
Biography:
Evgeny Khorov received his BS and MS degrees with honors
from Moscow Institute of Physics and Technology (MIPT)
in 2008 and 2010, respectively, the Ph.D. degree in
Telecommunications from Institute for Information
Transmission Problems of the Russian Academy of Sciences
(IITP RAS) in 2012, and the D.Sc. degree in
Telecommunications from MIPT in 2022. In 2015 he studied
Wireless Internet of Things as a Visiting Research
Fellow in King's College London. Currently, Evgeny
Khorov is the Head of Wireless Networks Lab established
within a Megagrant Project at IITP RAS. Also, he has led
the Intelligent Telecommunication Systems Lab at MIPT
and the Telecommunication Systems Lab at Higher School
of Economics (HSE). Evgeny Khorov has developed numerous
mathematical models of networking protocols and designed
several algorithms and protocols described in over 200
papers, some of which received Best Demo Award from ACM
Mobihoc (2022), Best Paper Awards from IEEE ISWCS
(2012), Elsevier Computer Communications (2018), and
IEEE PIMRC (2019). Evgeny Khorov has also received the
Moscow Government Prize for Young Scientists (2013),
Russian Government Prize in Science and Technology for
Young Scientists (2016), and Scopus Award Russia (2018).
Evgeny has led many national and international
projects sponsored by academia foundations (RSF, RFBR,
Ministry of Science and Higher Education) and industry.
For breakthrough results of the joint industrial
projects, he was awarded as the Best Cooperation Project
Leader many times. Evgeny Khorov is also a voting member
and contributor of IEEE 802.11 that develops and
standardizes Wi-Fi. He designed several improvements
included in the 802.11ax standard, aka Wi-Fi 6. He also
initiated activities in 802.11 towards the support of
real-time applications, which is currently a target for
802.11be, aka Wi-Fi 7.
Evgeny Khorov serves as
the Editor-in-Chief of “Problems of Information
Transmissions” since 2024. Also, he is a recipient of
the Ad Hoc Networks Editor ot the Year 2020 Award.
Evgeny gives keynotes & tutorials and participates in
panels at large conferences (incl. IEEE BlackSeaCom 2024
and 2017, EnT 2023, DCCN 2023, IEEE Standards Summit
2022, IEEE PIMRC 2019 and 2017, IEEE Globecom 2017, IEEE
ICC 2016, ISWCS 2014, NEW2AN 2018 and 2021). He is a TPC
Chair of the IEEE Globecom 2018 Workshop on Cloudified
Architectures for 5G and beyond Systems, IEEE
BlackSeaCom 2019, Executive Chair of WiFlex 2013. He
serves as an expert of Russian Academy of Sciences,
member of the Telecommunication Scientific Counsil of
the Russian Academy of Sciences, and a member of Expert
Council of the Russian Science Foundation, and
Vice-Chair of IEEE Russia.

Biography:
Liang Wu (Senior Member, IEEE) received his B.S. (2007),
M.S. (2010) and Ph.D. (2013) degrees all from School of
Information Science and Engineering, Southeast
University, Nanjing, China. From Sept. 2011 to Mar.
2013, he was with the School of Electrical Engineering
and Computer Science, Oregon State University as a
visiting Ph.D. student. In Sept. 2013, he joined the
National Mobile Communications
Research Laboratory,
Southeast University, Nanjing China. Since Apr. 2024, he
has been a full professor in Southeast University. His
research interests include multiple-antenna techniques,
interference coordination, optical wireless
communication systems, and wireless localization
systems.

Speech
Title: Architectures of Next Generation Wireless
Networks
Abstract: Internet Quality of Service
(QoS) mechanisms are expected to enable wide spread use
of real time services. New standards and new
communication architectures allowing guaranteed QoS
services are now developed. We will cover the issues of
QoS provisioning in heterogeneous networks, Internet
access over 5G networks and discusses most emerging
technologies in the area of networks and
telecommunications such as IoT, SDN, Edge Computing and
MEC networking. We will also present routing, security,
baseline architectures of the inter-networking protocols
and end-to-end traffic management issues.
Biography: Pascal Lorenz ([email protected]) received his
M.Sc. (1990) and Ph.D. (1994) from the University of
Nancy, France. Between 1990 and 1995 he was a research
engineer at WorldFIP Europe and at Alcatel-Alsthom. He
is a professor at the University of Haute-Alsace,
France, since 1995. His research interests include QoS,
wireless networks and high-speed networks. He is the
author/co-author of 3 books, 3 patents and 200
international publications in refereed journals and
conferences. He was Technical Editor of the IEEE
Communications Magazine Editorial Board (2000-2006),
IEEE Networks Magazine since 2015, IEEE Transactions on
Vehicular Technology since 2017, Chair of IEEE ComSoc
France (2014-2020), Financial chair of IEEE France
(2017-2022), Chair of Vertical Issues in Communication
Systems Technical Committee Cluster (2008-2009), Chair
of the Communications Systems Integration and Modeling
Technical Committee (2003-2009), Chair of the
Communications Software Technical Committee (2008-2010)
and Chair of the Technical Committee on Information
Infrastructure and Networking (2016-2017), Chair of
IEEE/ComSoc Satellite and Space Communications Technical
(2022-2023), IEEE R8 Finance Committee (2022-2023), IEEE
R8 Conference Coordination Committee (2023). He has
served as Co-Program Chair of IEEE WCNC'2012 and
ICC'2004, Executive Vice-Chair of ICC'2017, TPC Vice
Chair of Globecom'2018, Panel sessions co-chair for
Globecom'16, tutorial chair of VTC'2013 Spring and
WCNC'2010, track chair of PIMRC'2012 and WCNC'2014,
symposium Co-Chair at Globecom 2007-2011, Globecom'2019,
ICC 2008-2010, ICC'2014 and '2016. He has served as
Co-Guest Editor for special issues of IEEE
Communications Magazine, Networks Magazine, Wireless
Communications Magazine, Telecommunications Systems and
LNCS. He is associate Editor for International Journal
of Communication Systems (IJCS-Wiley), Journal on
Security and Communication Networks (SCN-Wiley) and
International Journal of Business Data Communications
and Networking, Journal of Network and Computer
Applications (JNCA-Elsevier). He is senior member of the
IEEE, IARIA fellow and member of many international
program committees. He has organized many conferences,
chaired several technical sessions and gave tutorials at
major international conferences. He was IEEE ComSoc
Distinguished Lecturer Tour during 2013-2014.

