All tutorials will be accessible to attendees who have registered. The list is below.
Please note: This list may change depending on how many people sign up for these tutorials in advance.

All rooms are located in the Palais des congrès de Montréal

Details

SUNDAY JUNE 08 - MORNING SESSION (9:00 - 12:30)

TUT-01: Generative Foundation Models (GFMs) For NextG Communication Networks: Fundamentals, Key Techniques, and Future Directions

Location: 512 E

Speakers: Hao Zhou (University of Ottawa, Canada); Chengming Hu (McGill University, Canada); Xue Liu (McGill University, Canada)

Abstract: Generative artificial intelligence (GenAI) is a promising technique for next generation (nextG) communication networks, and generative foundation models (GFMs) especially large language models (LLMs) have attracted considerable interest from academia and industry. Motivated by the recent progress of foundation model techniques, this tutorial will present a comprehensive overview of GFM fundamentals, key techniques, and future directions. In particular, we will first introduce GFM fundamentals, including model architecture, pre-training, fine-tuning, inference and utilization, and evaluation. Then, we will discuss various GFM deployment strategies in communication networks, such as edge, cloud, and on-device deployment. After that, we present GFM-enabled key techniques and network applications in terms of generation, optimization, classification, and prediction problems. Firstly, the GFM-enabled generation applications include network domain knowledge, code, and configuration generation. Secondly, we will present a network optimization case study of iterative prompting, along with multiple GFM-inspired optimization techniques. Meanwhile, the GFM-based classification applications involve network security, text, image, and traffic classification problems. In addition, for GFM-aided prediction problems, we will introduce a self-refined prompting-based prediction technique and other TIME-series prediction models. Finally, we highlight the challenges and identify the future directions of GFM-enabled nextG communication networks.

Biographies:

Hao Zhou (University of Ottawa, Canada)

Hao Zhou is currently a Postdoctoral Researcher at the School of Computer Science, McGill University. He completed my PhD degree at University of Ottawa, Canada, from 2019 to 2023. His research focuses on the intersection between machine learning, optimization, and networked systems, especially for 5G/6G wireless networks and power systems. He is dedicated to developing novel machine learning algorithms to address various optimization problems in networked systems, including resource allocation, computational task offloading, energy management and trading, network security, etc. He has published more than 40 peer-reviewed papers, and received the 2023 IEEE ICC Best Paper Award, 2023 IEEE ComSoc CSIM TC Best Journal Paper Award, and also won the 2023 Faculty of Engineering’s Best Doctoral Thesis Award at University of Ottawa. His recent project on LLM4Telecom has been granted the Samsung GRO project, in which only 11 projects worldwide received this prestigious recognition.

Chengming Hu (McGill University, Canada)

Chengming Hu is currently a Ph.D. candidate in the School of Computer Science at McGill University. Prior to joining McGill, Chengming received his M.Sc. from Concordia Institute for Information Systems Engineering (CIISE) at Concordia University in 2019. His research interests lie in investigating computational intelligence techniques to manage and optimize the resource efficiency, cybersecurity, and resilience of industrial networked systems, with a particular focus on smart grids, cyber-physical systems, and communication systems. He is actively exploring various computational intelligence techniques, including ensemble learning, knowledge distillation, generative foundation models, and feature learning, among others. Moreover, Chengming has actively engaged with the industry as a research intern in Ericsson GAIA Canada and Samsung Research America. To date, Chengming has authored over 20 peer-reviewed conference and journal papers spanning a range of research topics, including International Conference on Learning Representations (ICLR), IEEE Transactions on Smart Grid, IEEE Communications Surveys and Tutorials, IEEE International Conference on Communications (ICC), and IEEE Transactions on Vehicular Technology, among others.

Xue Liu (McGill University, Canada)

Dr. Xue (Steve) Liu is a William Dawson Chair Professor at the School of Computer Science at McGill University. He is a Fellow of the Canadian Academy of Engineering (FCAE), IEEE Fellow (FIEEE), and ACM Distinguished Member. He has been the Vice President R&D, Chief Scientist, and Co-Director of the SAMSUNG AI Center Montreal from 2019 to 2024. He is the current Chair of the ACM Special Interest Group in Embedded Systems (SIGBED), and also a Professor (by courtesy appointment) of Mathematics and Statistics at McGill University. He is also a faculty and associate member of the Quebec AI Institute (Mila). Dr. Liu has published more than 400 peer-reviewed publications with more than 23,000 citations in major highly-reputable peer-reviewed International academic journals and conference proceedings, including NeurIPS, ICLR, AAAI, IJCAI, WWW, IEEE ICRA, IEEE/RSJ IROS, ACM SIGIR, ACM WSDM, ACM MobiCom, ACM KDD, ACM Multimedia, ACM UbiComp, ACM SoCC, IEEE INFOCOM, IEEE ICNP, etc, and various IEEE and ACM Transactions. His research received many best paper awards from IEEE and ACM. Dr. Liu has served on the organizing committees of over 40 major international conferences and workshops including ACM/IEEE CPSWeek, INFOCOM, RTSS, RTAS, SenSys, ICDCS, IWQoS, and received several outstanding service awards. He has also served as program committee members for over 100 international conferences and workshops.

