Ultra Dense Networks in Globecom 2017, and Co-Chair of Workshop on LTE-U in Globecom 2017. He has served as a TPC member in a numerous international conferences. Prof. Zhang received the IEEE ComSoc Young Author Best Paper Award in 2017.


Yong Wang



Inverse synthetic aperture radar imaging of target with complex motion


Radar imaging has the characteristic of all-weather, day/night and long range, and has great value in civilian and military applications. Due to the dissimilarity of the Radar’s working mechanism and imaging mode, imging Radar can be divided into two categories-inverse synthetic aperture Radar (ISAR) and synthetic aperture Radar (SAR). In ISAR imaging, the echo after motion compensation can be characterized as the model of multi-component polynomial phase signal (PPS), and this is a typical kind of nonstationary signals. When implement the ISAR image of a target, this model can be approximated logically according to the movement character of the target, and the quality of the Radar images lies on the signal processing technique. That is to say, the quality of the Radar images can be improved greatly by the signal processing methods. This report divides the echo of the target into three categories from the aspects of parameter estimation and time frequency distribution, they are the constant amplitude polynomial phase signal (PPS) model, time varying amplitude PPS model and directly obtaining the time frequency structure of the signal based on the time frequency methods. New algorithms are presented in signal processing corresponding to the three models above in order to improve the quality of the Radar images.


Yong Wang was born in 1979. He received the B. S. degree and M. S. degree from Harbin Institute of Technology (HIT), Harbin, China, in 2002 and 2004, respectively, both in electronic engineering. He received the Ph. D. degree in information and communication engineering from HIT in 2008.

He is currently a Professor with the institute of electronic engineering technology in HIT. His main research interests are in the fields of time frequency analysis of nonstationary signal, radar signal processing, and their application in synthetic aperture radar (SAR) imaging.

Dr. Yong Wang has published more than 60 papers, most of them appeared in the journals of IEEE Trans. On GRS, IET Signal Processing, Signal Processing, etc. He received the Program for New Century Excellent Talents in University of Ministry of Education of China in 2012, and the Excellent Doctor’s Degree nomination Award in China in 2010.


National Instruments China, District Manager of Shandong&Henan, Lifan Liu

Lifan Liu got the Master degree of Fudan University on Electronics and Systems, and joined National Instrument in 2009. He ever worked as Application Engineer and Field Engineer to support user projects related to Wireless Channel, SDR Research, Radar System Prototype, Wireless ATE, RF Instrument, etc. Now he provides technical consulting and support service for customers in Universities and Industries.





Keynote Abstract”

From Concept to Prototype: NI software defined radio platform and 5G overview

National Instruments is collaborating with top researchers focused on 5G wireless communications. The graphical system design approach combines LabVIEW Communications System Design Software with SDR Platform to help researchers innovate faster. By using this approach, engineers can reduce the time form theory to results by testing their designs in a real-world environment. In this session, you will learn the key elements of NI SDR platform and four potential technologies to make 5G a reality, which include massive MIMO, densification of network, new waveforms and mmWave communications.