Biography: Si-Ping Gao (Senior
Member, IEEE) received the B.Eng., M.Eng. and D.Eng.
degrees in electronic engineering from the Nanjing
University of Aeronautics and Astronautics (NUAA),
Nanjing, China, in 2007, 2009, and 2013, respectively.
From 2010 to 2012, he was a Doctoral Exchange
Student at the Nanyang Technological University,
Singapore, funded by the Chinese Scholarship Council. He
joined the High Performance Computing (IHPC), A*STAR,
Singapore, first as a Scientist I and was promoted to
Scientist II on a fast track. In 2017, he served as a
Visiting Scholar at the University of L’Aquila, Italy.
From 2017 to 2022, he was a Research Fellow in the
Department of Electrical and Computer Engineering (ECE),
National University of Singapore (NUS), Singapore.
Thereafter, he joined AMD, Singapore, as a Senior SI/PI
Engineer, concurrently holding a position of Adjunct
Assistant Professor at ECE, NUS. Since 2024, he has been
with the College of Integrated Circuits, NUAA, as a Full
Professor. He became the Head of Department of Analog
Integrated Circuit and System and the Director of Center
for Advanced RF IC and System, NUAA in 2025. He has more
than 15 years of research experience in the area of
EMC/SI/PI. He has authored more than 110 refereed
papers/book chapters. He holds several patents. His
research interests include computational
electromagnetics, EMC/EMI, SI/PI for high-speed
electronics, chiplet interconnection, microwave ferrite
devices, novel 2D shielding materials, and
next-generation on-chip plasmonic interconnects.
He
received the Young Professional Award from the IEEE EMC
Society (EMC-S) in 2021, the IEEE Signal and Power
Integrity Young Investigator Training Program Award in
2017, the URSI GASS Young Scientist Award in 2017, and
the Outstanding Young Scientist Award at the 2018 Joint
IEEE EMC & APEMC Symposium. He won the Best Symposium
Paper Award from the Asia-Pacific International
Symposium on Electromagnetic Compatibility (APEMC) in
2016 and the Best Paper Award from the IEEE MTT-S
International Microwave Workshop Series on Advanced
Materials and Processes for RF and THz Applications
(IMWS-AMP) in 2020. He served as the TPC Chair of
ACES-China 2026 and IEEE MTT-S IMWS-AMP 2025, a TPC
Co-chair of IEEE MTT-S IMWS-AMP 2021 & 2026, a TPC
Co-chair of IEEE International Workshop on Advanced
Interconnects (WAI 2025), the Technical Paper Chair of
APEMC 2022. He is a Distinguished Lecturer of IEEE EMC-S
(2026-2027) and a Guest Editor of IEEE TRANSACTIONS on
MICROWAVE THEORY and TECHNIQUES (2025) and a
Distinguished Reviewer of IEEE TRANSACTIONS ON
ELECTROMAGNETIC COMPATIBILITY (2023, 2024). He has
served the IEEE EMC Singapore Chapter since 2016 in
various roles, including Secretary, Treasurer, and
Chapter Chair. Under his leadership, the Chapter won
IEEE EMC-S Chapter-of-the-Year Award in 2021.

Biography: Yanli Xu, a professor and associate Dean at the School of Information Engineering, Shanghai Maritime University. She graduated from Southeast University in 2012 with a Information and Communication Engineering Ph. D. degree. Her current research interests focused on integrated space-air-ground-sea communication technology and edge computing. These technologies provide high reliability and low delay information transmission for Marine development, environment monitoring, shipping and marine security. Dr. Xu has published over 40 top-quality academic papers, and she has served as guest editor or TPC chair for well-known journals and conferences in the field. She has also been honored as Special Expert for Talent Work in Liaoning Province and the Pearl Plan of Shanghai Pudong New Area.

Biography: Jingjing Cui (SM’18) is a Professor at the School of Information Science and Technology, Southwest Jiaotong University. She previously worked as a Research Scientist at Quantinuum in London and held research positions at Southampton, Queen Mary University of London, and Lancaster. Her research interests include classical and quantum optimization, airtificial intelligence algorithms for wireless communications, and quantum information technology.