TUT-02: The Interplay between Quantum Computing and Reinforcement Learning

Location: 512 F

Speakers: Mahdi Chehimi (American University of Beirut, Lebanon); Samuel Yen-Chi Chen (Wells Fargo, USA)

Abstract: Coming Soon

Biographies:

Mahdi Chehimi (American University of Beirut, Lebanon)

Mahdi Chehimi is a Ph.D. candidate in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. Mahdi received his B.S. in Electrical Engineering with honors from Kuwait University in 2018 and his M.E. in Electrical and Computer Engineering from the American University of Beirut in 2020 with a focus on communications, radio frequency, and physical layer security. His research interests include quantum communications, quantum networking, and quantum machine learning (QML) with applications to communication networks. Mahdi received the best paper award at the 2023 IEEE International Conference on Quantum Computing and Engineering (QCE) for his work on the scalability of quantum repeater networks. His seminal work on quantum federated learning (QFL) introduced its inaugural framework using quantum data, which pioneered one of the first open-source quantum federated datasets in literature. In 2022, Mahdi was a visiting scholar in the ACQuIRe Lab at the University of Massachusetts Amherst. In addition, Mahdi held a research stay in summer 2023 at Ingenii Inc. as a quantum scientist, where his work focused on practical QML applications in drug discovery and medical imaging. Mahdi was the lead organizer of the first Quantum Information Summit in Lebanon held at the American University of Beirut. He served as a technical committee member in multiple QML workshops at flagship IEEE conferences, and is a frequent reviewer at several IEEE journals. Mahdi is a Quantum Formalism fellow, by Zaiku Group in the United Kingdom, where he received multiple grants to support his research on distributed QML applications and QFL.

Samuel Yen-Chi Chen (Wells Fargo, USA)

Dr. Samuel Yen-Chi Chen received the Ph.D. and B.S. degree in physics from National Taiwan University, Taipei City, Taiwan. He is now a senior research scientist at Wells Fargo Bank. Prior to that, he was an assistant computational scientist in the Computational Science Initiative, Brookhaven National Laboratory. His research interests include building quantum machine learning algorithms as well as applying classical machine learning techniques to solve quantum computing problems. He won the First Prize In the Software Competition (Research Category) from Xanadu Quantum Technologies, in 2019.

TUT-03: Next Generation Multiple Access for 6G: Opportunities and Challenges

Location: 512 G

Speakers: Zhiguo Ding (University of Manchester, United Kingdom (Great Britain); Yuanwei Liu (The University of Hong Kong, Hong Kong)

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. 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 requirements of 6G, particularly for massive connectivity in Internet-of-things networks. Next, it presents the interplay between NGMA and emerging new techniques, e.g., pinching-antenna systems, integrated sensing and communications, THz networks, age of information, and simultaneously transmitting and reflecting surfaces. Furthermore, the tutorial discusses new applications of NGMA designs, e.g., semantic communications and mobile edge computing. Finally, it investigates the use of new tools, i.e., machine learning approaches, in NGMA networks, ushering in the era of machine learning-empowered NGMA for intelligent multiple access in 6G.

Biographies:

Zhiguo Ding (University of Manchester, United Kingdom (Great Britain)

Zhiguo Ding received his B.Eng in Electrical Engineering from the Beijing University of Posts and Telecommunications in 2000, and the Ph.D degree in Electrical Engineering from Imperial College London in 2005. He is currently a Professor in Communications at the University of Manchester, a Distinguished Adjunct Professor at Khalifa University, and an Academic Visitor at Princeton University. Previously, he had been working in Queen's University Belfast, Imperial College, Newcastle University and Lancaster University. Dr Ding' research interests are 6G networks, communications and signal processing. His h-index is over 100 and his work receives 60,000+ Google citations. He is serving as an Area Editor for the IEEE TWC, TCOM and OJ-COMS, an Editor for IEEE TVT, COMST, and OJ-SP, and was an Editor for IEEE TCOM, IEEE WCL, IEEE CL and WCMC. He received the best paper award of IET ICWMC-2009 and IEEE WCSP-2014, the EU Marie Curie Fellowship 2012-2014, the Top IEEE TVT Editor 2017, IEEE Heinrich Hertz Award 2018, IEEE Jack Neubauer Memorial Award 2018, IEEE Best Signal Processing Letter Award 2018, Alexander von Humboldt Foundation Friedrich Wilhelm Bessel Research Award 2020, IEEE SPCC Technical Recognition Award 2021, and IEEE VTS Best Magazine Paper Award 2023. He is a Web of Science Highly Cited Researcher in two disciplines (2019-2023), an IEEE ComSoc Distinguished Lecturer, and a Fellow of the IEEE.

