All tutorials will be accessible to attendees who have registered for the Tutorial session. The list is below.
Please note: This list is subject to change depending on how many people sign up for these tutorials in advance.
December 4, Monday - Morning Session
T01: Tactile Internet Support for the Metaverse
T02: Converged Terahertz Communications and Sensing: System and Link Level Considerations
T03: What Will Wi-Fi 8 Be? A Primer on IEEE 802.11bn Ultra High Reliability
T04: Task-oriented and Semantics-aware Communications and Networking for 6G
T05: Holographic Radio: A New Paradigm for Communication and Sensing in 6G
December 4, Monday - Afternoon Session
T06: Reconfigurable Intelligent Surfaces for 6G: From Academic Research to Industry Development
T07: Towards Unified Understanding of Semantic Communications and Networking
T08: Holographic MIMO Communications: Fundamentals, Extreme Spatial Multiplexing and Mutual Coupling CANCELLED
T09: Localization-of-Things in Beyond 5G Ecosystem CANCELLED
T10: Differentiable Ray Tracing for Digital Twin Networks
December 8, Friday - Morning Session
T11: Why OTFS 2.0 - How to make Communication and Radar Sensing More Predictable in 6G
T12: What Next Generation Multiple Access Will Be?
T13: Towards 6G Communications: Wireless Channel Measurements, Characteristics Analysis, and Modeling
T14: Non-Terrestrial Networks for the Next Generation Global Connectivity
T15: Automating 6G Operations: Architectural Design and Service Optimization
December 8, Friday – Afternoon Session
T16: Developing the Metaverse with Edge Intelligence: A Tutorial
T17: Rate-Splitting Multiple Access for 6G: Recent Advances and Future Research Trends
T18: Intelligent Network Synchronization in the 6G Era: Scalability, Efficiency, and Applications
T19: Tackling Training Data Scarcity for AI in Mobile Networks: Challenges and Solutions
T20: Digital Twins for 6G communications and networking
December 4, Monday - Morning Session (9:00 - 12:30)
T01: Tactile Internet Support for the Metaverse
Room 302, Kuala Lumpur Convention Center
Frank H.P. Fitzek (Technische Universität Dresden & ComNets - Communication Networks Group, Germany); Holger Boche (Technical University Munich, Germany)
Abstract: This tutorial provides an overview of how the Tactile Internet, a technology that enables ultra-low latency communication and control, can support the Metaverse, a virtual world where users interact in a shared space. We will explore the various applications and use cases where Tactile Internet can enhance the user experience in the Metaverse, and discuss the technical challenges and opportunities associated with this integration. The tutorial will address several cutting-edge topics in communication networks, including quantum communication, Post-Shannon Theory, 6G communication system, in-network computing, and human-machine interaction.
Bios
Frank H. P. Fitzek is a Professor and chair of the communication networks group at Technische Universität Dresden coordinating the 6G-life and the 5G Lab Germany. Currently he is also the speaker of the excellence cluster CeTI carrying out research in the field of tactile Internet. He received his diploma (Dipl.-Ing.) degree in electrical engineering from the University of Technology - Rheinisch-Westfälische Technische Hochschule (RWTH) - Aachen, Germany, in 1997 and his Ph.D. (Dr.-Ing.) in Electrical Engineering from the Technical University Berlin, Germany in 2002 and became Adjunct Professor at the University of Ferrara, Italy in the same year. In 2011 he received the SAPERE AUDE research grant from the Danish government and in 2012 he received the Vodafone Innovation price. His current research interests are in the areas of wireless and mobile 5G/6G communication networks, network coding, Post-Shannon communication, and quantum communication.
Holger Boche Professor Boche's research focuses on wireless network theory and applied mathematics - such as probability theory, optimization theory and game theory, or quantum information theory. Professor Boche (1966) studied information technology and mathematics at the University of Dresden and received his PhD in engineering from the TU Dresden as well as in mathematics from the TU Berlin. In 2002 he followed the call to the TU Berlin. He was head of the department for Mobile Broadband Communication at the HHI and director of the German-Sino Lab for Mobile Communication (FhG-MCI). Since 2010, Holger Boche has been a professor at the Chair of Theoretical Information Technology at the Technical University of Munich. He is a member of the German Academy of Science and Engineering, the Berlin-Brandenburg Academy of Sciences and Humanities and the National Academy of Sciences, Leopoldina.
T02: Converged Terahertz Communications and Sensing: System and Link Level Considerations
Room 303, Kuala Lumpur Convention Center
Nour Kouzayha (King Abdullah University of Science and Technology (KAUST), Saudi Arabia); Hadi Sarieddeen (American University of Beirut, Lebanon); Mohamed-Slim Alouini (King Abdullah University of Science and Technology (KAUST), Saudi Arabia); Tareq Y. Al-Naffouri (King Abdullah University of Science and Technology, USA
Abstract: Terahertz (THz)-band communications are a key enabler for future-generation wireless communication systems that promise to integrate a wide range of data-demanding applications at the intersection of communications, localization, and sensing. Prospect THz signal generation, modulation, and radiation methods are converging, and the corresponding channel model, noise, and hardware-impairment notions are emerging. Such progress paves the way for well-grounded research into
THz-specific techniques for wireless communications and sensing. This tutorial presents a closed-loop full discussion of these techniques, both from a system-level and a link-level perspective.
On the system level, we study performance analysis and multiconnectivity strategies for large-scale THz networks. We also motivate stochastic geometry techniques for performance analysis and system modeling and discuss the role of reconfigurable intelligent surfaces in THz systems. We also motivate sensing and localization in the THz band. On the link level, we focus on the classical problems of waveform design and modulation, beamforming and precoding, index modulation, channel estimation, channel coding, and data detection.
Bios:
Nour Kouzayha (S’16-M’18) received her Ph.D. degree in electrical and computer engineering from the American University of Beirut (AUB), Lebanon, in 2018. She is currently a postdoctoral fellow at King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia. Her research interests are in the area of wireless communications, internet of things and aerial networks.
Hadi Sarieddeen (S’13-M’18) received his Ph.D. degree in electrical and computer engineering from the American University of Beirut (AUB), Lebanon, in 2018. He held postdoctoral positions at KAUST and MIT between 2018 and 2022. He is currently an assistant professor in the Electrical and Computer Engineering department at AUB. His research interests are in signal processing for wireless communications, with an emphasis on THz communications and error correction coding.
Mohamed-Slim Alouini (S’94-M’98-SM’03-F’09) was born in Tunis, Tunisia. He received his Ph.D. degree in Electrical Engineering from Caltech, Pasadena, CA, in 1998. He served as a faculty member at the University of Minnesota, Minneapolis, then at Texas A&M University at Qatar, Education City, Doha, Qatar before joining KAUST as a professor of electrical engineering in 2009. His current research interests include the modeling, design, and performance analysis of wireless communication systems.
Tareq Y. Al-Naffouri (M’10-SM’18) received his Ph.D. degree in Electrical Engineering from Stanford University in 2004. He is currently a Professor at the Electrical and Computer Engineering department at KAUST. His research interests lie in the areas of sparse, adaptive, and statistical signal processing, localization, machine learning, and their applications.
T03: What Will Wi-Fi 8 Be? A Primer on IEEE 802.11bn Ultra High Reliability
Room 304, Kuala Lumpur Convention Center
Lorenzo Galati Giordano (Nokia Bell Labs, Germany); Giovanni Geraci (Telefonica Research and UPF Barcelona, Spain); Francesc Wilhelmi (Nokia Bell Labs, Germany); Boris Bellalta (Universitat Pompeu Fabra, Spain)
Abstract:
What will Wi-Fi 8 be? Driven by the strict requirements of emerging applications, next-generation Wi-Fi is set to prioritize Ultra High Reliability (UHR) above all. In this tutorial, we explore the journey towards IEEE 802.11bn UHR, the amendment that will form the basis of Wi-Fi 8. After providing an overview of the nearly completed Wi-Fi 7 standard, we will present new use cases calling for further Wi-Fi evolution. We will also outline current standardization, certification, and spectrum allocation activities, sharing updates from the newly formed UHR Study Group. We will then introduce the disruptive new features envisioned for Wi-Fi 8 and discuss the associated research challenges. To conclude, we will shed light on ongoing activities and opportunities associated with the integration and application of AI/ML techniques in Wi-Fi.
Bios:
Lorenzo Galati-Giordano (SM’20) is Senior Research Scientist at Nokia Bell Labs since 2015. His current focus is on future indoor networks and next generation Wi-Fi technologies, an area where he is contributing to the ongoing IEEE 802.11be standardization with pioneering works on large antenna arrays solutions for the unlicensed spectrum and receiving international attention from the press. He received the M.Sc. and the Ph.D. degrees in wireless communication from Politecnico di Milano, Italy, in 2005 and 2010, respectively, and the master's degree in Innovation Management from IlSole24Ore Business School, Italy, in 2014. He was also an R&D Engineer for Azcom Technology, an Italian SME, from 2010 to 2014. Lorenzo has more than 10 years of academic and industrial research experience on wireless communication systems and protocols, co-authored 20+ commercial patents, 30+ publications in prestigious books, IEEE journals and conferences, and 10+ standard contributions in the IEEE 802.11be.
Giovanni Geraci (SM’19) iscurrently attached to Telefonica Research and UPF Barcelona, Spain. He was previously a Research Scientist with Nokia Bell Labs and holds a Ph.D. from the UNSW Sydney. He has been serving as a Distinguished Lecturer for the IEEE ComSoc and the IEEE VTS and as an Editor for the IEEE TWC and IEEE COMML. He has been delivering over 30 IEEE ComSoc tutorials, keynotes, and industry seminars—many of which on Wi-Fi and unlicensed spectrum technologies—and frequently gives invited lectures at renowned industrial, governmental, and academic institutions. He has co-authored 70+ IEEE publications with 3000+ citations and is co-inventor of a dozen patent families on wireless communications and networking. He was the recipient of the IEEE ComSoc EMEA Outstanding Young Researcher Award and of Best Paper Awards at IEEE PIMRC’19 and IEEE Globecom’22.
Francesc Wilhelmi (M’23) is a research engineer at Nokia Bell Labs. He holds a Ph.D. in Information and Communication Technologies (2020) and an M.Sc. in Intelligent and Interactive Systems (2016) from Universitat Pompeu Fabra (UPF). Previously, he was a researcher at Centre Tecnològic de Telecomunicacions de Catalunya (CTTC). His main research interests are in Wi-Fi technologies and their evolution, network simulators and network digital twinning, machine learning, decentralized learning, and distributed ledger technologies. In the past, he was also involved in standardization activities within the ITU-T, where he was one of the main editors of recommendation Y.3181 “Architectural framework for Machine Learning Sandbox in future networks including IMT-2020”. In addition, he has organized three problem statements in the ITU AI/ML in 5G Challenge.
Boris Bellalta (SM’13) is a Full Professor at Universitat Pompeu Fabra (UPF), where he heads the Wireless Networking group. His research interests are in the area of wireless networks and performance evaluation, with emphasis on Wi-Fi technologies, machine learning, and resource management. His recent works on spatial reuse, spectrum aggregation, txop sharing and multi-link operation for next-generation Wi-Fi have received special attention from the research community and industry. He is currently involved as principal investigator in several EU, national and industry funded research projects that aim to push forward our understanding of complex wireless systems. The results from his research have been published in 150+ international journal and conference papers. He has supervised 11 PhD students.