Biography: Zhimin Chen received the Ph.D. degree from the School of Information Science and Engineering, Southeast University, Nanjing, China, in 2015. She is currently a professor at Shanghai Dianji University and the Vice Dean of the School of Electronic Information. From 2021 to 2022, she was a visiting scholar with the Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong. Her research interests include array signal processing, vehicle communications, and millimeter-wave communications.

Biography: Qiong Wu (Senior
Member, IEEE) received the Ph.D. degree in information
and communication engineering from National Mobile
Communications Research Laboratory, Southeast
University, Nanjing, China, in 2016. From 2018 to 2020,
he was a postdoctoral researcher with the Department of
Electronic Engineering, Tsinghua University, Beijing,
China. He is currently an associate professor with the
School of Internet of Things Engineering, Jiangnan
University, Wuxi, China.
Dr. Wu is a Senior
Member of IEEE and China Institute of Communications. He
has published over 90 papers in high impact journals and
conferences, and authorized over 30 patents. He was
elected as one of the world's top 2% scientists in 2024
and 2022 by Stanford University. He has received the
young scientist award for ICCCS'24 and ICITE’24. He won
the high-impact paper of Chinese Journal of Electronics
award. He has been awarded the National Academy of
Artifical Intelligence (NAAI) Certified AI Senior
Engineer, and was the excellent reviewer for Computer
Networks in 2024. He has severed as the editorial board
member, early career editorial board member, (lead)
guest editor for over 10 Journals, as well as the TPC
chair, Special Session Chair, workshop chair, TPC member
and session chair for over 20 international Conferences.
His current research interest focuses on vehicular
networks, autonomous driving communication technology,
and machine learning.

Biography: Xiaojun received the B.Eng degrees in Information Engineering from Huazhong University of Science and Technology, Wuhan, P.R. China. He also obtained his MPhil. Degree in Electrical and Electronic Engineering from the Hong Kong University of Science and Technology. Then, he received his Ph.D. degree in the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology. Starting from October 2008 till now, he has joined the School of Electronic Information and Communications, Huazhong University of Science and Technology, P.R. China. He is now an associate professor in the School of Electronic Information and Communications, Huazhong University of Science and Technology. Between September 2005 and September 2007, he worked on P2P networking in the Department of Computer and Information Science, Polytechnic University. He is co-author (with Yong Liu and Keith W. Ross) of the best paper in multimedia communications for 2008 by the Multimedia Communications Technical Committee of the IEEE Communications Society. He has been an internationally certified ISW facilitator since Jan. 2021. His current research interests include Artificial Intelligence Enabled Networking, Intelligent Healthcare, Robotic Applications, LLM Applications.

Speech Title: Secured Short
Packet xURLLC Technologies for 6G Mission-Critical
Applications
Abstract: Sixth-generation (6G)
mission-critical applications such as low altitude
economy, cooperative intelligent transportation systems
(C-ITS), and industrial control impose unprecedented
ultra-reliable low-latency communication (xURLLC)
requirements on short packet communications (SPC), which
invalidates the asymptotic Shannon capacity theory
assuming infinite block-length. Existing wireless
technologies also fail to address the coexistence
challenges of ultra-low latency, ultra-high reliability,
massive connectivity, and stringent security in 6G
mission-critical applications.
In this talk, we
present a comprehensive suite of secured SPC xURLLC
technologies tailored for 6G mission-critical
applications. We first introduce the precise channel
estimation and tracking method and the low-complexity
Weibull channel model to enable accurate and efficient
channel state information (CSI) acquisition in
high-mobility satellite-ground integrated networks.
Then, we develop novel channel coding schemes, i.e.,
sparse vector coding with minimal CSI, partitioned
analog fountain codes (PAFC) for rate-adaptive
transmission, and iterative error reduction decoding
(IERD) for low-complexity linear block code decoding.
Furthermore, we design the sparse code multiple access
(SCMA) codebook to support massive concurrent
connections with improved spectral efficiency. Finally,
we introduce endogenous security mechanisms to address
security threats in xURLLC systems. This talk provides
both theoretical and engineering insights for the
development of 6G mission-critical applications.
Biography: Di Zhang is a Senior Member of the Chinese
Institute of Command and Control, the China Institute of
Communications, the Chinese Institute of Electronics and
IEEE.
He has been honored with the Second Prize of
Henan Provincial Scientific and Technological
Achievements, 2025; the Second Prize of Henan Provincial
Science and Technology Progress Award, 2024; the First
Prize of Henan Provincial Science and Technology
Progress Award, 2022 and Second Prize of the
Sichuan-Chongqing Science and Technology Conference,
2021.
His primary research interests lie in short
packet communication technologies and their
applications. He is currently serving as an editorial
board member or guest editor for over 10 journals,
including Aerospace Technology, Communications
Technology, KSII Transactions on Internet and
Information Systems, and IEEE Wireless Communications.
He was the co-chair of the Communication Theory
Symposium at the 9th IEEE/CIC International Conference
on Communications in China (ICCC), and has led the
organization of multiple international academic
workshops on short packet communications at flagship
conferences including ICASSP 2023 and ICC 2022.