Yuanwei Liu (The University of Hong Kong, Hong Kong)

Yuanwei Liu is a tenured full Professor in Department of Electrical and Electronic Engineering (EEE) at The University of Hong Kong (HKU) and a visiting professor at Queen Mary University of London (QMUL). Prior to that, he was a Senior Lecturer (Associate Professor) (2021-2024) and a Lecturer (Assistant Professor) (2017- 2021) at QMUL, London, U.K, and a Postdoctoral Research Fellow (2016-2017) at King's College London (KCL), London, U.K. He received the Ph.D. degree from QMUL in 2016. His research interests include non-orthogonal multiple access, reconfigurable intelligent surface, near field communications, integrated sensing and communications, and machine learning. Yuanwei Liu is a Fellow of the IEEE, a Fellow of AAIA, a Web of Science Highly Cited Researcher, an IEEE Communication Society Distinguished Lecturer, an IEEE Vehicular Technology Society Distinguished Lecturer, the rapporteur of ETSI Industry Specification Group on Reconfigurable Intelligent Surfaces on work item of “Multi-functional Reconfigurable Intelligent Surfaces (RIS): Modelling, Optimisation, and Operation”, and the UK representative for the URSI Commission C on “Radio communication Systems and Signal Processing”. He was listed as one of 35 Innovators Under 35 China in 2022 by MIT Technology Review. He received IEEE ComSoc Outstanding Young Researcher Award for EMEA in 2020. He received the 2020 IEEE Signal Processing and Computing for Communications (SPCC) Technical Committee Early Achievement Award, IEEE Communication Theory Technical Committee (CTTC) 2021 Early Achievement Award. He received IEEE ComSoc Outstanding Nominee for Best Young Professionals Award in 2021. He is the co-recipient of the 2024 IEEE Communications Society Heinrich Hertz Award, the Best Student Paper Award in IEEE VTC2022-Fall, the Best Paper Award in ISWCS 2022, the 2022 IEEE SPCC-TC Best Paper Award, the 2023 IEEE ICCT Best Paper Award, and the 2023 IEEE ISAP Best Emerging Technologies Paper Award. He serves as the Co-Editor-in-Chief of IEEE ComSoc TC Newsletter, an Area Editor of IEEE Transactions on Communications and IEEE Communications Letters, an Editor of IEEE Communications Surveys & Tutorials, IEEE Transactions on Wireless Communications, IEEE Transactions on Vehicular Technology, IEEE Transactions on Network Science and Engineering, and IEEE Transactions on Cognitive Communications and Networking. He serves as the (leading) Guest Editor for Proceedings of the IEEE on Next Generation Multiple Access, IEEE JSAC on Next Generation Multiple Access, IEEE JSTSP on Intelligent Signal Processing and Learning for Next Generation Multiple Access, and IEEE Network on Next Generation Multiple Access for 6G. He serves as the Publicity Co-Chair for IEEE VTC 2019-Fall, the Panel Co-Chair for IEEE WCNC 2024, Symposium Co-Chair for several flagship conferences such as IEEE GLOBECOM, ICC and VTC. He serves the academic Chair for the Next Generation Multiple Access Emerging Technology Initiative, vice chair of SPCC and Technical Committee on Cognitive Networks (TCCN).

TUT-04: Reconfigurable Holographic Surfaces Enabled Communications and Sensing for 6G

Location: 512 H

Speakers: Lingyang Song (Peking University, China); Zhu Han (University of Houston, USA); Boya Di (Peking University, China); Hongliang Zhang (Peking University, China)

Abstract: Coming soon.

Biographies:

Lingyang Song (Peking University, China)

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 co-author 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.

Zhu Han (University of Houston, USA)

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.

Boya Di (Peking University, China)

Boya Di is an assistant professor at Peking University. She obtained her Ph.D. degree and B.S. degree from the Department of Electronics, Peking University, China, in 2019 and 2024, respectively. She was a postdoc researcher at Imperial College London during 2019-2021. Her current research interests include holographic surfaces, near-far field communications and sensing. She is the recipient of 2022 IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award, 2023 IEEE ComSoc TCCN Publication Award, and 2024 IEEE/CIC ICCC Best Demo Award. She serves as an associate editor for IEEE Transactions on Vehicular Technology, IEEE Communications Surveys & Tutorials, and IEEE Internet of Things Journal.