T04: Task-oriented and Semantics-aware Communications and Networking for 6G
Room 305, Kuala Lumpur Convention Center
Yansha Deng (King's College London, United Kingdom (Great Britain)); Nikolaos Pappas (Linköping University, Sweden); Jun Zhang (The Hong Kong University of Science and Technology, Hong Kong)
Abstract:
This tutorial will identify and discuss technical challenges and recent results related to task-oriented and semantics-aware communications for future wireless networks. The tutorial is mainly divided into four parts. In the first part, we will provide the motivation and we will discuss the current approaches towards semantics-aware goal-oriented communications such as earlier studies that consider the age and value of information. Then, we will consider the topic beyond the age of information. We will present some results on autonomous maintenance in industrial IoT, semantic source coding, and autonomous systems and then present a novel task-oriented and semantics-aware communication framework in AI-based future wireless networks. In the second part, we will focus on task-oriented and semantics-aware communication solutions for the virtual reality data type. In the third part, we will present task-oriented and semantics-aware communications solutions for control and command data, and sensor data. In the fourth part, we will focus on the application scenario of edge video analytics, and summarize the tutorial by providing a future outlook of task-oriented and semantics-aware communication and networks.
Bios:
Yansha Deng (S13-SM23) is currently a Senior Lecturer (Associate Professor) in the Department of Engineering at King’s College London, London, United Kingdom. She has secured more than £2.3 million of research funding as the Principal Investigator and has received EPSRC New Investigator Award. She has published 90+ journal papers and 40+ IEEE/ACM conference papers. She received the Best Paper Award in Globecom 2017, ICC 2016, and IEEE Communications Society Best Young Researcher Award for Europe, Middle East, and Africa Region 2021. She is currently the Senior Editor of IEEE Communications Letters since 2020, the Associate Editor of IEEE Transactions on Communications since 2017, the Associate Editor of IEEE Communications Surveys and Tutorials since 2022, the Associate Editor of IEEE Transactions on Machine Learning in Communications and Networking since 2022, the Associate Editor of IEEE Transactions on Molecular, Biological and Multi-scale Communications since 2019, the Associate Editor of IEEE Open Journal of Communications Society since 2019 and the Vertical Area Editor of IEEE Internet of Things Magazine since 2021.
Nikolaos Pappas is an Associate Professor in the Department of Computer and Information Science at Linköping University, Linköping, Sweden. His main research interests include the field of wireless communication networks with an emphasis on semantics-aware communications, energy harvesting networks, network-level cooperation, age of information, and stochastic geometry. Dr Pappas has served as the Symposium Co-Chair of the IEEE International Conference on Communications in 2022 and the IEEE Wireless Communications and Networking Conference in 2022. From 2013 to 2018, he was an Editor of the IEEE Communications Letters. He was a Guest Editor of the IEEE Internet of Things Journal on “Age of Information and Data Semantics for Sensing, Communication and Control Co-Design in IoT.” He is also an Editor of the IEEE Transactions on Communications, the IEEE Transactions on Machine Learning in Communications and Networking, the IEEE/KICS Journal of Communications and Networks, and the IEEE Open Journal of Communications Society, and an Expert Editor for invited papers of the IEEE Communications Letters.
Jun Zhang is an Associate Professor in the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology, and is an IEEE Fellow. His research interests include wireless communications and networking, mobile edge computing and edge AI, and cooperative AI. Dr Zhang co-authored the book Fundamentals of LTE (Prentice-Hall, 2010). He is a co-recipient of several best paper awards, including the 2021 Best Survey Paper Award of IEEE Communications Society, the 2019 IEEE Communications Society & Information Theory Society Joint Paper Award, and the 2016 Marconi Prize Paper Award in Wireless Communications. Two papers he co-authored received the Young Author Best Paper Award of the IEEE Signal Processing Society in 2016 and 2018, respectively. He also received the 2016 IEEE ComSoc AsiaPacific Best Young Researcher Award. He is an Editor of IEEE Transactions on Communications and was an editor of IEEE Transactions on Wireless Communications (2015-2020). He served as a MAC track co-chair for IEEE Wireless Communications and Networking Conference (WCNC) 2011 and a wireless communications symposium co-chair of IEEE International Conference on Communications (ICC) 2021.
T05: Holographic Radio: A New Paradigm for Communication and Sensing in 6G
Room 306, Kuala Lumpur Convention Center
Hongliang Zhang and Boya Di (Peking University, China); Zhu Han (University of Houston, USA); Lingyang Song (Peking University, China)
Abstract:
Holographic radio, which integrates massive antenna elements into a compact space to achieve ultra-massive MIMO for high-resolution sensing and high-capacity communications, has been considered as a promising enabling technique for the forthcoming sixth generation (6G) networks. Widely-utilized phased arrays relying on costly components make the implementation of ultra-massive MIMO in practice become prohibitive from both cost and power consumption perspectives. In contrast, the recent developed reconfigurable holographic surfaces (RHSs) composing of densely packing sub-wavelength metamaterial elements provide a new method to solve the above issue without costly hardware components. By leveraging the holographic principle, the RHS serves as an ultra-thin and lightweight surface antenna integrated with the transceiver, thereby providing a promising alternative to phased arrays for realizing ultra-massive MIMO. In this tutorial, we will first provide a basic introduction of RHSs. We then introduce the unique features of RHSs which enables both communication and sensing, in a comprehensive way. Related design, analysis, optimization, and signal processing techniques will be presented. Typical RHS-based applications for the wireless communications and radio-frequency sensing will be explored. Our implementation of RHSs as well as the developed prototypes of communication and sensing systems will also be reported. Several up-to-date challenges and potential research directions will be discussed as well.
Bios:
Hongliang Zhang (S’15-M’19) received B.S. and Ph.D. degrees at the School of Electrical Engineering and Computer Science at Peking University, in 2014 and 2019, respectively, where he is currently an assistant professor with School of Electronics. His current research interests include reconfigurable intelligent surfaces, aerial access networks, optimization theory, and game theory. He received the best doctoral thesis award from Chinese Institute of Electronics in 2019. He is also the recipient of 2021 IEEE Comsoc Heinrich Hertz Award for Best Communications Letters and 2021 IEEE ComSoc AsiaPacific Outstanding Paper Award. He has served as a TPC Member and a workshop co-chair for many IEEE conferences. He is the winner of the Outstanding Leadership Award as the publicity chair for IEEE EUC in 2022. He is currently an Editor for IEEE Transactions on Vehicular Technology, IEEE Communications Letters, IET Communications, and Frontiers in Signal Processing. He has also served as a Guest Editor for several journals, such as IEEE Internet of Things Journal and Journal of Communications and Networks. He is an exemplary reviewer for IEEE Transactions on Communications in 2020.
Boya Di (S’17-M’19) obtained her Ph.D. degree from the Department of Electronics, Peking University, China, in 2019. Prior to that, she received the B.S. degree in electronic engineering from Peking University in 2014. She was a postdoc researcher at Imperial College London and is now an assistant professor at Peking University. Her current research interests include holographic radio, reconfigurable intelligent surfaces, multi-agent systems, edge computing, and aerial access networks. She has published over 30 journal papers on the topic of reconfigurable holographic surface aided communications and sensing. She received the best doctoral thesis award from China Education Society of Electronics in 2019. She is also the recipient of 2022 IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award and 2021 ComSoc Asia-Pacific Outstanding Paper Award. She serves as an associate editor for IEEE Transactions on Vehicular Technology since June 2020. She has also served as a workshop co-chair for IEEE WCNC 2020&2021 and ISWCS 2022.
Zhu Han (S’01–M’04-SM’09-F’14) 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 a Professor in Electrical and Computer Engineering Department as well as Computer Science Department at the University of Houston, Texas. His research interests include wireless resource allocation and management, wireless communications and networking, game theory, wireless multimedia, security, and smart grid communication. Dr. Han received an NSF Career Award in 2010, the Fred W. Ellersick Prize of the IEEE Communication Society in 2011, the EURASIP Best Paper Award for the Journal on Advances in Signal Processing in 2015, the IEEE Kiyo Tomiyasu Award in 2021, and several best paper awards in IEEE conferences. Dr. Han is top 1% highly cited researcher according to Web of Science since 2017, and AAAS fellow since 2019.
Lingyang Song (S’03-M’06-SM’12-F'19) received his PhD from the University of York, UK, in 2007. 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, and is now a Boya Distinguished Professor. His main research interests include wireless communications, mobile computing, and machine learning. Dr. Song is the coauthor of many awards, including IEEE Leonard G. Abraham Prize in 2016, IEEE ICC 2014, IEEE ICC 2015, IEEE Globecom 2014, and the best demo award in the ACM Mobihoc 2015. He received National Science Fund for Distinguished Young Scholars in 2017, First Prize in Nature Science Award of Ministry of Education of China in 2017. Dr. Song has served as an IEEE ComSoc Distinguished Lecturer (2015-2018), an Area Editor of IEEE Transactions on Vehicular Technology (2019-), Co-chair of IEEE Communications Society Asia Pacific Board Technical Affairs Committee (2020-). He is a Clarivate Analytics Highly Cited Researcher.
December 4, Monday - Afternoon Session (14:00 - 17:30)
T06: Reconfigurable Intelligent Surfaces for 6G: From Academic Research to Industry Development
Room 302, Kuala Lumpur Convention Center
Linglong Dai (Tsinghua University, China); Yifei Yuan (China Mobile Research Institute, China)
Abstract:
6G Reconfigurable intelligent surface (RIS) has become a promising technology for future 6G wireless communications. RISs have recently attracted extensive research interests to enhance the wireless communications through enlarging signal coverage, improving channel capacity, and increasing energy efficiency. However, practical applications of RISs still face challenges. This tutorial will introduce the latest progress of RIS from perspectives of both academic research and industry development. First, this tutorial will introduce the advanced algorithms for RIS. By considering the physical characteristics of RIS channels including near-field propagation, spatial non-stationarity, ultra-wide broadband effect, etc., we will present the corresponding advanced algorithm designs for RIS channel estimation, beamforming, and beam training. Then, this tutorial will discuss the architecture designs for RIS. Facing the challenges including the multiplicative fading effect and excessive pilot overhead for channel state information acquisition, some new architecture designs of RIS, such as active RIS, sensing RIS, and time-phase adjustable RIS, will be discussed from the viewpoint of joint hardware and software optimization. Subsequently, this tutorial will present the recent system-level simulations of RIS, and the trial test results of RIS in commercial 5G networks. The multi-stage standardization of RIS will also be discussed. Finally, we will review the predecessor technologies of RIS in 4G and 5G (relay and full-dimensional MIMO) to predict the development trends of RIS in the future.
Bios:
Linglong Dai (Fellow, IEEE) received the B.S. degree from Zhejiang University, Hangzhou, China, in 2003, the M.S. degree from the China Academy of Telecommunications Technology, Beijing, China, in 2006, and the Ph.D. degree from Tsinghua University, Beijing, in 2011. From 2011 to 2013, he was a Post-Doctoral Researcher with the Department of Electronic Engineering, Tsinghua University, where he was an Assistant Professor from 2013 to 2016, an Associate Professor from 2016 to 2022, and has been a Professor since 2022. His current research interests include massive MIMO, reconfigurable intelligent surface (RIS), millimeter-wave and Terahertz communications, wireless AI, and electromagnetic information theory. He has coauthored the book MmWave Massive MIMO: A Paradigm for 5G (Academic Press, 2016). He has authored or coauthored over 70 IEEE journal papers and over 40 IEEE conference papers. He also holds 19 granted patents. He has received five IEEE Best Paper Awards at the IEEE ICC 2013, the IEEE ICC 2014, the IEEE ICC 2017, the IEEE VTC 2017-Fall, and the IEEE ICC 2018. He has also received the Tsinghua University Outstanding Ph.D. Graduate Award in 2011, the Beijing Excellent Doctoral Dissertation Award in 2012, the China National Excellent Doctoral Dissertation Nomination Award in 2013, the URSI Young Scientist Award in 2014, the IEEE Transactions on Broadcasting Best Paper Award in 2015, the Electronics Letters Best Paper Award in 2016, the · National Natural Science Foundation of China for Outstanding Young Scholars in 2017, the IEEE ComSoc AsiaPacific Outstanding Young Researcher Award in 2017, the IEEE ComSoc Asia-Pacific Outstanding Paper Award in 2018, the China Communications Best Paper Award in 2019, the IEEE Access Best Multimedia Award in 2020, the IEEE Communications Society Leonard G. Abraham Prize in 2020, the IEEE ComSoc Stephen O. Rice Prize in 2022, and the IEEE ICC Best Demo Award in 2022. He was listed as a Highly Cited Researcher by Clarivate Analytics in 2020-2022. He was elevated as an IEEE Fellow in 2021. Particularly, he is dedicated to reproducible research and has made a large amount of simulation codes publicly available.
