Prof. Kin K. Leung
Tananka Chair Professor of Imperial College, U.K.
Fellow of the Royal Academy of Engineering
Member of Academia
European, IEEE Fellow,
IET Fellow
Imperial College, U.K.
Speech Title: Optimization by Learning and
Federated Learning for Communication Networks
Abstract: Allocation of network
resources to competing demands is an important problem
for efficient design and management of future
communication networks. The complexity of the issue is
compounded by system dynamics in terms of fluctuation
of resource demands and availability. On the future
communication networks, users do not expect them to
support only conventional multi-media services, but
also future artificial intelligence (AI) and
machine-learning (ML) applications for sensing and
communications.
In the first part of this
speech, the speaker will discuss the issue of network
resource allocation. Specifically, he will present a
new machine-learning method by using two Coupled Long
Short-Term Memory (CLSTM) networks to quickly and
robustly produce the optimal or near-optimal resource
allocation, which is modeled as constrained
optimization problem, over a range of system
parameters. Numerical examples for allocation of
network resources will be presented to confirm the
validity of the proposed method.
In the second
part, the speaker will present new approaches to
supporting federated learning (FL) and improving the
learning process by model pruning in communication
networks with resource constraints. The FL technique
learns the model parameters from data collected at
distributed nodes and adapts according to the limited
availability of resources. The key idea of model
pruning is to remove unimportant model parameters to
reduce computation and communication burden and speed
up the learning convergence, while maintaining the
model accuracy. Using real datasets, the
experimentation results show that the proposed
approaches perform near to the optimum or offer
significant performance improvement over other
methods.
Bio: Kin K. Leung
received his B.S. degree from the Chinese University
of Hong Kong, and his M.S. and Ph.D. degrees from
University of California, Los Angeles. He worked at
AT&T Bell Labs and its successor companies in New
Jersey from 1986 to 2004. Since then, he has been the
Tanaka Chair Professor in the Electrical and
Electronic Engineering (EEE), and Computing
Departments at Imperial College in London. He also
served as the Head of Communications and Signal
Processing Group in the EEE Department at Imperial
from 2009 to 2024. His current research focuses on
optimization and machine learning for system design
and control of large-scale communications, computer
and quantum networks. He also works on multi-antenna
and cross-layer designs for wireless networks.
He is a Fellow of the Royal Academy of Engineering,
IEEE Fellow, IET Fellow, and member of Academia
Europaea. He received the Distinguished Member of
Technical Staff Award from AT&T Bell Labs (1994) and
the Royal Society Wolfson Research Merits Award
(2004-09). Jointly with his collaborators, he received
the IEEE Communications Society (ComSoc) Leonard G.
Abraham Prize (2021), the IEEE ComSoc Best Survey
Paper Award (2022), the U.S.–UK Science and Technology
Stocktake Award (2021), the Lanchester Prize Honorable
Mention Award (1997), and several best conference
paper awards. He was an IEEE ComSoc Distinguished
Lecturer (2022-23). He was a member (2009-11) and the
chairman (2012-15) of the IEEE Fellow Evaluation
Committee for the ComSoc. He has served as an editor
for 10 IEEE and ACM journals and chaired the Steering
Committee for the IEEE Transactions on Mobile
Computing. Currently, he is an editor for the ACM
Computing Survey and International Journal of Sensor
Networks.
Speech Title: mmWave Integrated Communications and Sensing
Abstract: Integrated
communications and sensing (ISAC) has become very popular
for the next generation mobile communications. This seminar
will introduce the concept and challenges of using milimeter
wave (mmWave) for ISAC. The latest research results in
mmWave ISAC will be presented in conjunction with hybrid
beamforming and rate splitting multiple access technologies.
Bio: Jiangzhou Wang is a Professor
with the University of Kent, U.K. He has published more than
500 papers and five books. His research interest is in
mobile communications. He was a recipient of the 2022 IEEE
Communications Society Leonard G. Abraham Prize. He was the
Technical Program Chair of the 2019 IEEE International
Conference on Communications (ICC2019), Shanghai, Executive
Chair of the IEEE ICC2015, London, and Technical Program
Chair of the IEEE WCNC2013. He is/was the editor of multiple
international journals, including IEEE Transactions on
Communications from 1998 to 2013. Professor Wang is an
International Member of the Chinese Academy of Engineering
(CAE), a Fellow of the Royal Academy of Engineering (RAEng),
U.K., Fellow of the IEEE, and Fellow of the IET.
Speech Title: Some Thoughts on
6G Modulation
Abstract: I
will talk about some of my own thoughts on 6G modulation. I
think that 6G modulation should be a trade-off between
complexity and performance. Two extremes are OFDM and single
carrier frequency domain equalizer (SC-FDE). I will briefly
introduce vector OFDM (VOFDM) that is in the middle of the
two, and is a natural trade-off of complexity and
performance, in particular for time-varying channels (delay
Doppler channels).