Hongliang Zhang (Peking University, China)

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 Endowed Boya Young Fellow Assistant Professor with School of Electronics. His current research interests include intelligent surfaces, aerial access networks, and Internet of Things. He received the best doctoral thesis award from Chinese Institute of Electronics in 2019. He is also the recipient of 2024 IEEE GLOBECOM Best Paper Award, 2024 IEEE/CIC ICCC Best Demo Award, 2023 IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award, 2021 IEEE Comsoc Heinrich Hertz Award for Best Communications Letters, and 2021 IEEE ComSoc Asia-Pacific 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 Cognitive Communications and Networking, IEEE Internet of Things Journal, IEEE Transactions on Vehicular Technology, IEEE Communications Letters, and IET Communications. He is an exemplary editor for IEEE Communications Letters in 2023.

TUT-05: Distributed Vision Analytics for Immersive 6G Time-Sensitive Systems

Location: 514 A

Speakers: Rodolfo W. L. Coutinho (Concordia University, Canada); Azzedine Boukerche (University of Ottawa, Canada)

Abstract: Many time-sensitive 6G applications will use vision analytics to extract the environment's contextual information. The challenge is that the video analytics performed by complex DNN models is often not possible on mobile devices due to their limited computation, storage, and energy supply. The common approach of deploying large and complex models in the cloud infrastructure might be unfeasible for 6G time-critical systems due to the high latency in the processing and communication tasks. This fact demands a new computing paradigm for providing vision analytic services more efficiently for 6G time-sensitive systems. A promising direction is to provide vision analytic services in a distributed manner along the edge computing stratum and in the network computing fabric to reduce latency. This tutorial will cover the KPIs of time-critical 6G systems, the pipeline of mobile vision analytics, the deployment of video analytic services across the edge computing stratum and in the network compute fabric, the daunting challenges for the management and allocation of distributed resources to mobile vision analytic services, the current state-of-the-art in the field and future research directions.

Biographies:

Rodolfo W. L. Coutinho (Concordia University, Canada)

Rodolfo W. L. Coutinho is an Associate Professor at the Department of Electrical and Computer Engineering at Concordia University, Canada. He received the MSWiM Rising Star Award (2019) and the Pierre Laberge Prize at the University of Ottawa (2018). He served as TPC Co-Chair in multiple flagship IEEE and ACM conferences including IEEE GLOBECOM 2024 (IoT and Sensor Networks Symposium), IEEE PIMRC 2023 (Networking and MAC Track), ACM MobiWac 2022/2023, and IEEE ICC 2020 (Ad Hoc and Sensor Networks Symposium). He serves as Editor for the Ad Hoc Networks Journal and served as Guest Editor for special issues with the Computer Communications Journal, Journal of Parallel and Distributed Computing, and Ad Hoc Networks Journal and as an Editorial Board Member in the ACM International Conference Proceedings Series (ICPS). His research interests include pervasive computing, 6G networks, mobile extended reality, IoT, and edge computing.

Azzedine Boukerche (University of Ottawa, Canada)

Azzedine Boukerche [FIEEE, FEiC, FCAE, FAAAS, FAAIA] is a Distinguished University Professor and holds a Senior Canada Research Chair Tier-1 position with the University of Ottawa. He is the founding director of the PARADISE Research Laboratory and the DIVA Strategic Research Center, and NSERC-CREATE TRANSIT at the University of Ottawa. He has received the C. Gotlieb Computer Medal Award, Ontario Distinguished Researcher Award, Premier of Ontario Research Excellence Award, G. S. Glinski Award for Excellence in Research, IEEE Computer Society Golden Core Award, IEEE CS-Meritorious Award, IEEE TCPP Leadership Award, IEEE Com Soc ComSoft and IEEE ComSoc ASHN Leadership and Contribution Award, and the University of Ottawa Award for Excellence in Research. He serves as an Editor-in-Chief for ACM ICPS and Associate Editor for several IEEE transactions and ACM journals and is also a Steering Committee Chair for several IEEE and ACM international conferences. His current research interests include sustainable sensor networks, autonomous and connected vehicles, wireless networking and mobile computing, wireless multimedia, QoS service provisioning, performance evaluation and modeling of large-scale distributed and mobile systems, and large scale distributed and parallel discrete event simulation. He has published extensively in these areas and received several best research paper awards for his work. He is a Fellow of the Engineering Institute of Canada, the Canadian Academy of Engineering, and the American Association for the Advancement of Science.