Yifei Yuan (Senior Member, IEEE) received his Bachelor & Master degrees from Tsinghua University of China, and a Ph.D. from Carnegie Mellon University, USA. He was with Alcatel-Lucent from 2000 to 2008, working on 3G/4G key technologies. From 2008 to 2020, he was with ZTE as technical director and chief engineer responsible for standards research on LTE-Advanced and 5G. Since 2020, he has been with China Mobile Research Institute, responsible for advanced technologies of 6G. His research interests include MIMO, channel coding, non-orthogonal multiple access (NOMA), internet-of-things (IoT), resource scheduling. He has extensive publications, including 6 books on LTE-Advanced and 5G. He is the rapporteur of NOMA study item in 3GPP. He is the recipient of Best Paper Award by IEEE Communications Society Asia-Pacific Board for co-authoring a paper on NOMA in IEEE Communications Magazine.
T07: Towards Unified Understanding of Semantic Communications and Networking
Room 303, Kuala Lumpur Convention Center
Jihong Park (Deakin University, Australia); Zhijin Qin (Tsinghua University, China); Jinho Choi (Deakin University, Australia)
Abstract:
Semantic communication (SC) is an emerging approach to designing the next generation communication systems. In contrast to traditional communication systems focusing solely on delivering bits at Level A, SC encompasses Levels B and C, aiming to convey the semantics behind the bits and maximize their effectiveness for specific tasks, respectively. These issues were identified over 70 years ago, yet overlooked due to the lack of tools. However, recent advances in machine learning (ML) have given substance to initial SC concepts, positioning SC as a key enabler for 6G. Despite growing interest, significant limitations persist in SC. Key among them is the absence of clear definitions for semantics, leading to disjointed research on the principles and architectures of SC. The role of ML in SC also remains ambiguous, complicating the distinction between SC and other existing ML-based communication frameworks. Furthermore, most of studies concentrates on the physical (PHY) layer in point-point scenarios, questioning scalability and compatibility for multiple users, as well as applicability to the medium access control (MAC) and higher layers. This tutorial aims to consolidate the understanding of SC by presenting a comprehensive definition of semantics and its relationship with ML and communication system architectures. Through this unified perspective, we will illustrate how ML facilitates PHY-layer SC in point-to-point scenarios, extend these methodologies to large-scale SC systems, and demonstrate their application to MAC-layer SC through selected use cases. Finally, we will introduce non-ML and theoretical approaches for modelling ML-based SC frameworks, paving the way for future research directions.
Bios:
Jihong Park is a Lecturer at the School of IT, Deakin University, Australia. He received the B.S. and Ph.D. degrees from Yonsei University, Seoul, Korea, in 2009 and 2016, respectively. He was a Post-Doctoral Researcher with Aalborg University, Denmark, from 2016 to 2017; the University of Oulu, Finland, from 2018 to 2019. His recent research focus includes AI-native and semantic communications, as well as distributed and quantum machine learning. He served as a Conference/Workshop Program Committee Member for IEEE GLOBECOM, ICC, and INFOCOM, as well as NeurIPS, ICML, and IJCAI. He received 2023 IEEE Communications Society Heinrich Hertz Award, 2022 FL-IJCAI Best Student Paper Award, and IEEE GLOBECOM Student Travel Grant, IEEE Seoul Section Student Paper Prize, and the 6th IDIS-ETNEWS Paper Award in 2014. Currently, he is the co-chair for IEEE GLOBECOM 2023 Symposium on Machine Learning for Communications, and an Associate Editor of Frontiers in Data Science for Communications and in Signal Processing for Communications. He is a Senior Member of IEEE and a Member of ACM and AAAI.
Zhijin Qin is currently an associate professor at Tsinghua University, China. She was with Queen Mary University of London and Lancaster University as a Lecturer and Imperial College London as a research associate from 2016 to 2022. Her research interest is semantic communications. She is serving as the guest editor of IEEE Communications Magazine Special Issue on semantic communications, an associate editor of IEEE Transactions on Communications, IEEE Transactions on Cognitive Networking, and IEEE Communications Letters. She served as the guest editor of IEEE JSAC Special Issue on semantic communications and area editor of IEEE JSAC Series. She also served as the symposium co-chair for IEEE GLOBECOM 2020 and 2021. She won the 2017 IEEE GLOBECOM Best Paper Award, 2018 IEEE Signal Processing Society Young Author Best Paper Award, 2021 IEEE Communications Society Signal Processing for Communications Committee Early Achievement Award, and 2022 IEEE Communications Society Fred W. Ellersick Prize.
Jinho Choi was born in Seoul, Korea. He received B.E. (magna cum laude) degree in electronics engineering in 1989 from Sogang University, Seoul, and M.S.E. and Ph.D. degrees in electrical engineering from Korea Advanced Institute of Science and Technology (KAIST) in 1991 and 1994, respectively. He is with the School of Information Technology, Burwood, Deakin University, Australia, as a Professor. Prior to joining Deakin in 2018, he was with Swansea University, United Kingdom, as a Professor/Chair in Wireless, and Gwangju Institute of Science and Technology (GIST), Korea, as a Professor. His research interests include the Internet of Things (IoT), wireless communications, and statistical signal processing. He authored two books published by Cambridge University Press in 2006 and 2010 and one book by Wiley-IEEE in 2022. Prof. Choi received a number of best paper awards including the 1999 Best Paper Award for Signal Processing from EURASIP. He is a Fellow of the IEEE and has been on the list of World’s Top 2% Scientists by Stanford University since 2020. Currently, he is a Senior Editor of IEEE Wireless Communications Letters and a Division Editor of Journal of Communications and Networks (JCN). He has also served as an Associate Editor or Editor of other journals including IEEE Trans. Communications, IEEE Communications Letters, JCN, IEEE Trans. Vehicular Technology, and ETRI journal.
T08: Holographic MIMO Communications: Fundamentals, Extreme Spatial Multiplexing and Mutual Coupling CANCELLED
Room 304, Kuala Lumpur Convention Center
Luca Sanguinetti (University of Pisa, Italy); Emil Björnson (KTH Royal Institute of Technology, Sweden)
Abstract:
Massive MIMO (multiple-input multiple-output) became a reality in 5G with 64-antenna fully digital base stations becoming commonplace. This technology constitutes a paradigm shift in the design of wireless technology, where the focus shifts from using more spectrum to using the spatial resources more effectively. Since the need for ubiquitous wireless access grows at an exponential pace, the logical consequence is that the array dimensions will continue to grow in the 6G era towards what is known as Holographic MIMO. In this future situation, the arrays are dense and electrically large, to exploit all the maximum spatial degrees of freedom for beamforming and spatial multiplexing. The first part of this tutorial covers the fundamentals of Holographic MIMO, which begins by determining the relation between wireless channels, electromagnetic waves, and antenna array geometries. Next, the new phenomena that appear in the radiative near-field will be characterized and shown to the dominant propagation regime in systems with large apertures and higher carrier frequencies. One such effect is to resolve spherical wavefronts for more precise spatial resolution, and another is the ability to perform finite-depth beamforming. Next, the theoretically maximum spatial degrees of freedom (DoF) will be derived, and it will be exemplified how the array geometry can be tweaked to make use of these DoF for massive spatial multiplexing. The second part of the tutorial focuses on understanding the electromagnetic interactions of closely spaced antennas in Holographic MIMO. The electric current flowing in one antenna excites its own electromagnetic field which is felt and responded to by the other neighboring antennas in the array. This results in strong mutual antenna coupling. Understanding the fundamentals and implications of mutual coupling requires the combination and integration of electromagnetic theory, information theory, signal processing and circuit theory. This is the point where the multiport communication theory comes into play whose main principles will be pedagogically introduced and used to derive a physically consistent model that is instrumental for the design and study of the uplink and downlink of Holographic MIMO with closely spaced antennas.
Bios:
Emil Björnson (S'07-M'12-SM'17-F'22) is a Professor of Wireless Communication at the KTH Royal Institute of Technology, Stockholm, Sweden. He is an IEEE Fellow, Digital Futures Fellow, and Wallenberg Academy Fellow. He has a podcast and YouTube channel called Wireless Future. His research focuses on multi-antenna communications and radio resource management, using methods from communication theory, signal processing, and machine learning. He has authored three textbooks and has published a large amount of simulation code. He has received the 2018 and 2022 IEEE Marconi Prize Paper Awards in Wireless Communications, the 2019 EURASIP Early Career Award, the 2019 IEEE Communications Society Fred W. Ellersick Prize, the 2019 IEEE Signal Processing Magazine Best Column Award, the 2020 PierreSimon Laplace Early Career Technical Achievement Award, the 2020 CTTC Early Achievement Award, the 2021 IEEE ComSoc RCC Early Achievement Award, and the 2023 IEEE Communications Society Outstanding Paper Award. His work has also received six Best Paper Awards at conferences.
Luca Sanguinetti (S'03-M'07-SM’15) is currently a Full Professor with the Dipartimento di Ingegneria dell’Informazione, University of Pisa. He has coauthored two textbooks Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency (2017) and Foundation of User-centric Cell-free Massive MIMO (2021). His expertise and general interests span the areas of communications and signal processing. He has received the 2018 and 2022 IEEE Marconi Prize Paper Awards in Wireless Communications, and the 2023 IEEE Communications Society Outstanding Paper Award. He was also the co-author of a paper that received the Young Best Paper Award from the ComSoc/VTS Italy Section. He served as an Associate Editor for IEEE TWC and the IEEE JSAC (series on Green Communications and Networking) and as a Lead Guest Editor for IEEE JSAC Special Issue on “Game Theory for Networks”, as an Associate Editor for the IEEE SPL. He was also a member of the Executive Editorial Committee of the IEEE TWC. He is currently serving as an Associate Editor for the IEEE TCOM and he is a member of the Steering Committee of IEEE TWC.
T09: Localization-of-Things in Beyond 5G Ecosystem CANCELLED
Room 305, Kuala Lumpur Convention Center
Moe Z. Win (Massachusetts Institute of Technology, USA); Andrea Conti (DE and CNIT, University of Ferrara, Italy)
Abstract: The availability of real-time high-accuracy location awareness is essential for current and future wireless applications, particularly those involving Internet-of-Things and beyond 5G ecosystems. The coming years will see the emergence of network localization and navigation in challenging environments with sub-meter accuracy, low latency, and minimal infrastructure requirements as the wireless ecosystem evolves beyond 5G networks. This will call for the Localization-of-Things (LoT), a recent paradigm referring to locating, tracking, and navigating collaborative and non-collaborative nodes (e.g., sensors, vehicles, and objects). LoT will be a critical component for a diverse set of applications including connected communities, smart environments, vehicle autonomy, asset tracking, medical services, military systems, and crowd sensing. We will discuss the limitations of traditional positioning and move on to the key enablers for high-accuracy location awareness: wideband transmission and cooperative processing. Topics covered will include: fundamental bounds, soft information (SI) based algorithms for 5G and beyond standardized scenarios, and network experimentation. Fundamental bounds serve as performance benchmarks, and as a tool for network design. SI-based algorithms are a way to achieve dramatic performance improvements compared to existing positioning. To harness these benefits, system designers must consider realistic operational settings; thus, we present the performance of SI-based localization algorithms in 3GPP scenarios. We will also present LoT enablers, including reconfigurable intelligent surfaces, which promise to provide a dramatic gain in terms of localization accuracy and system robustness in next generation networks toward 6G.