Biography: Shuai Ma received the B.S. and Ph.D. degrees in communication and information systems from Xidian University, Xi'an, China, in 2009 and 2016, respectively. From 2014 to 2015, he was a Visiting Scholar with the Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA. From 2016 to 2019, he has been an associate Professor with the School of Information and Control Engineering, at the China University of Mining and Technology, Xuzhou, China. From 2019 to 2022, he worked as a Postdoctoral Fellow with Telecom Paris, France. Since 2023, he has been an Associate Researcher at Peng Cheng Laboratory, Shenzhen, China. His research interests include semantic communications, visible light communications, and network information theory.

Speech Title: Max-Min SINR
Beamforming with BER Guarantee for RIS-Aided AFDM-NOMA
Uplink under Mobile Interference over Doubly-Dispersive
Channels
Abstract: Affine frequency division
multiplexing (AFDM) provides robust performance in
high-mobility communication scenarios, yet it suffers
from severe path-loss degradation in obstructed
doubly-dispersive links, especially under
non-line-of-sight (NLoS) conditions and in the presence
of a mobile interference source (MIS). This work
proposes a reconfigurable intelligent surface
(RIS)-aided, non-orthogonal multiple access (NOMA)-based
multi-user (MU) AFDM uplink network to mitigate these
impairments. A max-min signal-to-interference-plus-noise
ratio (SINR) beamforming framework with a bit error rate
(BER) guarantee is formulated to jointly optimize RIS
phase shifts, power allocation, and precoding. To solve
this mixed-integer nonlinear programming problem, we
develop an alternating optimization (AO) algorithm: the
precoding and power allocation subproblem is convexified
via quadratic transform and successive convex
approximation (SCA), while the RIS phase shifts admit a
closed-form solution via a coordinate-ascent strategy
based on weighted phase alignment. Extensive numerical
simulations validate our analysis, showing that the
proposed strategy not only achieves superior max-min
SINR performance and significantly improves system
reliability (i.e., BER) compared to existing benchmarks,
but also requires much lower SINR to reach the same BER
level.
Biography: Tianming (Tian-Ming) Ma received Ph.D. degree from Shanghai institute of Microsystem and Information Technology (SIMIT), Chinese Academy of Sciences (CAS), Shanghai, China in 2012. He was a post-doctoral researcher and obtained the first-class general financial grant from the China Postdoctoral Science Foundation in Tsinghua University, Beijing, China from 2012 to 2014. Now he is an associate professor in the School of Electronic & Electrical Engineering (SEEE), Shanghai University of Engineering Science (SUES), Shanghai, China and serve as the leader of the intelligent wireless perception research team in SEEE. He has authored/co-authored over 60 journal/conference papers and held 10 Chinese authorized invention patents as the first inventor or as a mentor for graduate students, of which 3 have already achieved technology transfer. He is a member of IEEE ComSoc & IEEE SPS, a senior member of CIC, a senior member & life member of CIE, a life member of SCS, a council member of SHIE, and the main contact person of RISTA member units. He has served as an OC member/TPC member/Track Chair/Workshop Chair/Session Chair/Special Session Chair/Program Committee Chair/Publicity Chair/Financial Chair/Moderator/Invited Speaker of prominence academic conferences for more than 30 times and received Outstanding Organization Award. He has also served as an official reviewer for many domestic and international journals in the field of communications, such as IEEE TWC, IEEE TVT, IEEE CNCOMM, IEEE CL, IEEE SPL, CJE, JC, JXD, JEIT, JSEE, JCIN, JCUPT, etc. His current interests include 6G waveform modulation technologies & multiple access technologies.

Biography: You You received the B.S. degree in Information Science and Engineering from Southeast University in 2012, and the M.S.E. degree in Communications and Signal Processing from the University of Leeds and Nanjing University of Science & Technology, in 2015 and 2016, respectively, and the Ph.D. degrees from the University of Leeds in 2021. He is currently an Associate Professor with the Purple Mountain Laboratories, Nanjing, China. His research interest is focused on algorithms and implementations for signal processing and communication systems. He has published more than 20 articles indexed in SCI and EI. He has applied for and received authorization for over 20 invention patents. He has served as Symposium Chair of ICSPS 2025, a Local Arrangement Chair for ICTC 2023, a Tutorial Speaker for IEEE APCCAS 2022, and a Session chair for ICCT 2022.

Speech Title: Signal Processing
and Learning for Next Generation Multiple Access in 6G
Abstract: Massive machine-type communications (MTC)
focus on uplink access of large-scale users with bursty
short-time transmissions. Orthogonal multiple access is
impossible to support massive connectivity due to the
limited radio resources. The use of grant-based random
access protocols inevitably incur severe access latency
and excessive signaling overhead. How to design
effective and reliable wireless access techniques to
support massive IoT is a meaningful and interesting
topic. We adopt Sparse Bayesian Learning (SBL)
approaches to solve the multi-user detection (MUD)
problem for next generation multiple access in 6G. The
MUD problem within a certain access slot is formulated
as a Single Measurement Vector (SMV) model and
efficiently solved via SBL-based methods. To further
improve the MUD performance, we set up a Multiple
Measurement Vector (MMV) model and develop block
SBL-based MUD methods, by exploiting the temporal
correlation of user activity over successive access
slots. Simulation results show that the proposed
SBL-based MUD algorithms achieve substantial performance
gain over traditional ones.
Biography: Xiaoxu Zhang (associate professor, IEEE Senior Member) received her PhD degree in communication and information systems from University of Electric Science and Technology of China (UESTC) in 2019. From August 2017 to August 2018, she was with the department of Electrical and Computer Engineering, McGill University, as a visiting scholar. She joined the Southwest Jiaotong University (SWJTU) in 2019. Her main research areas are wireless communications, sparse signal processing, high mobility communications, Bayesian inference for data analysis, machine learning, and artificial intelligence. She is currently a reviewer for international journals and conference papers such as IEEE Transactions on Wireless Communications, IEEE Transactions on Vehicular Technology, IEEE Wireless Communications Letters and IEEE Vehicular Technology Conference.