TUT-06: Theoretical Foundations for Ubiquitous Connectivity, Intelligence, and Security in the 6G Era and Beyond

Location: 514 B

Speakers: Hesham ElSawy (School of Computing, Queen's University, Canada); Mustafa A Kishk (National University of Ireland, Maynooth, Ireland); Tareq Y. Al-Naffouri (King Abdullah University of Science and Technology, USA); Mohamed-Slim Alouini (King Abdullah University of Science and Technology (KAUST), Saudi Arabia)

Abstract: 6G is poised to revolutionize wireless connectivity by providing omnipresent communication, computational, sensing, and machine learning services to a vast array of users, devices, and smart objects. With built-in cognitive capacities, 6G networks will support applications in sectors like smart cities, healthcare, public safety, and autonomous driving, all characterized by diverse spatial, temporal, and contextual requirements. Many 6G devices will depend on network edge or cloud servers for machine learning and complex computational tasks, raising security concerns, especially as most will be deployed by unaware consumers. Federated learning at the network edge will enhance distributed and secure AI applications. However, this leap to 6G introduces challenges such as increased energy consumption, potential security risks, and a widening digital divide. Novel techniques must address communications, computing, sensing, machine learning, and security issues. The tutorial discusses mathematical models and solutions using stochastic geometry, queueing theory, and percolation theory to design large-scale 6G networks. Key topics include joint communications and sensing, drone-enabled networks, intelligent surfaces, edge computing, self-sustaining networks, and malware mitigation. The session concludes by highlighting open research areas for future exploration in 6G.

Biographies:

Hesham ElSawy (School of Computing, Queen's University, Canada)

Hesham ElSawy (Senior Member, IEEE) is an Assistant Professor with the School of Computing, Queen's University, Kingston, ON, Canada. Prior to that, he was an assistant professor at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia, a Post-Doctoral Fellow at the King Abdullah University of Science and Technology (KAUST), Saudi Arabia, a Research Assistant at TRTech, Winnipeg, MB, Canada, and a Telecommunication Engineer at the National Telecommunication Institute, Egypt. He received the Ph.D. degree in electrical engineering from the University of Manitoba, Canada, in 2014. He is a recipient of the IEEE ComSoc Outstanding Young Researcher Award for Europe, Middle East \& Africa Region in 2018. He also received several best paper awards including the IEEE COMSOC Best Tutorial Paper Award in 2020 and IEEE COMSOC Best Survey Paper Award 2017. He is an Editor of the IEEE Transactions on Wireless Communications, the IEEE Communications Surveys \& Tutorials, and the IEEE Communications Letters. He is recognized as an exemplary Editor for the IEEE Transactions on Network Sciences and Engineering and IEEE Communications Letters as well as an exemplary reviewer by the IEEE Transactions on Communications, the IEEE Transactions on Wireless Communications, and the IEEE Wireless Communications Letters. He conducts research in the broad area of wireless communications and networking with a special focus on 5G/6G networks, Internet of Things, joint communications and sensing, edge computing, and non-terrestrial networks.

Mustafa A Kishk (National University of Ireland, Maynooth, Ireland)

Mustafa Kishk (Member, IEEE) received the B.Sc. and M.Sc. degrees from Cairo University, Giza, Egypt, in 2013 and 2015, respectively, and the Ph.D. degree in electrical engineering from Virginia Tech, Blacksburg, VA, USA, in 2018. He is an Assistant Professor with the Electronic Engineering Department, Maynooth University, Maynooth, Ireland. Before that, he was a Postdoctoral Research Fellow with the Communication Theory Laboratory, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia. His current research interests include stochastic geometry, UAV-enabled communication systems, and satellite-enabled communications. Dr. Kishk is a recipient of the IEEE ComSoc Outstanding Young Researcher Award for Europe, Middle East, and Africa Region, in 2022. He currently serves as an Associate Editor with IEEE WIRELESS COMMUNICATIONS LETTERS. He was recognized as an Exemplary Reviewer by the IEEE COMMUNICATIONS LETTERS in 2020.

Tareq Y. Al-Naffouri (King Abdullah University of Science and Technology, USA)

Tareq Al-Nafouri (Fellow, IEEE) received the B.S. degree (Hons.) in mathematics and electrical engineering from the King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia, in 1996, the M.S. degree in electrical engineering from Georgia Institute of Technology, Atlanta, GA, USA, in 1998, and the Ph.D. degree in electrical engineering from Stanford University, Stanford, CA, USA, in 2004. He was a Visiting Scholar with California Institute of Technology, Pasadena, CA, USA, in 2005 and summer 2006. He was a Fulbright Scholar with the University of Southern California, Los Angeles, CA, USA, in 2008. He is currently a Professor with the Electrical and Computer Engineering Program, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia. He has over 370 publications in journals and conference proceedings and 24 issued/pending patents. His research interests include sparse, adaptive, and statistical inference/learning and their applications to wireless communications, localization, smart cities, and smart health. Dr. Al-Naffouri was a recipient of the IEEE Education Society Chapter Achievement Award in 2008, the Al-Marai Award for Innovative Research in Communication in 2009, and Abdul Hameed Shoman Arab Researchers Award in for innovative research in IoT in 2022. He was an Associate Editor of IEEE TRANSACTIONS ON SIGNAL PROCESSING from 2013 to 2018.