Bios:
Moe Z. Win is a Professor at the Massachusetts Institute of Technology (MIT). Prior to joining MIT, he was at AT&T Research Laboratories and at the NASA Jet Propulsion Laboratory. His research encompasses theoretical foundation, algorithm design, and network experimentation for a broad range of real-world problems. His current research topics include network localization and navigation, network interference exploitation, and quantum information science. Professor Win has served the IEEE Communications Society as an elected Member-at-Large on the Board of Governors, as elected Chair of the Radio Communications Committee, and as an IEEE Distinguished Lecturer. Over the last two decades, he held various Editorial posts for IEEE journals and organized numerous international conferences. Recently, he has served on the SIAM Diversity Advisory Committee. He was honored with two IEEE Technical Field Awards: the IEEE Kiyo Tomiyasu Award and the IEEE Eric E. Sumner Award. Other recognitions include the MIT Everett Moore Baker Award, the IEEE Vehicular Technology Society James Evans Avant Garde Award, the IEEE Communications Society Edwin H. Armstrong Achievement Award, the Cristoforo Colombo International Prize for Communications, the Copernicus Fellowship and the Laurea Honoris Causa from the Università degli Studi di Ferrara, and the U.S. Presidential Early Career Award for Scientists and Engineers. Professor Win is elected Fellow of the AAAS, the EURASIP, the IEEE, and the IET. He is an ISI Highly Cited Researcher.
Andrea Conti is a Professor at the University of Ferrara and Research Affiliate at the MIT Wireless Information and Network Sciences Laboratory. His research interests involve theory and experimentation of wireless systems and networks including network localization and distributed sensing. He received the HTE Puskás Tivadar Medal, the IEEE Communications Society’s Stephen O. Rice Prize in the field of Communications Theory, and the IEEE Communications Society’s Fred W. Ellersick Prize. Dr. Conti has served as editor for IEEE journals, as well as chaired international conferences. He has been elected Chair of the IEEE Communications Society’s Radio Communications Technical Committee. He is a co-founder and elected Secretary of the IEEE Quantum Communications & Information Technology Emerging Technical Subcommittee. Professor Conti is an elected Fellow of the IEEE and of the IET, and he has been selected as an IEEE Distinguished Lecturer.
T10: Differentiable Ray Tracing for Digital Twin Networks
Room 306, Kuala Lumpur Convention Center
Jakob Hoydis (Nvidia, France); Fayçal Ait Aoudia (NVIDIA, France); Sebastian Cammerer (NVIDIA, Germany)
Abstract: Digital Twin Networks (DTNs) are an emerging technology that will allow for the artificial intelligence (AI) and machine learning (ML)-based design, simulation, optimization, and control of 6G systems. Thanks to the recent progress of computer graphics, such as neural radiance fields (NeRFs), and other enabling technologies like LIDAR, scene geometries can be obtained with unprecedented accuracy in an automated fashion. However, the simulation of radio wave propagation via ray tracing does not only require accurate scene geometries but also the electromagnetic material properties of all scene objects. Obtaining the latter is a delicate task for which no mainstream solutions exist. In this tutorial, we will introduce a potential solution to this problem, called differentiable ray tracing for radio propagation modeling, which is inspired by the recently developed inverse rendering techniques in computer graphics. Apart from providing a solid theoretical introduction to (differentiable) ray tracing, we will explain different approaches to the creation of scenes and discuss several concrete applications of this novel technology which opens many exciting directions for future research. Of particular interest are learning-based approaches to aligning ray tracing algorithms and scene descriptions to measurements. All examples shown in the tutorial can be reproduced with the freely available open-source link-level simulator Sionna that is developed and maintained by the instructors.
Bios:
Jakob Hoydis is a Principal Research Scientist at NVIDIA working on the intersection of machine learning and wireless communications. Prior to this, he was head of a research department at Nokia Bell Labs, France, and co-founder of the social network SPRAED. He is one of the maintainers and core developers of the Sionna open-source link-level simulator. He obtained the diploma degree in electrical engineering from RWTH Aachen University, Germany, and the Ph.D. degree from Supéléc, France. He is a Distinguished Industry Speaker of the IEEE Signal Processing Society for the 2023-2024 term. From 2019-2021, he was chair of the IEEE COMSOC Emerging Technology Initiative on Machine Learning as well as Editor of the IEEE Transactions on Wireless Communications. Since 2019, he is Area Editor of the IEEE JSAC Series on Machine Learning in Communications and Networks. He is recipient of the 2019 VTG IDE Johann-PhilippReis Prize, the 2019 IEEE SEE Glavieux Prize, the 2018 IEEE Marconi Prize Paper Award, the 2015 IEEE Leonard G. Abraham Prize, the IEEE WCNC 2014 Best Paper Award, the 2013 VDE ITG Förderpreis Award, and the 2012 Publication Prize of the Supéléc Foundation. He has received the 2018 Nokia AI Innovation Award, as well as the 2018 and 2019 Nokia France Top Inventor Awards. He is a co-author of the textbook “Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency” (2017).
Fayçal Aït Aoudia is a Senior Research Scientist at NVIDIA working on the convergence of wireless communications and machine learning. Before joining NVIDIA, he was a research scientist at Nokia Bell Labs, France. He is one of the maintainers and core developers of the Sionna open-source link-level simulator. He obtained the diploma degree in computer science from the Institut National des Sciences Appliquées de Lyon, France, in 2014, and the PhD in signal processing from the University of Rennes 1, France, in 2017. He has received the 2018 Nokia AI Innovation Award, as well as the 2018, 2019, and 2020 Nokia Top Inventor Awards
Sebastian Cammerer is a Research Scientist at NVIDIA. Before joining NVIDIA, he received his PhD in electrical engineering and information technology from the University of Stuttgart, Germany, in 2021. He is one of the maintainers and core developers of the Sionna open-source link-level simulator. His main research topics are machine learning for wireless communications and channel coding. Further research interests include parallel computing for signal processing and information theory. He is recipient of the IEEE SPS Young Author Best Paper Award 2019, the Best Paper Award of the University of Stuttgart 2018, the Anton- und Klara Röser Preis 2016, the Rohde&Schwarz Best Bachelor Award 2015, the VDE-Preis 2016 for his master thesis and third prize winner of the Nokia Bell Labs Prize 2019.
December 8, Friday - Morning Session (9:00 - 12:30)
T11: Why OTFS 2.0 - How to make Communication and Radar Sensing More Predictable in 6G
Room 302, Kuala Lumpur Convention Center
Saif Khan Mohammed (Indian Institute of Technology Delhi, India); Ronny Hadani (University of Texas-Austin, USA); A. Chockalingam (Indian Institute of Science, India); Robert Calderbank (Duke University, USA)
Abstract: 6G presents an opportunity to reflect on the fundamentals of wireless communication, as it becomes more and more difficult to estimate, track and equalize channels with Doppler spreads measured in KHz. It is an opportunity to question the standard model-dependent approach to wireless communication that requires channel estimation. Orthogonal Time Frequency Space (OTFS) 2.0 modulation waveform is designed to make communication and radar sensing more predictable. It is a pulse in the delay-Doppler (DD) domain, formally a quasi-periodic localized function with specific periods along delay and Doppler. Viewed in the time domain, it is realized as a pulse train modulated by a tone (pulsone). The main insight of the tutorial is that, when the channel delay spread is less than the delay period, and the channel Doppler spread is less than the Doppler period, the OTFS 2.0 input-output (I/O) relation is predictable and non-fading. Given the I/O response at one DD point in a frame, it is possible to predict the I/O response at all other points. It is possible to learn the I/O relation without estimating the channel, opening up the possibility of a model-free mode of operation. The counterpart of predictability in radar sensing is unambiguous delay-Doppler estimation. To date, most research attention has focused on OTFS 1.0, which was constrained to be compatible with OFDM modulators used in 4G/5G systems, but is less predictable in high delay/Doppler spread scenarios than OTFS 2.0. This tutorial is timely since the challenges of 6G have renewed interest in waveform design.
Bios:
Saif Khan Mohammed is a Professor with the Department of Electrical Engineering, Indian Institute of Technology Delhi (IIT Delhi). He currently holds the Prof. Kishan and Pramila Gupta Chair at IIT Delhi. He received the B.Tech. degree in Computer Science and Engineering from IIT Delhi, New Delhi, India, in 1998, and the Ph.D. degree from the Electrical and Communication Engineering Department, Indian Institute of Science, Bangalore, India, in 2010. From 2010 to 2011, he was a Post-Doctoral Researcher at the Communication Systems Division (Commsys), Electrical Engineering Department (ISY), Linkoping University, Sweden. He was an Assistant Professor at Commsys, from September 2011 to February 2013. His main research interests include, waveforms for high mobility scenarios in sixth generation (6G) communication systems, wireless communication using large antenna arrays, coding and signal processing for wireless communication systems, information theory, and statistical signal processing. He currently serves as an Editor for the IEEE Transactions on Wireless Communications and in the past he has served as an Editor for the IEEE Wireless Communications Letters and Physical Communication journal (Elsevier). He holds four granted U.S. patents in multi-user detection and precoding for multiple-input multiple-output (MIMO) communication systems. He received the 2017 NASI Scopus Young Scientist Award and the Teaching Excellence Award at IIT Delhi for the year 2016–2017. He was also a recipient of the Visvesvaraya Young Faculty Fellowship from the Ministry of Electronics and IT, Government of India, from 2016 to 2019.
Ronny Hadani is an associate professor in the Mathematics Department of the University of Texas at Austin. Prior to that he was a Dickson post-doctoral fellow in the University of Chicago. His field of expertise is representation theory and harmonic analysis. Hadani is a cofounder of Cohere technologies and currently serves as its Chief Science Officer. Hadani is a co-inventor of the OTFS modulation technique and has been granted over 70 OTFS related patents. Hadani holds a PhD in pure mathematics from Tel-Aviv University under advisory of Professor Joseph Bernstein and a Master degree in applied mathematics from The Weizmann Institute of Science under advisory of Professor David Harel. Ananthanarayanan Chockalingam is a Professor in the Department of Electrical Communication Engineering, Indian Institute of Science, Bangalore, India, working in the area of wireless communications. He has made pioneering contributions in the area of large-scale/massive MIMO systems. He has served as an Associate Editor of the IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, as an Editor of the IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, and as a Guest Editor for the IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS and IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING. He is a Fellow of the Indian National Academy of Engineering, the National Academy of Sciences, India, the Indian National Science Academy, and the Indian Academy of Sciences. He is a recipient of the prestigious J. C Bose Fellowship from the Science and Engineering Research Board, Department of Science & Technology, Government of India. He is an author of the book on ‘Large MIMO Systems’ published by Cambridge University Press.