Biography: Shanxiang Lyu received his Ph.D. from Imperial College London in 2018. He is currently an Associate Professor at Jinan University, where he leads the Laboratory of Quantum and Post-Quantum Cryptography. He is a recipient of the Guangdong Provincial Excellent Young Talents Program and the 2021 CIE Information Theory Society Yong-Star Award. Dr. Lyu has served on the organizing and technical program committees of major international conferences such as IEEE ITW, Inscrypt, IEEE GLOBECOM, and IEEE VTC. He was the organizer of LatticeCC: Workshop on Lattice Coding and Crypto at Asiacrypt 2025. His research interests include lattice-based cryptography, secure communication systems, and the intersection of PQC and quantum technologies.

Speech Title: Machine Learning
for Communication Baseband Systems: Opportunities and
Hardware Design Challenges
Abstract: Machine
learning (ML) is opening new opportunities for
communication baseband systems, where increasingly
complex wireless environments challenge conventional
model-based signal processing. ML-based approaches have
shown strong potential in key baseband tasks such as
decoding, detection, and channel estimation. However,
their practical deployment remains challenging due to
strict constraints on throughput, latency, energy
efficiency, and hardware complexity. This talk will
present representative examples of ML in communication
baseband processing and discuss the associated hardware
design challenges. Through selected case studies, the
talk will highlight the importance of algorithm–hardware
co-design for enabling efficient and practical ML-driven
communication systems.
Biography: Youngjoo Lee received
the B.S., M.S., and Ph.D. degrees in electrical
engineering from Korea Advanced Institute of Science and
Technology (KAIST), Daejeon, Republic of Korea, in 2008,
2010, and 2014, respectively.
Since 2025, he has
been with the School of Electrical Engineering, KAIST,
Daejeon, Republic of Korea, where he is currently an
Associate Professor. Prior to joining KAIST, he was with
the Interuniversity Microelectronics Centre (IMEC),
Leuven, Belgium, from 2014 to 2015, where he worked on
reconfigurable SoC platforms for software-defined radio
systems. He was an Assistant Professor with the
Department of Electronic Engineering, Kwangwoon
University, Seoul, Republic of Korea, from 2015 to 2017,
and a faculty member with the Department of Electrical
Engineering, Pohang University of Science and Technology
(POSTECH), Pohang, Republic of Korea, from 2017 to 2025.
His current research interests include
algorithm-hardware co-design methodologies for
application-specific processors, energy-efficient ML
accelerators, advanced error-correction codes, and
next-generation wireless systems.

Speech Title: Improving the
communication and secure communication of cell-free
network via reconfigurable intelligent surface.
Abstract: With the rapid development of mobile Internet,
the problems of "cell edge effect" and "spectrum
resource tension" faced by traditional cellular networks
have become increasingly prominent. Cell-free (CF)
networks break the cell boundary restrictions of
cellular networks by virtue of the cooperative
transmission of distributed access points (APs), and
achieve uniform coverage and fair services. However, due
to the random distribution of APs, the user data
transmitted by APs is easily obscured by the
ever-changing wireless environment, and coupled with the
open nature of wireless channels, CF networks also face
the threat of information eavesdropping. In recent
years, reconfigurable intelligent surface (RIS)
technology has emerged, which reshapes the wireless
environment through amplitude and phase modulation of
electromagnetic units, achieving dual improvements in
spectrum efficiency and secure transmission in CF
networks. However, existing related research has the
problem of idealizing system modeling, such as not
considering the power consumption of electromagnetic
unit circuits in RIS, and setting the channel state
Information (CSI) of eavesdroppers (Eve) in secure
communication models to be perfectly obtained, which
limits the practical application value of research
results. This report introduces the latest research
achievements of our team in empowering CF networks with
RIS in the past two years, including how to improve the
transmission performance of CF networks under limited
RIS power supply and how to use active RIS to enhance
network security transmission performance under
non-ideal CSI conditions. The report focuses on
introducing the research model, optimizing modeling, and
algorithm design, as well as verifying the effectiveness
of the proposed solution by presenting simulation
results.
Biography: Limeng Dong,
Associate Professor at the School of Electronics and
Information Technology, Northwestern Polytechnical
University. He Obtained bachelor's, master's, and
doctoral degrees from the School of Electronics and
Information Technology at Northwestern Polytechnical
University in 2012, 2015, and 2019, respectively. From
2015 to 2017, he was an visiting doctoral student at the
School of Electrical Engineering and Computer Science at
the University of Ottawa in Canada. From 2019 to 2021,
working as a postdoctoral researcher at the School of
Information and Communication Engineering, Xi'an
Jiaotong University. In 2024 and 2025, he was
continuously selected for the list of "World’s Top 2%
Scientists", which was jointly released by Stanford
University and Elsevier in the United States. His main
research directions are multi-antenna wireless physical
layer security, cognitive radio communication
technology, cell-free massive MIMO network technology,
and reconfigurable intelligent surface assisted wireless
communication theory.
Personal web page:
https://teacher.nwpu.edu.cn/CC90E8FB89B1687AE053650A280AC773