Mohamed-Slim Alouini (King Abdullah University of Science and Technology (KAUST), Saudi Arabia)

Mohamed-Slim Alouini (Fellow, IEEE) was born in Tunis, Tunisia. He received the Ph.D. degree in electrical engineering from California Institute of Technology, Pasadena, CA, USA, in 1998. He served as a Faculty Member with the University of Minnesota, Minneapolis, MN, USA, then in the Texas A& M University at Qatar, Doha, Qatar, before joining King Abdullah University of Science and Technology, Thuwal, Saudi Arabia, where he is currently a Distinguished Professor of Electrical and Computer Engineering. He is currently particularly interested in addressing the technical challenges associated with the uneven distribution, access to, and use of information and communication technologies in far-flung, rural, low-density populations, low-income, and/or hard-to-reach areas. Prof. Alouini is a Fellow of Optica (formerly OSA).

TUT-07: Building Foundation Models and Generalizable AI in 6G: From Theory to Practice

Location: 514 C

Speakers: Hatem Abou-Zeid (University of Calgary, Canada); Akram Bin Sediq (Ericsson Canada, Canada); Ashkan Eshaghbeigi (Qoherent inc, Canada); Ahmad M. Nagib (Queen's University, Canada)

Abstract: Artificial intelligence capabilities are envisioned to transform the design and operation of 6G networks. While research efforts have demonstrated the potential of AI for wireless, the lack of generalization and the need for tailored AI models per wireless function/task have challenged their practical adoption in real-world networks. In this tutorial we will discuss these challenges with real-world examples. We will then discuss the emerging paradigm of foundational models and strategies toward achieving such models in the wireless context. The tutorial will provide concrete examples of building multi-task foundational models using pre-training and self-supervised approaches for wireless signals. We will review literature and present a suite of methods to effectively represent wireless data into embeddings that achieve generalizability and robustness - key requirements for the development of foundational AI models. The techniques presented will provide a guide to researchers and practitioners to design generalizable multi-task AI methods that are suited for practical deployment. Practical interactive demos will be provided including a case study on "multi-task spectrogram sensing" using real-world data from an SDR testbed. This will be followed with an interactive session where the audience are guided to implement and test their own AI and foundational model codes. Finally, the tutorial will conclude with a discussion on exciting future research directions toward foundational AI models for 6G networks.

Biographies:

Hatem Abou-Zeid (University of Calgary, Canada)

Dr. Hatem Abou-Zeid received the Ph.D. degree from Queen’s University in 2014. He is currently an Assistant Professor with the University of Calgary and the director of the WAVES research group. Prior to that, he was at Ericsson leading 5G research for intelligent radio access networks and low-latency communications. Several wireless access and traffic engineering techniques that he co-invented and co-developed are deployed in 5G mobile networks worldwide. His research expertise is in generalizable and trustworthy AI for wireless networks, extended reality networking, and resource management. His work resulted in 20 patent filings and over 80 journals and conference publications in several IEEE flagship venues. He is an avid supporter of industry-university partnerships, and he served on the Ericsson Government Industry Relations and Talent Development Committees, where he directed numerous academic research partnerships. He served as the Co-Chair for the IEEE ICC Workshop on Wireless Network Innovations for Mobile Edge Learning and the Corporate Co- Chair for the IEEE LCN Conference 2022. He delivered numerous invited talks on trustworthy and generalizable AI for future communication networks and received several accolades for his academic contributions, including a Best Paper Award at IEEE ICC 2022, the Research Excellence Awards at the University of Calgary (2023, 2024), AI/ML ASTech Award Finalist, Outstanding Academic Achievement Award, and the Software Engineering Professor of the Year Award at the University of Calgary (2023).