Robert Calderbank directs the Rhodes Information initiative at Duke University, where he is a Distinguished Professor of Electrical and Computer Engineering, Computer Science and Mathematics. He started his career in the Mathematical Sciences Research Center at Bell Labs, and he left AT&T in 2003 as Vice President for Research. Dr. Calderbank directed the Program in Applied and Computational Mathematics at Princeton University before joining Duke University in 2010. He was elected to the National Academy of Engineering in 2005, and to the American Academy of Arts and Sciences in 2022. Dr. Calderbank received the 2015 Hamming Medal, and the 2015 Shannon Award. Dr. Calderbank is known for contributions to voiceband modem technology at the dawn of the internet, and for contributions to wireless communication that are incorporated in billions of cell phones. He has also made contributions to 5 quantum error correction that provide a foundation for fault tolerant quantum computation.
T12: What Next Generation Multiple Access Will Be?
Room 303, Kuala Lumpur Convention Center
Zhiguo Ding (University of Manchester, United Kingdom (Great Britain)); Yuanwei Liu (Queen Mary University of London, United Kingdom (Great Britain))
Abstract:
Due to the explosive growth in the number of wireless devices and diverse wireless services, such as virtual/augmented reality and Internet-of-Everything, next-generation wireless networks face unprecedented challenges caused by heterogeneous data traffic, massive connectivity, ultra-high bandwidth efficiency and ultra-low latency requirements. To address these challenges, advanced multiple access schemes are expected to be developed, namely next-generation multiple access (NGMA), which are capable of supporting massive numbers of users and network functions, e.g., communication, computation, and sensing, in a more resource- and complexity-efficient manner than existing multiple access schemes. Although the research on NGMA is in a very early stage, the trend of NGMA primarily aims to transition from orthogonality to non-orthogonality. Serving multiple users in the same orthogonal time/frequency resource helps to further enhance spectral efficiency. This tutorial introduces the "One Basic Principle plus Four New" concept for designing NGMA, which begins with the basic principle by exploring possible multiple access techniques in a non-orthogonal manner. The tutorial then delves into the application of NGMA to meet the new 6G performance requirements, particularly for massive connectivity in Internet-of-things networks. Next, it presents the interplay between NGMA and emerging physical-layer techniques, e.g., near-field communications, integrated sensing and communications, THz networks, age of information, and simultaneously transmitting and reflecting surfaces. Furthermore, the tutorial discusses practical applications of NGMA designs, such as semantic communications and mobile edge computing. Finally, it investigates the use of machine learning in NGMA networks, ushering in the era of machine learning-empowered NGMA for intelligent multiple access in 6G.
Bios:
Zhiguo Ding received his Ph.D degree in Electrical Engineering from Imperial College London in 2005. Since Apr. 2018, he has been with the University of Manchester as a Professor in Communications. From Sept. 2012 to Sept. 2020, he has also been an academic visitor in Princeton University. Dr Ding’ research interests are machine learning, B5G networks, cooperative and energy harvesting networks, and statistical signal processing. He is serving as an Area Editor for the IEEE OJ-COMS, an Editor for IEEE TVT and OJ-SP, and was an Editor for IEEE TCOM, IEEE WCL, IEEE CL and WCMC. He was the TPC Co-Chair for the 6th IET ICWMMN2015, Symposium Chair for ICNC 2016, and the 25th WOCC, and Co-Chair of WCNC-2013 Workshop on New Advances for Physical Layer Network Coding. He received the best paper award in IET Comm. Conf. on Wireless, Mobile and Computing 2009 and the International Conference on WCSP 2015, the EU Marie Curie Fellowship 2012-2014, IEEE TVT Top Editor 2017, 2018 IEEE Communication Society Heinrich Hertz Award, 2018 IEEE Vehicular Technology Society Jack Neubauer Memorial Award, and 2018 IEEE Signal Processing Society Best Signal Processing Letter Award. He is a Web of Science Highly Cited Researcher and a Fellow of the IEEE.
Yuanwei Liu received the Ph.D. degree from the Queen Mary University of London (QMUL), U.K., in 2016. He has been a Senior Lecturer (Associate Professor) with the School of Electronic Engineering and Computer Science, QMUL, since Aug. 2021. His research interests include NOMA, RIS, ISAC, and machine learning. He is a Web of Science Highly Cited Researcher in 2021 and 2022, an IEEE ComSoc Distinguished Lecturer, an IEEE VTS Distinguished Lecturer, the academic Chair for the NGMA Emerging Technology Initiative, and the vice chair of the IEEE TCCN. He received IEEE ComSoc Outstanding Young Researcher Award for EMEA in 2020. He received the 2020 IEEE SPCC and 2021 CTTC Technical Early Achievement Awards. He received IEEE ComSoc Outstanding Nominee for Best Young Professionals Award in 2021. He is the co-recipient of the Best Student Paper Award in IEEE VTC2022-Fall, the Best Paper Award in ISWCS 2022, and IEEE SPCC Best Paper Award 2022. He serves as a Senior Editor of IEEE Communications Letters, an Editor of the IEEE TWC, the IEEE TCOM and the IEEE TNSE. He serves as the Guest Editor for IEEE JSAC, IEEE JSTSP, and IEEE Network. He serves as the Publicity Co-Chair for IEEE VTC 2019-Fall, Symposium Co-Chair for Cognitive Radio & AI-Enabled Networks for IEEE GLOBECOM 2022 and Communication Theory for IEEE GLOBECOM 2023. He serves as the chair of Special Interest Group (SIG) in SPCC Technical Committee on signal processing Techniques for NGMA, the vice-chair of SIG WTC on RISs for Smart Radio Environments.
T13: Towards 6G Communications: Wireless Channel Measurements, Characteristics Analysis, and Modeling
Room 304, Kuala Lumpur Convention Center
Cheng-Xiang Wang (Southeast University, China & Purple Mountain Laboratories, China); Jie Huang (Southeast University, China); Chen Huang (Purple Mountain Laboratories & Southeast University & Beijing Jiaotong University, China); Harald Haas (The University of Strathclyde, United Kingdom (Great Britain))
Abstract: For the design, performance evaluation, and optimization of wireless communication systems, channel measurements and realistic channel models with good accuracy-complexity-pervasiveness trade-off are indispensable. The proposed tutorial is intended to offer a comprehensive and in-depth course to communication professionals/academics, aiming to address recent advances and future challenges on channel measurements and modeling methods for sixth generation (6G) wireless systems. Network architecture and key technologies for 6G that will enable global coverage, all spectra, and full applications will be first discussed. Channel measurements and non-predictive channel models are then reviewed for challenging 6G scenarios and frequency bands, focusing on millimeter wave, terahertz, and optical wireless communication channels under all spectra, satellite, unmanned aerial vehicle, and maritime communication channels under global coverage scenarios, and vehicle-to-vehicle, ultra-massive multiple-input multiple-output (MIMO), industrial Internet of things (IoT), reconfigurable intelligent surface (RIS), and integrated sensing and communication (ISAC) channels under full application scenarios. New beam domain channel models and artificial intelligence (AI)/machine learning (ML) based space-time-frequency predictive channel models will also be investigated. A non-predictive 6G pervasive channel model for all frequency bands and all scenarios will then be proposed, which is expected to serve as a baseline for future standardized 6G channel models. Future research challenges and trends for 6G channel measurements and models will be discussed in the end of the tutorial.
Bios:
Prof. Cheng-Xiang Wang received the B.Sc. and M.Eng. degrees in communication and information systems from Shandong University, China, in 1997 and 2000, respectively, and the Ph.D. degree in wireless communications from Aalborg University, Denmark, in 2004. He has been with Heriot-Watt University, Edinburgh, United Kingdom, since 2005 and became a professor in 2011. In 2018, he joined Southeast University, China, and Purple Mountain Laboratories, China, as a professor. He is now the Executive Dean of the School of Information Science and Engineering, Southeast University. He has authored 4 books, 3 book chapters, and more than 490 papers in refereed journals and conference proceedings, including 25 highly cited papers. He has also delivered 24 invited keynote speeches/talks and 17 tutorials in international conferences. His current research interests include wireless channel measurements and modeling, 6G wireless communication networks, and electromagnetic information theory. He is a Member of the Academia Europaea (The Academy of Europe), a Fellow of the Royal Society of Edinburgh, IEEE, IET, and China Institute of Communication (CIC), an IEEE Communications Society Distinguished Lecturer in 2019 and 2020, and a Highly-Cited Researcher recognized by Clarivate Analytics in 2017-2020. He is currently an Executive Editorial Committee Member of the IEEE TWC. He has served as an Editor for over ten international journals. He has served as a TPC Member, a TPC Chair, and a General Chair for more than 80 international conferences. He received 15 Best Paper Awards.
Dr. Jie Huang received the B.E. degree in Information Engineering from Xidian University, China, in 2013, and the Ph.D. degree in Information and Communication Engineering from Shandong University, China, in 2018. From Oct. 2018 to Oct. 2020, he was a Postdoctoral Research Associate in the National Mobile Communications Research Laboratory, Southeast University, China, supported by the National Postdoctoral Program for Innovative Talents. From Jan. 2019 to Feb. 2020, he was a Postdoctoral Research Associate in Durham University, U.K. Since Mar. 2019, he is a parttime researcher in Purple Mountain Laboratories, China. Since Nov. 2020, he is an Associate Professor in the National Mobile Communications Research Laboratory, School of Information Science and Engineering, Southeast University, China. He has authored and co-authored more than 70 papers in refereed journals and conference proceedings. He received 3 Best Paper Awards from WPMC 2016, WCSP 2020, and WCSP 2021. He has also delivered 10 tutorials in various conferences. His research interests include millimeter wave, massive MIMO, reconfigurable intelligent surface channel measurements and modeling, wireless big data, and 6G wireless communications.
Dr. Chen Huang received the Ph.D. degree from Beijing Jiaotong University, China, in 2021. He is currently a research assistant professor in Purple Mountain Laboratories, China, and also a Post Doc in Southeast University, China. From 2018 to 2020, he has been a Visiting Scholar with the University of Southern California, Los Angeles, CA, USA and with the Universite Catholique de Louvain (UCL), Louvain-la-Neuve, Belgium. Dr. Huang is selected in the Young Elite Scientists Sponsorship Program by China Association for Science and Technology, and Outstanding Postdoctoral Fellow Program in Jiangsu, received two Best Paper Awards at international conferences, and serves as the Technical Program Committee (TPC) member for several conferences, such as VTC-fall, GlobeCom. His research interests include channel characterization, AI-based 6G channel modeling. He has authored/co-authored 1 book chapters, more than 40 journal and conference papers, as well as several patents.
Prof. Harald Haas received the Ph.D. degree in wireless communications from the University of Edinburgh, Edinburgh, U.K., in 2001. He is the Director of the LiFi Research and Development Centre at the University of Strathclyde. He is also the Initiator, co-founder and Chief Scientific Officer of pureLiFi Ltd. He has authored 630 conference and journal papers, including papers in Science and Nature Communications. His main research interests are in optical wireless communications, hybrid optical wireless and RF communications, spatial modulation, and interference coordination in wireless networks. His team invented spatial modulation. He introduced LiFi to the public at an invited TED Global talk in 2011. He gave a second TED Global lecture in 2015 on the use of solar cells as LiFi data detectors and energy harvesters. In 2016, he received the Outstanding Achievement Award from the International Solid State Lighting Alliance. In 2019 he was recipient of IEEE Vehicular Society James Evans Avant Garde Award. Haas was elected a Fellow of the Royal Society of Edinburgh (RSE) in 2017. In the same year he received a Royal Society Wolfson Research Merit Award and was elevated to IEEE Fellow. In 2018 he received a three-year EPSRC Established Career Fellowship extension and was elected Fellow of the IET. He was elected Fellow of the Royal Academy of Engineering (FREng) in 2019. In 2022 he was the recipient of a Humboldt Research Award for his research achievements to date.