Assoc. Prof. Wenchao Xia
Nanjing
University of Posts and Telecommunications, China
Biography: Wenchao Xia
received his B.S. degree in communication engineering
and Ph.D. degree in communication and information
systems from Nanjing University of Posts and
Telecommunications, Nanjing, China, in 2014 and 2019,
respectively. From 2019 to 2020, he was a Postdoctoral
Research Fellow with Singapore University of Technology
and Design, Singapore. He is currently with the faculty
of the Jiangsu Key Laboratory of Wireless
Communications, College of Telecommunications and
Information Engineering, Nanjing University of Posts and
Telecommunications. His research interests include edge
intelligence and mobile IoT.
He was a recipient
of the IEEE Globecom Best Paper Award in 2016 and the
IEEE JC&S Best Paper Award in 2022. He serves as an
Associate Editor for the IEEE Wireless Communications
Letters and IET Electronics Letters.

Speech Title: Performance
Tradeoff and Security Enhancement in ISAC Networks
Abstract: Integrated sensing and communication
(ISAC) is a key enabler of future 6G networks, aiming to
unify radar sensing and reliable communications on
shared spectrum. However, practical deployment faces
critical challenges including dynamic interference,
mobility-induced signal degradation, and eavesdropping
vulnerabilities. In this talk, I will present a unified
ISAC framework that tackles these issues from three
perspectives: interference prediction via stochastic
geometry, mobility-resilient beamforming for UAV
networks, and physical-layer security mechanisms that
convert channel dynamics into anti-eavesdropping gains.
The focus is on how to balance the inherent tradeoff
among sensing, communication, and security, offering
practical insights for secure and efficient ISAC system
design.
Biography: Xuran Li is currently an Associate Professor at the School of Communication and Electronic Engineering, Shandong Normal University (SDNU), Jinan, China. He received his M.Sc. and Ph.D. degrees in 2015 and 2018, respectively, from the Faculty of Information Technology at the Macau University of Science and Technology (MUST). His research interests include wireless communication networks, wireless network security, and integrated sensing and communication (ISAC). He serves as the PI for one national-level and two provincial-level research projects. He has authored over 30 academic papers, with publications in top-tier journals such as IEEE JSAC and flagship conferences including IEEE ICC and IEEE Globecom. He is a member of both the Communication and Microwave Committee and the Aerospace Information Committee of the Shandong Institute of Electronics. He is a recipient of the Excellent Paper Award from the Chin. J. Internet Things (2022) and the Best Paper Award at IEEE CCAI 2025. He has delivered invited talks at academic conferences including IEEE WOCC 2025 and IEEE CCAI 2025. He serves as a Guest Editor for the journal Network and a reviewer for IEEE TIFS, IEEE TVT, IEEE IoT J, Digit. Commun. Netw., etc. He has also served as Session Chair for NCIC 2024, NCIC 2025, CCAI 2025, and CCAI 2026, and as a TPC Member for IEEE VTC-Fall 2023, IEEE VTC-Spring 2024, IEEE ISPA 2024, IEEE WCSP 2024, and IEEE ISPA 2025.

Biography: Hoang Le is currently an Associate Professor with the School of Computer Science and Engineering at the University of Aizu (UoA), Japan. His research interests are in the areas of optical wireless communications, satellite/vehicular networks, applied AI/ML, and network security-based quantum cryptography.

Speech Title: Distributed
Transceiver Design and Duplex Mode Selection in Scalable
CF-RAN with Network-assisted Free-duplex
Abstract: Cell-free radio access network (CF-RAN) with
network-assisted free-duplex (NA-FD) architecture
evolved from cell-free massive multiple input multiple
output (CF-mMIMO) network unifies various operating
modes, such as flexible duplex, hybrid duplex, and full
duplex. For the distributed transceiver design and
access point (AP) duplex mode selection, we consider the
information constraints of each edge distributed unit
(EDU), the transmit power constraints of each AP/user
equipment (UE), and with the goal of maximizing the rate
of system, we propose a partial distributed block
coordinate descent (PDBCD) algorithm, which decouples
the complex optimization problem into three subproblems
for two-layer iterative solution. The algorithm
distributes the computing tasks of the transceiver
corresponding to the subproblems to EDUs for processing,
approximates the centralized processing performance
through iterative updating, fully utilizes the powerful
computing resources of EDUs, and significantly reduces
the computational pressure of cell-free cloud computing
center (CCU). In addition, when solving the receiver
subproblem, to reduce the signaling overhead, an
inter-EDU information sharing mechanism is proposed,
which realizes the dynamic balance between resource
overhead and uplink performance. Then the PDBCD
algorithm is combined with greedy search to quickly
determine an optimal duplex mode, which further reduces
the cross-link interference (CLI) effects in NA-FD
systems.
Biography: Xinjiang Xia received the
B.S. and M.S. degrees in communication and information
systems from Hohai University, Nanjing, China, in 2009
and 2012, respectively, and the Ph.D. degree with the
National Mobile Communications Research Laboratory,
Southeast University, Nanjing, in 2021. He is currently
a Associate Researcher with the Purple Mountain
Laboratories. From 2021 to 2024, he was a Postdoctoral
Scholar with the Purple Mountain Laboratories, Nanjing.
His research interests include cell free massive MIMO,
signal processing, and full duplex.