Akram Bin Sediq (Ericsson Canada, Canada)

Dr. Akram Bin Sediq is a Principal AI/ML Developer at Ericsson Canada, where he leads the AI/ML technical development in physical-layer and radio-resource-management domains, drives early-phase system designs of 5G and beyond 5G wireless systems, generates patents, and manages collaborations with seven Canadian universities. His work has resulted in 40+ granted and filed patents, as well as 50+ peer-reviewed publications in the areas of Artificial Intelligence (AI)/Machine Learning (ML), beam management, dual connectivity, link adaptation, scheduling, reference signals and control channel design, energy-saving, and interference coordination, among others. Dr. Bin Sediq is a recipient of the President's Cup for graduating with the highest GPA at the Bachelor’s level at AUS in 2006, the Ontario Graduate Scholarship for international students for three years in a row during 2007–2010, two Senate Medals for outstanding academic achievement from Carleton University at the Master's and Ph.D. levels in 2008 and 2013, respectively, the EDC Teaching Assistant Outstanding Award at Carleton University in 2013, NSERC Industrial R&D Fellowship (IRDF) from 2013 to 2015, Ericsson's Key Contributor Award for three years in a row (2015-2017), AUS Alumni Wall of Fame recognition in 2015, and a Best Paper Award at IEEE ICC 2022.

Ashkan Eshaghbeigi (Qoherent inc, Canada)

Ashkan Eshaghbeigi is the founder and CEO of Qoherent and works with scientists and engineers to build the next generation of wireless technologies with machine learning. Ashkan's career focus has been in the business development of test and measurement solutions, including RF instrumentation and software-defined radios. Ashkan has a Bachelor’s degree in Engineering Physics & Management from McMaster University in Hamilton, Ontario, Canada, and a Master of Business Administration from the Schulich School of Business at York University, in Toronto, Ontario, Canada.

Ahmad M. Nagib (Queen's University, Canada)

Ahmad Nagib received his Ph.D. from the School of Computing at Queen’s University in 2024. He also holds B.Sc. and M.Sc. degrees from the Faculty of Computers and Artificial Intelligence at Cairo University. Currently, he is a Postdoctoral Fellow at the Queen’s Telecommunications Research Lab (TRL), where he leads research efforts on AI for Next-Generation Wireless Networks (NGWNs). His work focuses on the practical challenges of deploying machine learning algorithms, particularly reinforcement learning (RL) and generative artificial intelligence (GenAI), in NGWNs. During his Ph.D. studies, Ahmad participated in an industry-academia collaboration with Ericsson in Canada, where he also had previously begun exploring trustworthy RL as part of a Machine Learning Ph.D. Co-op. His research findings have been published in several flagship IEEE venues, including the Journal on Selected Areas in Communications (JSAC), Transactions on Network and Service Management (TNSM), Network, Global Communications Conference (GLOBECOM), International Conference on Communications (ICC), and Local Computer Networks (LCN). He has also served as a reviewer and Technical Program Committee (TPC) member for most of these and other prominent venues, such as IEEE Transactions on Mobile Computing, Communications Letters, Internet Computing, and Networking Letters. Ahmad’s achievements have earned him multiple accolades, including the Queen’s Graduate Award and International Tuition Award, as well as the IEEE Communication Society (ComSoc) student grant. He also received an honourable mention for the Queen’s School of Computing Ph.D. Research Achievement Award and has been recognized 13 times at Ericsson for his creativity, collaboration, and leadership.

SUNDAY JUNE 08 - AFTERNOON SESSION (13:30 - 17:30)

TUT-08: Generalizability and Interpretability of Deep Learning Models for Next-Generation (xG) Wireless Communications: A Tutorial

Location: 512 E

Speaker: Ekram Hossain (University of Manitoba, Canada)

Abstract: This tutorial will provide a friendly introduction to the different principles and methods for domain generalization (DG) and incorporating interpretability in the deep learning (DL) models with applications to next-generation (xG) wireless communication systems. After motivating the potential applications of machine learning (ML) for the evolving future cellular networks (e.g., beyond 5G [B5G]/6G cellular networks), it will introduce the basics of DL models (e.g., supervised and unsupervised DL, and deep reinforcement learning) and the related mathematical preliminaries. Then the concepts of domain shift/task mismatch and DG will be introduced. Different concepts related to DG and a taxonomy of the different DG methods including the different learning paradigms for DG will then be presented. Several case studies on the applications of DG methods for wireless communications will be discussed. To this end, several methods related to improving the interpretability of the DL models will be presented. In particular, several concepts and methods for science-informed design and evaluation of DL architectures and models will be elaborated. Finally, the current trends, open research challenges and future research directions on domain generalization and interpretability of DL models and techniques for xG wireless communication networks will be discussed.

Biographies:

Ekram Hossain (University of Manitoba, Canada)

Ekram Hossain (F'15) is a Professor in the Department of Electrical and Computer Engineering at University of Manitoba, Canada. His current research interests include design, analysis, and optimization of next-generation (xG) wireless communication networks. He has authored/edited several books in these areas (http://home.cc.umanitoba.ca/~hossaina). To date, his research works have received more than 47,000 citations (in Google Scholar, with h-index = 112). He has presented many invited talks as well as tutorials in IEEE conferences including IEEE Globecom, ICC, WCNC, and VTC. He was a Distinguished Lecturer of the IEEE Communications Society for two consecutive terms (2012-2015) and also a Distinguished Lecturer of the IEEE Vehicular Technology Society. He was listed as a Clarivate Analytics Highly Cited Researcher in Computer Science for 8 consecutive years from 2017 to 2024. He served as the Editor-in-Chief of IEEE Press (2018-2021) and also IEEE Communications Surveys and Tutorials (2012-2016).