T14: Non-Terrestrial Networks for the Next Generation Global Connectivity
Room 305, Kuala Lumpur Convention Center
Aryan Kaushik (University of Sussex, United Kingdom (Great Britain)); Muhammad Zeeshan Shakir (University of the West of Scotland, United Kingdom (Great Britain)); Wonjae Shin (Ajou University, Korea (South))
Abstract:
There is an indispensable need of technical advancements and digital transformation for the next generation communication networks not only supporting terrestrial setups but also the emerging satellite and sky-oriented technologies. In the direction of non-terrestrial networks (NTNs) technology, evolving signal processing methods, edge and cloud computing, deep reinforcement learning techniques for low Earth orbit (LEO) satellites and unmanned aerial vehicles (UAVs)/flying platforms in NTNs, next generation multiple access (NGMA)-assisted deployments for NTNs, etc., have drastically changed the current realization of the space, sky and terrestrial communication networks. This tutorial will present a comprehensive overview of the emerging NTNs based wireless networking including fundamentals, requirements and emerging problem design concepts. The tutorial will cover key enabling technologies for NTNs such as green artificial intelligence (AI) for NTNs, deep reinforcement learning and edge computing enabled NTNs, robust multiple-input multiple-output (MIMO) beamforming and interference management through NGMA for NTNs, UAVs/flying platforms in NTNs, and wireless fronthaul/backhaul NTN technologies which have led to the development of exciting new vertical frameworks.
Bios:
Prof. Aryan Kaushik is Assistant Professor at the University of Sussex, UK. He has been with University College London, UK, from 2020-21, University of Edinburgh, UK, from 2015-19, and Hong Kong University of Science and Technology, Hong Kong, from 2014-15. He has held visiting appointments at Imperial College London, UK, University of Luxembourg, Luxembourg, Beihang University, China, and Athena RC, Greece. He is the Editor of upcoming book on “Integrated Sensing and Communications for Future Wireless Networks: Principles, Advances and Key Enabling Technologies,” Elsevier. He has been Associate Editor of the IEEE Open Journal of the Communications Society, IEEE Communications Letters, IET Signal Processing and IET Networks, and Lead/Co-Lead Guest Editor for several Special Issues at IEEE and IET journals such as IEEE Internet of Things Magazine and IEEE Open Journal of the Communications Society. He has been a Tutorial/Invited Speaker at IEEE WCNC 2023 conference and workshop, EuCNC and 6G Summit, ICASIS 2023 and WiSPNET 2023, Track Chair at IEEE ICC 2024 and IEEE WCNC 2023, Publication Chair at IEEE WCNC 2024 and IEEE ICMLCN 2024, Tutorial Chair at IEEE WF-PST 2024, and General Chair for workshops at IEEE conferences such as IEEE PIMRC 2023, IEEE WCNC 2023, IEEE PIMRC 2022 and IEEE SECON 2022. He has been a TPC Member at IEEE ICC 2021-23 and IEEE Globecom 2023, Sessions Chair at IEEE WCNC 2023, and Conference Champion at IEEE PIMRC 2020. https://sites.google.com/view/aryankaushik/
Prof. Muhammad Zeeshan Shakir is Professor of Wireless Communications at the University of the West of Scotland (UWS), UK has received over £3m research funding from Innovate UK, ERASMUS, QNRF and Scottish Govt. He has over 15 years’ experience in digital technologies, published over 150 research articles and contributed to 10 books. He is a recipient of numerous awards including Scottish Association of Minority Ethnic Educators (SAMEE) STEM Inspiring Diversity and Inclusion award 2022, SICSA (The Scottish Informatics and Computer Science Alliance) Best Poster Award 2022, IEEE Communications Society Fred W. Ellersick Award 2021, IEEE Communications Society and China Institute of Communications Best Journal Article Award 2019 and UWS STARS Award 2020 & 2018 for outstanding research, teaching and enterprise performances. He is a Fellow of Higher Education Academy, UK, Senior Member of IEEE, member of IEEE Communications Society, Royal Society of Edinburgh, Young Academy of Scotland and Scottish Parliament Framework Agreement Covid-19 Pandemic. He is serving as a chair and organizing committee in several IEEE flagship conferences, including Globecom, ICC and WCNC. He is a frequent keynote speaker at IEEE flagship conferences. He is Chair of IEEE ComSoc emerging technologies committee on backhaul/fronthaul, and Public Safety Technology Committee. https://research-portal.uws.ac.uk/en/persons/muhammad-zeeshan-shakir-shakir
Prof. Wonjae Shin is Associate Professor at Ajou University, South Korea. He was Faculty Member with Pusan National University, from 2018-21. He received B.S. and M.S. from KAIST, South Korea, in 2005 and 2007, respectively, and Ph.D. from Seoul National University, in 2017. From 2007-14, he was a Technical Staff with the Samsung AIT and Samsung Electronics Ltd., South Korea. From 2016-18, he was Visiting Scholar and Research Fellow with Princeton University, NJ, USA. He is Senior Member of the IEEE. He was recipient of Fred W. Ellersick Prize and Asia-Pacific Outstanding Young Researcher Award from IEEE ComSoc in 2020, Best Ph.D. Dissertation Award in 2017, Gold Prize from IEEE Student Paper Contest in 2014, and Award of the Ministry of Science and ICT of Korea in 2017. He was a corecipient of the SAIT Patent Award (2010), Samsung JIT (2010), Samsung Human Tech Paper Contest (2010), and Samsung CEO Award (2013). He was “Exemplary Reviewer” for IEEE WCL in 2014 and IEEE TCOM in 2019. He is Editor for IEEE OJCOMS, workshop co-chair at IEEE PIMRC 2020/22, IEEE WCNC 2022 and IEEE ICC 2022. He served as Guest Editor for ICT Express and IET Signal Processing Special Issues. https://sites.google.com/view/theshinlab/home
T15: Automating 6G Operations: Architectural Design and Service Optimization
Room 401, Kuala Lumpur Convention Center
Anwer Al-Dulaimi (EXFO Inc., Canada)
Abstract:
As fifth-generation (5G) networks continue to be deployed, researchers and industry experts are already exploring potential use cases and enabling technologies for the next generation: 6G. These networks will be designed to incorporate new and innovative technologies, including Artificial Intelligence (AI), digital twin, quantum networking, blockchains, and more. However, integrating these technologies will increase network complexity, leading to new challenges in managing the network infrastructure and ensuring smooth operations. This tutorial provides an overview of the potential use cases for 6G networks, the various elements of such networks, the integration of new technologies, and most importantly, how to manage 6G network operations. It covers topics such as the architecture and components of 6G networks, network management and monitoring tools, and the challenges and opportunities for automating 6G services. The tutorial also explores the role of AI in 6G network management, including the use of machine learning algorithms to optimize network performance and enhance security. It provides insights into the implementation of advanced network management practices, such as automation, orchestration, and selforganizing networks. This tutorial is designed for academics, postgraduates, network operators, engineers, and managers who are interested in staying ahead of the curve in managing the next generation of wireless networks. By the end of the tutorial, attendees will have a solid understanding of the key concepts, best practices, and challenges in 6G network management.
Bios:
Anwer Al-Dulaimi is currently a Senior Manager for Emerging technologies & Innovations and Distinguished Member of the Technical Staff in the 5G Center of Excellence at EXFO, Montreal, Canada. He received the Ph.D. degree in electrical and computer engineering from Brunel University, London, U.K., in 2012 after receiving M.Sc. and B.Sc. honors degrees in communication engineering. He was a Postdoctoral Fellow with the Department of Electrical and Computer Engineering, University of Toronto, sponsored by Blackberry’s advanced research team. He is the chair of the newly established IEEE 5G/6G Innovations testbed working to develop a virtual testing platform for E2E network innovation. His research interests include 5G and 6G networks, cloud computing, Blockchains and cybersecurity. Dr. Al-Dulaimi is the editor of Future Networks Series on 5G & 6G in IEEE Vehicular Technology magazine, Editor of Vehicular Networking Series in IEEE Standards Magazine, Editor of IEEE ITSS Series on Intelligent Autonomous Transport, and guest editor for many IEEE journals. He was the recipient of the 2013 Worldwide Universities Network best paper for outstanding research in cognitive communications, best IEEE/WWRF VTM best paper award for 3 times, as well as many other awards and grants. He has published many papers in refereed publications and patents. He provided many talks about 5G/6G networks in academia, industry forums, O-RAN and ITU. He is the chair of the IEEE 1932.1 ‘Standard for Licensed/Unlicensed Spectrum Interoperability in Wireless Mobile Network’, invited expert to ITU-T SG11, and voting member of IEEE MobiNet Standards Committee. He is an IEEE ComSoc Distinguished Lecturer, Fellow of the Institution of Engineering and Technology (FIET), Associate Fellow of the British higher education Academy (AFHEA) and registered as a Chartered Engineer (CEng) by the British Engineering Council since 2010. He is a member of the discovery grants committee for the Natural Sciences and Engineering
December 8, Friday – Afternoon Session (14:00 - 17:30)
T16: Developing the Metaverse with Edge Intelligence: A Tutorial
Room 302, Kuala Lumpur Convention Center
Dusit Niyato (Nanyang Technological University, Singapore); Zehui Xiong (Singapore University of Technology and Design, Singapore); Wei Yang Bryan Lim (Nanyang Technological University & Alibaba-NTU Joint Research Institute, Singapore); Hoang Thai Dinh (University of Technology Sydney (UTS), Australia)
Abstract: In 2021, Facebook was even rebranded as "Meta" as it reinvents itself to be a "Metaverse company" from a "social media" company. Furthermore, Government bodies around the world have announced their interest in establishing a presence in the Metaverse. However, the development of the Metaverse is still in its infancy. The stringent sensing, communication, and computation requirements impede the real-time, scalable, and ubiquitous implementation of the Metaverse. In this tutorial, we begin by presenting to the audience the current progress in the development of the Metaverse. Then, we motivate the definition and introduction to the architecture of the Metaverse, as well as highlight upcoming trends and novel applications both from the industry and academia. To realize the Metaverse and its unique challenges, we mainly focus on the edge intelligence driven infrastructure layer, which is a core feature in future wireless networks. In short, edge intelligence is the convergence between edge computing and AI. We adopt the two commonly-quoted divisions of edge intelligence, i.e., i) Edge for AI: which refers to the end-to-end framework of bringing sensing, communication, AI model training, and inference closer to where data is produced, and ii) AI for Edge: which refers to the use of AI algorithms to improve the orchestration of the aforementioned framework. Then, as a case study, we present a framework for the collaborative edge-driven virtual city development in the Metaverse. Finally, we discuss the open research issues.
Bios:
Dusit Niyato is currently a professor in the School of Computer Science and Engineering, Nanyang Technological University, Singapore. Currently, Dusit is serving as editor-in-chief of IEEE Communications Surveys and Tutorials, an area editor of IEEE Transactions on Vehicular Technology, an editor of IEEE Transactions on Wireless Communications, an associate editor of IEEE Internet of Things Journal, IEEE Transactions on Mobile Computing, IEEE Wireless Communications, IEEE Network, and ACM Computing Surveys. He is a Fellow of IEEE.
Zehui Xiong is currently an Assistant Professor in the Pillar of Information Systems Technology and Design, Singapore University of Technology and Design. He is now serving as the editor or guest editor for many leading journals including IEEE JSAC, TVT, IoTJ, TCCN, TNSE, ISJ, JAS. He is the recipient of IEEE TCSC Early Career Researcher Award for Excellence in Scalable Computing, IEEE TEMS Technical Committee on Blockchain and Distributed Ledger Technologies Early Career Award.