Speech Title: Sensing Priority:
A Novel Paradigm for Diverse Sensing Tasks in 6G ISAC
Systems
Abstract: In future 6G Integrated Sensing
and Communication (ISAC) systems, supporting diverse
sensing tasks—from safety-critical collision avoidance
to experience-oriented passenger monitoring—under
limited resources presents a fundamental challenge.
Undifferentiated resource allocation leads to
inefficiency and risks. To address this, we propose
"Sensing Priority" as a novel paradigm. This framework
first introduces three priority partitioning schemes:
Sensing Target-Based (STB), Sensing Zone-Based (SZB),
and Sensing Behavior-Based (SBB), which classify tasks
by target identity, geographic area, and behavioral
patterns, respectively. We then develop a dual approach
for priority assessment: a systematic Analytic Hierarchy
Process (AHP) for interpretable expert-driven scoring
and a data-driven AI model for dynamic, real-time
adaptation. Finally, we establish a threshold-based,
cross-domain resource allocation strategy. This strategy
strictly prioritizes high-criticality tasks, such as
ensuring the Cramér-Rao Bound for a Primary Sensing
Target is met first, before optimizing for communication
and lower-priority sensing needs. This holistic
priority-based framework ensures the reliable execution
of critical services while enhancing overall ISAC system
efficiency.
Biography: Linsong Du is currently an
Associate Professor with the School of Information
Science and Technology, Southwest Jiaotong University,
Chengdu. He received the M.S. and Ph.D. degrees in
communication and information systems from the National
Key Laboratory of Science and Technology on
Communications, University of Electronic Science and
Technology of China, Chengdu, in 2018 and 2022,
respectively. With over 30 peer-reviewed publications in
IEEE flagship journals and conferences, including
approximately 15 first-authored papers, his research
focuses on integrated sensing and communication,
reconfigurable intelligent surface-assisted interference
suppression, full-duplex communications, and
information-theoretic security. His first-author
contributions appear prominently in IEEE Transactions on
Communications, IEEE Transactions on Wireless
Communications, and IEEE Transactions on Vehicular
Technology, He served as EDAS Co-Chair for IEEE PIMRC
2023 and actively reviews for IEEE Transactions on
Communications, IEEE Wireless Communications Letters,
and IEEE Communication Letters
Personal webpage:
https://faculty.swjtu.edu.cn/dulinsong1/zh_CN/index.htm

Biography: Li Yan, Lecturer. She earned her Ph.D. from the University of Electronic Science and Technology of China, during which she was jointly Ph.D at the University of Alberta in Canada. After obtaining her doctorate, she worked for seven years at Huawei Technologies Co., Ltd., focusing on millimeter-wave-related algorithms and hardware design. She completed the fault tolerance theory and tape-out of an independently designed chip end-to-end, which was published in the journal JSSC for circuit design. In early 2024, she joined the University of Electronic Science and Technology of China as a lecturer, primarily engaged in teaching and research related to millimeter-wave sensing and communication integration, as well as low-power high-reliability hardware architecture. She has participated in or led multiple enterprise projects on sensing and communication integration, including those by China Mobile and Datang, as well as national key projects. Under her guidance, students won the second prize in the National Graduate Electronic Design Competition Final in 2024. She has published over 20 academic papers and applied for/invented more than 6 patents.

Speech Title: Cache-Assisted
Integrated Sensing-Communication-Computation for Online
Federated Learning: A Framework for Resource-Constrained
Edge Networks
Abstract: This talk presents a
cache-assisted integrated
sensing-communication-computation (ISCC) framework for
online federated edge learning (FEEL) in OFDM systems.
Unlike conventional FEEL approaches that rely solely on
real-time sensory data, our framework intelligently
combines real-time samples with selectively cached
historical data to enhance learning efficiency under
limited cache and broadband channel constraints. We
address two key challenges: concept drift in historical
data, which degrades model relevance, and the coupled
optimization of sensing, communication, and computation
resources. A rigorous convergence analysis is conducted
using first-order Taylor approximation, quantifying the
impact of sensing SNR, quantization distortion, batch
size, and concept drift. To maximize per-round loss
reduction, we formulate a non-convex optimization
problem under latency, energy, and cache constraints,
and solve it via alternating optimization with
closed-form solutions for power, RB, and batch size
allocation. Extensive simulations on a human motion
recognition task validate the theoretical convergence
and demonstrate significant accuracy gains over
baselines.
Biography: Nannan Zhang is currently a lecture with the School of Electronic and Electrical Engineering (SEEE), Shanghai University of Engineering Science (SUES), Shanghai, China. She received the B.S. degree from the Northeastern University, Shenyang, China, in 2016, and the Ph.D. degree from the Zhejiang University, Hangzhou, China, in 2024. From 2022 to 2023, she was a Visiting Student with the School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom. To date, she has authored over 10 academic papers, with publications in leading journals such as IEEE Transactions on Wireless Communications, IEEE Transactions on Communications, IEEE Transactions on Cognitive Communications and Networking, and so on. She has actively participated in various academic conferences, chaired multiple sessions on 6G communications, and been honored with the Best Organization Award. Her research interests mainly focus on wireless edge caching for low-delay communications, integrated sensing-computation-computation, reconfigurable intelligent surface-assisted communications.