Bio: Xiang-Gen
Xia is the Charles Black Evans Professor, Department of
Electrical and Computer Engineering, University of Delaware,
Newark, Delaware, USA. Dr. Xia was the Kumar’s Chair
Professor Group Professor (guest) in Wireless
Communications, Tsinghua University, during 2009-2011, the
Chang Jiang Chair Professor (visiting), Xidian University,
during 2010-2012, and the World Class University (WCU) Chair
Professor (visiting), Chonbuk National University, South
Korea, during 2009-2013. He received the National Science
Foundation (NSF) Faculty Early Career Development (CAREER)
Program Award in 1997, the Office of Naval Research (ONR)
Young Investigator Award in 1998, the Outstanding Overseas
Young Investigator Award from the National Nature Science
Foundation of China in 2001, and the Information Theory
Outstanding Overseas Chinese Scientist Award from the
Chinese Information Theory Society of Chinese Institute of
Electronics in 2019. Dr. Xia was the General Co-Chair of
ICASSP 2005 in Philadelphia. He is a Fellow of IEEE. His
current research interests include space-time coding, MIMO
and OFDM systems, digital signal processing, and SAR and
ISAR imaging. He is the author of the book Modulated Coding
for Intersymbol Interference Channels (New York, Marcel
Dekker, 2000) and a co-author of the book Array Beamforming
Enabled Wireless Communications (New York, CRC Press, 2023).
Speech Title: Intelligent Signal Sensing and
Recognition Techniques Towards 6G
Abstract: The dawn of 6G wireless
communication introduces a transformative era characterized
by pervasive sensing and advanced intelligent
identification, essential for ensuring physical security.
This keynote speech highlights the integration of Artificial
Intelligence (AI) and Deep Learning (DL) as pivotal in
addressing the dynamic and complex challenges of 6G
networks. We emphasize the role of AI in revolutionizing
signal sensing and recognition. Our discussion centers on
the application of these neural networks in enhancing signal
detection, classification, and Specific Emitter
Identification (SEI). By leveraging gradient-based
optimization techniques, we demonstrate how ANNs can improve
model and algorithm parameterization, leading to a
data-driven approach that surpasses traditional rule-based
systems. This advancement is crucial in the physical layer
of wireless communications, where intelligent signal
recognition plays a key role in maintaining security and
efficiency. We also explore the challenges faced by
conventional model-based methods in the evolving landscape
of 6G communication systems, which are marked by complex
interference and uncertain channel conditions. DL emerges as
a solution, offering innovative strategies for redesigning
baseband module functionalities, including coding/decoding
and detection processes. In conclusion, this keynote
underscores the significance of integrating intelligent
signal sensing and recognition with DL technologies in 6G
networks. This approach not only enhances physical security
but also paves the way for a more robust, efficient, and
intelligent wireless communication ecosystem, capable of
meeting the security demands of the future.
Bio: Guan Gui received the Ph.D. degree from the
University of Electronic Science and Technology of China,
Chengdu, China, in 2012. From 2009 to 2014, he joined Tohoku
University as a Research Assistant and a Post-Doctoral
Research Fellow. From 2014 to 2015, he was an Assistant
Professor with Akita Prefectural University, Akita, Japan.
Since 2015, he has been a Professor with the Nanjing
University of Posts and Telecommunications, Nanjing, China.
He has published more than 200 IEEE journals/conference
papers. His recent research interests include intelligence
sensing and recognition, intelligent signal processing, and
physical layer security. Dr. Gui contributions to
intelligent signal analysis and wireless resource
optimization have earned him the title of fellow of the
IEEE, IET, and AAIA. He was a recipient of several Best
Paper Awards, such as ICC 2017, ICC 2014, and VTC
2014-Spring. He received the IEEE Communications Society
Heinrich Hertz Award in 2021, top 2% scientists of the world
by Stanford University from 2021 to 2023, the Clarivate
Analytics Highly Cited Researcher in Cross-Field from 2021
to 2023, the Highly Cited Chinese Researchers by Elsevier
from 2020 to 2023, a member and Global Activities
Contributions Award in 2018, the Top Editor Award of IEEE
Transactions on Vehicular Technology in 2019, the
Outstanding Journal Service Award of KSII Transactions on
Internet and Information System in 2020, the Exemplary
Reviewer Award of IEEE Communications Letters in 2017, the
2012 Japan Society for Promotion of Science (JSPS)
Postdoctoral Fellowships for Foreign Researchers, and the
2018 Japan Society for Promotion of Science (JSPS)
International Fellowships for Overseas Researchers. He was
also selected as the Jiangsu Specially-Appointed Professor
in 2016, the Jiangsu High-Level Innovation and
Entrepreneurial Talent in 2016, and the Jiangsu Six Top
Talent in 2018.