Wei Yang Bryan Lim is currently a researcher and Wallenberg-NTU Presidential Postdoctoral Fellow. He received the PhD degree in Nanyang Technological University (NTU), Singapore, in 2022 under the Alibaba PhD Talent Programme.
Dinh Thai Hoang is currently a faculty member at the School of Electrical and Data Engineering, University of Technology Sydney, Australia. He received his Ph.D. in Computer Science and Engineering from the Nanyang Technological University, Singapore, in 2016. Currently, he is an Editor of IEEE Transactions on Wireless Communications, IEEE Transactions on Cognitive Communications and Networking, IEEE Transactions on Vehicular Technology, and Associate Editor of IEEE Communications Surveys & Tutorials.
T17: Rate-Splitting Multiple Access for 6G: Recent Advances and Future Research Trends
Room 303, Kuala Lumpur Convention Center
Daniel Benevides da Costa (Technology Innovation Institute, United Arab Emirates); Yijie Mao (ShanghaiTech University, China); Zhaohui Yang (Zhejiang University, China); Bruno Clerckx (Imperial College London, United Kingdom (Great Britain))
Abstract:
This tutorial focuses on a more general and powerful transmission framework, namely, rate-splitting multiple access (RSMA) based on rate-splitting (RS) that splits messages into common and private parts and enables to partially decode interference and treat remaining part of the interference as noise. This enables RSMA to softly bridge and therefore reconcile the two extreme strategies of fully decode interference and treat interference as noise and provide room for spectral efficiency, energy efficiency and QoS enhancements, robustness to imperfect channel state information at the transmitter (CSIT), and feedback overhead and complexity reduction. RSMA provides a powerful framework for the design and optimization of non-orthogonal transmission, multiple access, and interference management strategies. Thanks to its versatility, RSMA has the potential to tackle challenges of modern communication systems and is a gold mine of research problems for academia and industry, spanning fundamental limits, optimization, PHY and MAC layers, and standardization.
Bios:
Daniel Benevides Da Costa was born in Fortaleza, Cear, Brazil, in 1981. He received the B.Sc. degree in telecommunications from the Military Institute of Engineering (IME), Rio de Janeiro, Brazil, in 2003, and the M.Sc. and Ph.D. degrees in electrical engineering, area: telecommunications from the University of Campinas, So Paulo, Brazil, in 2006 and 2008, respectively. His Ph.D. Thesis was awarded the Best Ph.D. Thesis in electrical engineering by the Brazilian Ministry of Education (CAPES) at the 2009 CAPES Thesis Contest. From 2008 to 2009, he was a Postdoctoral Research Fellow with INRS-EMT, University of Quebec, Montreal, QC, Canada. From 2010 to 2022, he was with the Federal University of Cear, Brazil. From January 2019 to April 2019, he was a Visiting Professor at the Lappeenranta University of Technology (LUT), Finland, with financial support from Nokia Foundation. He was awarded with the prestigious Nokia Visiting Professor Grant. From May 2019 to August 2019, he was with the King Abdullah University of Science and Technology (KAUST), Saudi Arabia, as a Visiting Faculty. From September 2019 to November 2019, he was a Visiting Researcher at Istanbul Medipol University, Turkey. From 2021 to 2022, he was a Full Professor at the National Yunlin University of Science and Technology (YunTech), Taiwan. Since 2022, he has been with the AI and Digital Science Research Center, Technology Innovation Institute (TII), a global research center and the applied pillar of Abu Dhabis Advanced Technology Research Council. He has acted as a symposium co-chair /a track co-chair in numerous IEEE flagship conferences. He is the editor of several IEEE journals.
Yijie (Lina) Mao is an Assistant Professor at the School of Information Science and Technology, ShanghaiTech University, Shanghai, China. She received the B.Eng. degree from the Beijing University of Posts and Telecommunications, and the B.Eng. (Hons.) degree from the Queen Mary University of London (London, United Kingdom) in 2014. She received the Ph.D. degree in the Electrical and Electronic Engineering Department from the University of Hong Kong (Hong Kong, China) in 2018. She was a Postdoctoral Research Fellow at the University of Hong Kong (Hong Kong, China) from Oct. 2018 to Jul. 2019 and a postdoctoral research associate with the Communications and Signal Processing Group (CSP), Department of the Electrical and Electronic Engineering at the Imperial College London (London, United Kingdom) from Aug. 2019 to Jul. 2021. Her research interests include the design of future wireless communications and artificial intelligence-empowered wireless networks. She is a senior member of China Institute of Communications. Dr. Mao receives the Best Paper Award of EURASIP Journal on Wireless Communications and Networking 2022 and the Exemplary Reviewer for IEEE Transactions on Communications 2021. She is currently serving as a guest editor for special issues of IEEE Journal on Selected Areas in Communications and IEEE Open Journal of the Communications Society. She has been a workshop co-chair for 2020-2022 IEEE ICC, 2021-2022 IEEE WCNC, and 2020, 2022 IEEE PIMRC, and she has been a Technical Program Committee (TPC) member of many symposia on wireless communication for several leading international IEEE conferences.
Zhaohui Yang received the B.S. degree in information science and engineering from Chien-Shiung Wu Honors College, Southeast University, Nanjing, China, in June 2014, and the Ph.D. degree in communication and information system with the National Mobile Communications Research Laboratory, Southeast University, Nanjing, China, in May 2018. From 2018 to 2020, he was a Postdoctoral Research Associate with the Center for Telecommunications Research, Department of Informatics, Kings College London, UK. From 2020 to 2022, he was a Research Fellow with the Department of Electronic and Electrical Engineering, University College London, UK. He is currently a ZJU young Professor with College of Information Science and Electronic Engineering Zhejiang Key Lab of Information Processing Communication and Networking, Zhejiang University, and also a Research Scientist with Zhejiang Lab. He is an Associate Editor for the IEEE Communications Letters, IET Communications and EURASIP Journal on Wireless Communications and Networking. He has guest edited a feature topic/special issue of IEEE Communications Magazine, IEEE Wireless Communications, and IEEE Journal on Selected Areas in Communications. He was a Co-Chair for international workshops with more than 10 times including ICC, GLOBECOM, WCNC, PIMRC, INFOCOM. His research interests include joint communication, sensing, and computation, federated learning, reconfigurable intelligent surface, UAV, and NOMA. He was a TPC member of IEEE ICC during 20152022 and GLOBECOM during 2017-2022. He was an exemplary Reviewer for IEEE Transactions on Communications in 2019 and 2020.
Bruno Clerckx (Fellow, IEEE) is a (Full) Professor, the Head of the Wireless Communications and Signal Processing Lab, and the Deputy Head of the Communications and Signal Processing Group, within the Electrical and Electronic Engineering Department, Imperial College London, London, U.K. He is also the Chief Technology Officer (CTO) of Silicon Austria Labs (SAL) where he is responsible for all research areas of Austria’s top research center for electronic based systems. He received the MSc and Ph.D. degrees in Electrical Engineering from Universit Catholique de Louvain, Belgium, in 2000 and 2005, respectively, and the Doctor of Science (DSc) degree from Imperial College London, U.K. in 2022. From 2006 to 2011, he was with Samsung Electronics, Suwon, South Korea, where he actively contributed to 4G (3GPP LTE/LTE-A and IEEE 802.16m) and acted as the Rapporteur for the 3GPP Coordinated Multi-Point (CoMP) Study Item. Since 2011, he has been with Imperial College London, first as a Lecturer from 2011 to 2015, Senior Lecturer from 2015 to 2017, Reader from 2017 to 2020, and now as a Full Professor. From 2014 to 2016, he also was an Associate Professor with Korea University, South Korea, and from 2021 to 2022, he was a visiting Professor at Seoul National University, South Korea. He also held various long or short-term visiting research appointments at Stanford University, EURECOM, National University of Singapore, The University of Hong Kong, Princeton University, The University of Edinburgh, The University of New South Wales, and Tsinghua University. He received the prestigious Blondel Medal 2021 from France for exceptional work contributing to the progress of Science and Electrical and Electronic Industries, the 2021 Adolphe Wetrems Prize in mathematical and physical sciences from Royal Academy of Belgium, multiple awards from Samsung, IEEE best student paper award, and the EURASIP (European Association for Signal Processing) best paper award 2022. He is a Fellow of the IEEE and the IET, and an IEEE Communications Society Distinguished Lecturer 2021-2023
T18: Intelligent Network Synchronization in the 6G Era: Scalability, Efficiency, and Applications
Room 304, Kuala Lumpur Convention Center
Xianbin Wang and Pengyi Jia (Western University, Canada); Sumei Sun (Institute for Infocomm Research, Singapore)
Abstract: Synchronizing large-scale networked systems forms the backbone of holistic temporal collaboration among distributed devices, machines, and infrastructures, which is essential for achieving tight orchestration of vertical industries in the 6G era. However, the low efficiency and situation agnosticism of conventional network synchronization methods with routine "observing-and-calibrating" will impede the performance of vertical applications with dramatically increased system scale and intrinsic heterogeneity. In this tutorial, we will first provide an in-depth analysis of the challenges associated with conventional network synchronization schemes in meeting the stringent synchronization requirements of large-scale 6G-enabled vertical applications. The diverse synchronization requirements of different industry applications are investigated and compared to shed light on potential design directions. In meeting these new requirements, several promising synchronization techniques for achieving accurate, intelligent, low-overhead, and secure network synchronization are presented. More specifically, we'll first introduce digital twin model-based network synchronization schemes that can proactively enable low-overhead clock calibration by exploring the inherent characteristics of heterogeneous clocks. Second, we will present customized network synchronization design methods to achieve intelligent and tailored clock calibration for different devices by clustering their distinctive synchronization requirements and multi-dimensional attributes. Third, we will elaborate timestamp-free mechanisms to achieve low-overhead network synchronization. Furthermore, future research directions on network synchronization in terms of synchronization process design, intelligent adaptation, and integration with vertical applications will be presented to guide researchers and industry practitioners toward more intelligent and effective network synchronization in the 6G era.
Bios:
Xianbin Wang (Fellow, IEEE) is a Professor and Tier-1 Canada Research Chair at Western University, Canada. He received his Ph.D. degree in electrical and computer engineering from the National University of Singapore in 2001. Prior to joining Western, he was with Communications Research Centre Canada as a Research Scientist/Senior Research Scientist between July 2002 and Dec. 2007. From Jan. 2001 to July 2002, he was a system designer at STMicroelectronics. His current research interests include 5G/6G technologies, Internet-of-Things, communications security, machine learning and intelligent communications. Dr. Wang has over 500 highly cited journal and conference papers, in addition to 30 granted and pending patents and several standard contributions. Dr. Wang is a Fellow of Canadian Academy of Engineering, a Fellow of Engineering Institute of Canada, a Fellow of IEEE and an IEEE Distinguished Lecturer. He has received many prestigious awards and recognitions, including IEEE Canada R.A. Fessenden Award, Canada Research Chair, Engineering Research Excellence Award at Western University, Canadian Federal Government Public Service Award, Ontario Early Researcher Award and six IEEE Best Paper Awards. He currently serves/has served as an Editor-in-Chief, Associate Editor-inChief, Editor/Associate Editor for over 10 journals. He was involved in many IEEE conferences including GLOBECOM, ICC, VTC, PIMRC, WCNC, CCECE and CWIT, in different roles such as general chair, symposium chair, tutorial instructor, track chair, session chair, TPC co-chair and keynote speaker. He has been nominated as an IEEE Distinguished Lecturer several times during the last ten years. Dr. Wang was the Chair of IEEE ComSoc Signal Processing and Computing for Communications (SPCC) Technical Committee and is currently serving as the Central Area Chair of IEEE Canada.