Speech Title: ORIS-Enabled
Optical Communication and Sensing Integration: From
Physical Modeling to Network Coordination
Abstract: Optical wireless communication provides
abundant spectrum resources and high spatial resolution,
while optical sensing enables fine-grained environmental
perception. Integrating these functionalities within a
unified optical framework is an important direction for
future wireless systems. However, the strong
directionality and line-of-sight dependency of optical
signals impose fundamental constraints on coverage
flexibility, alignment robustness, and multi-user
support. Optical Reconfigurable Intelligent Surfaces
(ORIS) offer a programmable mechanism for optical
wavefront manipulation without altering the active
transceiver structure. This talk presents our recent
work on ORIS-enabled optical communication and sensing
integration, structured from physical modeling to
network coordination. We first develop array-based ORIS
physical models and analyze their optical field
transformation characteristics and efficiency limits.
Based on these models, the impact of ORIS-assisted beam
shaping, spatial diversity, and spatial multiplexing on
communication reliability and sensing performance is
systematically characterized under realistic propagation
conditions. A unified analytical framework is
established to capture the coupling among optical
propagation, programmable surface control, and sensing
feedback. Finally, multi-ORIS cooperative architectures
are discussed, where distributed coordination and
resource allocation mechanisms are designed for
multi-user optical communication and sensing
integration. The presented results provide a
system-level understanding of ORIS-enabled optical
integration and identify key challenges for scalable
deployment.
Biography: Haibo Wang received the B.S., M.S., and Ph.D. degrees in Information and Communication Engineering from Southeast University, Nanjing, China. He is currently an assistant professor at Southeast University. His research focuses on optical reconfigurable intelligent surfaces (ORIS) and optical wireless communication systems, with particular emphasis on ORIS-assisted system modeling, optical field manipulation, and performance analysis. He has published 26 papers in leading IEEE journals, including IEEE Transactions on Wireless Communications, IEEE Journal of Lightwave Technology, and IEEE Transactions on Vehicular Technology.

Biography: Qianli Wang (Member, IEEE) received the B.S. degree in electronic and information engineering, M.S. degree in electronics and communication engineering and the Ph.D. degree in information and communications engineering from University of Electronic Science and Technology of China, in 2013, 2016 and 2020, respectively. Now he is an associate professor in the School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China. His research interests include estimation and detection theory, compressed sensing, radar signal processing, array signal processing, integrated sensing and communication. He has authored/co-authored over 30 journal and conference papers. He has served as TPC member of IEEE GLOBECOM and IEEE ICC. He has also served as reviewer for many top journals, such as IEEE TSP, IEEE TWC, IEEE TGRS, IEEE TCOM, IEEE TVT, etc.

Biography: Xixi Zhang (Member, IEEE) received the Ph.D. degree in information and communication engineering from the Nanjing University of Posts and Telecommunications (NJUPT), Nanjing, China, in June 2025. She currently works at Hohai University, China. Her research interests include deep learning, neural architecture search, and its applications in signal recognition, cyber security, and Internet of Things.
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| Prof. Yijun Cui Nanjing University of Aeronautics and Astronautics, China |
Prof. Yanli Xu Shanghai Maritime University, China |
Prof. Kun Guo East China Normal University, China |
Prof. Cui-qin Dai Chongqing University of Posts and Telecommunications, China |
Prof. Du Li Nanjing University, China |
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| Prof. Zhaozhong Guo Beijing Information Science and Technology University, China |
Assoc. Prof. Bingcheng Zhu Southeast University, China |
Assoc. Prof. Xingyu Lu Nanjing University of Science and Technology, China |
Assoc. Prof. Simeng Feng Nanjing University of Aeronautics and Astronautics, China |
Assoc. Prof. Xiaojun Hei Huazhong University of Science and Technology, China |
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| Associate Researcher Jiao Zhang Purple Mountain Laboratories, China |
Assoc. Prof. Han Wu Sichuan University, China |
Assoc. Prof. Tianming Ma Shanghai University of Engineering Science, China |
Assoc. Prof. Fanfan Shen Nanjing Audit University, China |
Associate Researcher Shuai Ma Peng Cheng Laboratory, China |
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| Associate Researcher Xinjiang Xia Purple Mountain Laboratories, China |
Assoc. Prof. Chuanting Zhang Shandong University, China |
Research Assoc. Prof. Chen Huang Purple Mountain Laboratories & Southeast University, China |
Assoc. Prof. Ruoyu Zhang Nanjing University of Science and Technology, China |
Assoc. Prof. Jihao Fan Nanjing University of Science and Technology, China |
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| Assoc. Prof. Xiangping Zhai Nanjing University of Aeronautics and Astronautics, China |
Assoc. Prof. Mingjie Shao Academy of Mathematics and Systems Science, Chinese Academy of Sciences, China |
Assoc. Prof. Bingpeng Zhou Sun Yat-sen University, China |
Assoc. Prof. Chao Fang Beijing University of Technology, China |
Lecturer Jiachi Zhang Shandong Police College, China |
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| Lecturer Li Yan University of Electronic Science and Technology of China, China |
Dr. Yanqing Xu The Chinese University of Hong Kong, Shenzhen, China |
Assoc. Prof. Ling Liu Guangzhou Institute, Xidian University, China |