Pengyi Jia (Member, IEEE) received his Ph.D. degree from the Department of Electrical and Computer Engineering, Western University, London, ON, Canada, in 2021. He is currently a Postdoctoral Associate at Western University. His research interests include intelligent network synchronization, digital twin, and machine learning, as well as their applications in vertical IoT systems, cellular networks, and advanced manufacturing. One focus of his recent research is to develop accurate and efficient digital twin paradigms by investigating the intrinsic temporal correlations behind the massive sampling data to support network optimization and application-oriented service provisioning. He has been involved in organizing IEEE CCECE 2021 and served as a TPC member for many conferences. He is serving as the Vice Chair of ComSoc Chapter in IEEE London Section.
Sumei Sun (Fellow, IEEE) is currently the Acting Executive Director and Distinguished Institute Fellow at the Institute for Infocomm Research (I2R), A*STAR, Singapore. She is also holding a joint appointment with the Singapore Institute of Technology, and an adjunct appointment with the National University of Singapore, both as a full professor. Her research interests include next-generation wireless communications, cognitive communications and networks, industrial internet of things, communications-computing-control integrative design, joint radar-communication systems, and signal intelligence. She is the Editor-in-Chief of IEEE Open Journal of Vehicular Technology, Chair of the IEEE Transactions on Machine Learning in Communications and Networking Steering Committee, and a Distinguished Speaker of the IEEE Vehicular Technology Society 2018-2024. She is also a Member-at-Large at the IEEE Communications Society and a member of the Board of Governors at the IEEE Vehicular Technology Society.
T19: Tackling Training Data Scarcity for AI in Mobile Networks: Challenges and Solutions
Room 305, Kuala Lumpur Convention Center
Ali Imran (University of Oklahoma, USA); Muhammad Ali Imran (University of Glasgow, United Kingdom (Great Britain))
Abstract:
Despite the continued hype surrounding AI in mobile networks, real progress towards AI-enabled zero-touch automation within the mobile network industry is hindered by a fundamental challenge: Training Data Scarcity (TDS). The TDS challenge is unique to mobile networks, as other domains where AI is shown to be highly successful, such as computer vision or social networks, have large, freely available training datasets. These datasets not only facilitate the development of domain-aware AI but also enable reproducible benchmarking. Consequently, AI is already delivering practical solutions in these TDS-free domains. The TDS challenge in mobile networks remains unaddressed by existing tutorials and literature. This tutorial will be the first to tackle this crucial topic. Its goal is to provide a case study-based analysis of the implications of TDS on the practical performance of AI-based solutions for mobile networks, particularly for system-level problems. The tutorial then explores promising approaches for addressing the TDS challenge. Some of the approaches discussed include mobile network native AI and few-shot learning design by leveraging domain knowledge; mobile network-friendly transfer learning design; novel methods for realistic synthetic data generation through domain-aware generative adversarial network (GAN) architecture design while avoiding mode collapse; and strategies to fuse sparse real data with system-level simulators and testbed data to overcome the TDS challenge. This tutorial is expected to inspire practical, adaptable, reproducible, and impactful research towards zero-touch automation through the design of mobile network native AI and datasets.
Bios:
Prof. Ali Imran is the founding director of the AI4Networks Research Centre (www.ai4networks.com) at the University of Oklahoma. AI4Networks was the first academic center dedicated exclusively to research on zerotouch deep network automation. The center also hosts TurboRAN (https://ai4networks.com/turboran/ ) - a first of its kind cellular testbed for enabling system level research on AI-based zero-touch automation in mobile networks. Dr. Imran's research on network automation has been supported by over $5M in nationally and internationally competitive research grants. He has published over 150 refereed journal and conference papers on this topic and has several granted and pending patents. His work includes some of the most influential publications in the area of mobile network automation.The impact of Dr. Imran's work on network automation has been recognized by several prestigious awards, such as the VPR Outstanding International Impact Award at the University of Oklahoma in 2018, the IEEE Green ICT YP International Award in 2017, and the Best Paper Award at IEEE CAMAD in 2013. In 2019, he was named the William H. Barkow Presidential Professor at the University of Oklahoma for his contributions to this field.Dr. Imran is frequently invited to serve as an advisor to key stakeholders in the cellular network ecosystem and as a speaker and panelist at international industry forums and academic conferences on this topic. He is an Associate Fellow of the Higher Education Academy (AFHEA) in the UK, President of the ComSoc Tulsa Chapter, a Senior Member of IEEE, a Member of the Advisory Board for the Special Technical Community on Big Data at the IEEE Computer Society, and a board member of ITERA. For a more detailed bio of Dr. Imran, please visit: www.ali-imran.com.
Prof. Muhammad Imran received his M.Sc. (Distinction) and Ph.D. degrees from Imperial College London, UK, in 2002 and 2007, respectively. He is currently a Chair Professor at the University of Glasgow and visiting Professor at 5GIC Surrey. He is the founding director of the Communications Sensing and Imaging Research labs and a regular invited speaker on several mobile network related talks, industrial panels and policy events for wireless communication technology. He has a global collaborative research network spanning both academia and key industrial players in the field of wireless communications. He has led a number of multimillion pounds international research projects encompassing the areas of Internet of Things (IoT), energy efficiency, fundamental performance limits, sensor networks and self-organizing cellular networks. He led the physical layer research for 5G innovation centre at Surrey (an outdoor cellular testbed developed at University of Surrey with a grant of above $50m). He has supervised 60+ successful Ph.D. graduates and published over 500 peer-reviewed research papers including more than 40 IEEE transactions. He is associate editor of IEEE Transactions on Communications, IEEE Access, IEEE Communications Letters and guest editor of several special issues in IEEE journals. He is a chair for several tracks in highly reputed international conferences and workshops including forthcoming IEEE ICC 2020 (co-chair for Next Generation Networking Symposium). He has been awarded IEEE Comsoc’s Fred Ellersick award 2014 and FEPS Learning and Teaching award 2014. He has also been shortlisted for Wharton-QS Stars Reimagine Education Awards 2014. He is a Fellow IEEE, Fellow of IET and a Senior Fellow of Higher Education Academy (SFHEA), UK.
T20: Digital Twins for 6G communications and networking
Room 401, Kuala Lumpur Convention Center
Hamed Ahmadi (University of York, United Kingdom (Great Britain)); Trung Q. Duong (Queen's University Belfast, United Kingdom (Great Britain)); Berk Canberk (Edinburgh Napier University, United Kingdom (Great Britain)); Vishal Sharma (Queen's University Belfast, United Kingdom (Great Britain))
Abstract:
6G has ambitious KPIs that are defined to satisfy the requirements of its driving applications such as connected robotics and autonomous systems, immersive experience of augmented reality (AR)/virtual reality (VR)/mixed reality (MR), and blockchain and trust technologies. 6G KPIs and driving applications enable a comprehensive digital representation of the physical world, along with the creation and the support for real-time interaction. In this environment, the cyber and cyber-physical worlds are connected, and digital twins (DTs) of various objects can be created. DT is a real-time evolving digital duplicate of a physical object or even a process that contains all its history. DT is enabled by massive real-time multi-source data collection and its analysis. Therefore, on a larger scale we can say that it is a crossing point of 6G and AI. While 6G is considered as an enabler of DT, we believe that DT can be a facilitator for integrating AI and 6G, towards the desired KPIs. The wide and universal potential applications of DT, ranging from aerospace to Industry 4.0, and its high communication requirements will make it the killer application of 6G.
Bios:
Dr. Hamed Ahmadi is a Senior Lecturer (Associate Professor) in the school of Physics, Engineering and Technology at University of York, UK. His current research interests include Digital twins of networks; design, analysis, and optimization of wireless communications network; applications of machine learning in wireless networks; airborne networks; Internet-of-Things and self-organizing networks. He is a member of the editorial board of IEEE Communications Standards magazine, IEEE Systems, IEEE Access, and Springer Wireless Networks. He is a senior member of IEEE, Fellow of UK Higher Education Academy, and Networks working group chair and a management committee member of COST Action CA20120 (INTERACT). He received his PhD Degree in Electrical and Computer Engineering from the National University of Singapore.
Prof. Trung Q. Duong is Chair Professor of Telecommunications at Queen’s University Belfast, U.K., and a Research Chair of Royal Academy of Engineering, UK. His current research interests include physical layer security, 5G-6G networks, digital twin. He is the recipient of the prestigious Royal Academy of Engineering Research Fellowship (2015-2020) and won the Newton Prize in 2017. He is a fellow of IEEE. He has recently been invited to be a keynote speaker in the topic of digital twin for 6G networks at premier conferences including 2022 16th IEEE-RIVF International Conference on Computing and Communication Technologies, 2022 IEEE VTS Asia Pacific Wireless Communications Symposium, 2022 IEEE 9th International Conference on Communications and Electronics (ICCE), 2022 IEEE 95th Vehicular Technology Conference (VTC) Workshop, and 2022 IEEE INFOCOM Workshop on Pervasive Network Intelligence for 6G Networks (PerAI-6G).
Dr. Berk Canberk is a Professor within the School of Computing, Engineering and The Built Environment at Edinburgh Napier University-UK, where he leads interdisciplinary research and initiatives in AI-enabled Digital Twins, IoT Communication, and Smart Wireless Networks. He is an IEEE Senior Member, and he acts as an active Associate Editor at several world-leading academic journals such as IEEE Transactions on Vehicular Technology (Scopus Q1 Quartile) since 2016, Elsevier Computer Networks Journal (Scopus Q1 Quartile) since 2013, Elsevier Communication Networks Journal (Scopus Q1 Quartile) since 2017, and IEEE Communications Letters (Scopus Q1 Quartile) between 2018-2021. He’s actively involved in several conferences as TPC chair and Organizing Committee Member. In his research group named Broadband Communication and Network Automation Research Group (BCRG), he leads the research activities in highly interdisciplinary fields, actively supervising 5 PhD and 2 MSc students. So far, he has supervised 16 MSc students, and 6 PhD students who are now all tenure-track professors. He has published 63 journal papers (43 in Q1 quartile, 7 in Q2 quartile, and 13 are Q3+Q4 quartiles), 58 conference papers, 2 books, 7 book chapters, 2 approved US patents and 9 patents waiting for approval. Berk has been a Post-Doctoral researcher at Georgia Institute of Technology USA between 2011-2013. He received his PhD in Computer Science from Istanbul Technical University (ITU) Turkey in 2011, his MSc in Telecommunications Engineering from the Chalmers University of Technology Sweden in 2005, and his BSc in Electrical Engineering from ITU in 2003. He’s been an Adjunct Professor within the Department of Electrical and Computer Engineering at Northeastern University USA since 2017, and Adjunct Faculty within the Department of Artificial Intelligence and Data Engineering at Istanbul Technical University (ITU) since 2022. He was an Associate Professor at Department of Computer Engineering at ITU between 2016-2021, and full Professor between 2021-2022. He has been involved with several industrial research activities with leading technology companies all over the world, including research scholarship program funding with Google Deepmind, Turkcell, Turkish Telekom, BTS Group Turkey and Uniper Energy Germany.
Dr Vishal Sharma is a Lecturer in the School of Electronics, Electrical Engineering and Computer Science at Queen's University Belfast. He has published over 120 research articles in prestigious journals and conferences and received four best paper awards, including one for his PhD work from his Alma mater. He has several projects funded by Innovate UK, PwC, VIAVI, UKRI-Horizon, DCMS, and DSTL in defence and security, distributed ledger technology, and digital twins. His digital twin platform for securing drones has been selected as an innovation zone exhibitor at the CyberUK event in 2023. He is a Fellow of the Higher Education Academy, a senior member of IEEE, and served as the associate technical editor for IEEE Communications Magazine.