TUT-09: Advancing Optical Communication: Visible Light Communication and Multi-Layer Airborne Backhaul Networks

Location: 512 F

Speakers: Maysa Yaseen (Lakehead University, Canada); Mohammed Elamassie (Özyeğin Üniversitesi, Türkiye); Salama Said Ikki (Lakehead University, Canada)

Abstract: Optical wireless communication (OWC) plays an important role in modern wireless networks, providing high-speed data transmission while overcoming the limitations of traditional radio frequency (RF) systems. OWC encompasses two significant technologies: Visible light communication (VLC) and free-space optical (FSO) communication. VLC operates in the visible light spectrum and is commonly used for LED-based indoor applications, although it is also expanding into outdoor and vehicular environments. In contrast, FSO relies on point-to-point laser communication, operating in the infrared spectrum. FSO is widely utilized in outdoor applications such as space and airborne communication, inter-satellite links, satellite-to-ground links, and airborne-to-ground connections. In the first part of this tutorial, we focus on VLC systems. Despite their advantages, VLC performance is affected by hardware imperfections such as signal-dependent shot noise (SDSN) and relative intensity noise (RIN), which complicate accurate channel estimation. Addressing these challenges is crucial to unlocking the full potential of VLC in future communication networks. Accordingly, we explore channel estimation under realistic conditions that account for SDSN and RIN, employing various estimation techniques. To evaluate their accuracy, we derive the Cramér-Rao lower bound (CRLB) as a benchmark and compare it with the proposed estimators. Our analysis considers both deterministic and random channel gains, and we evaluate the mean square error (MSE) of the studied estimators against the relevant benchmarks. Heading into the second part of this tutorial, we explore FSO communication and its outdoor applications, considering emerging technologies and the 6G and beyond goals of global coverage, i.e., addressing unconnected populations. The deployment of non-terrestrial networks (NTNs) such as satellites (GEO, MEO, LEO), high-altitude platform stations (HAPSs), and UAVs will provide global connectivity. This part of the tutorial focuses on designing a multi-layer airborne backhaul network with HAPSs and UAVs for FSO backhaul connections. The design process involves selecting the appropriate number of airborne nodes, trajectories, UAVs, and laser sources based on the coverage area. Additionally, we assess the bit error rate (BER) performance for dual-hop and triple-hop systems, including power allocation strategies to optimize BER across all hops. Furthermore, we discuss optimizing UAV altitude to minimize BER.

Biographies:

Maysa Yaseen (Lakehead University, Canada)

Maysa Yaseen currently serves as an Assistant Professor at Lakehead University, Barrie, ON, Canada. She received her Ph.D. in Electrical and Computer Engineering from Lakehead University, Thunder Bay, ON, Canada, in 2024. Her research interests include visible light communications, channel estimation, wireless sensor networks, machine learning in communications, and 6G and beyond wireless communication systems. Dr. Yaseen was the recipient of the DAAD Scholarship in 2007. Also, she received the Faculty Research Scholarship and the Faculty of Engineering Award from Lakehead University in 2021.

Mohammed Elamassie (Özyeğin Üniversitesi, Türkiye)

Mohammed Elamassie earned his Ph.D. in electrical and electronics engineering from Ozyegin University, Istanbul, Turkey, in 2020. He currently serves as an Assistant Professor at the same institution. He serves as an Executive Co-Director of both the Center of Excellence in Optical Wireless Communication Technologies (OKATEM) and the Communication Theory and Technologies (CT&T) research group at Ozyegin University.

Actively engaged in the academic community, Dr. Elamassie holds senior memberships in both IEEE and Optica and serves as an Optica Travelling Lecturer. He has several editorial positions, including serving as an Editor for the IEEE TRANSACTIONS ON COMMUNICATIONS since April 2024, an Associate Editor at Frontiers in Marine Science since May 2023, and as a Review Editor on the Editorial Boards of Frontiers in Communications and Networks' specialty sections 'Non-Conventional Communications and Networks' and 'Wireless Communications.' Additionally, he has served as a Guest Editor for a Special Issue at MDPI Photonics. Lastly, he recently joined the journal "Comm &Optics Connect" editorial board as the regional editor for the Middle East.

Dr. Elamassie's research interest lies in the broad area of wireless communications. Specific topics include HAPS/UAV-based optical wireless communication, atmospheric attenuation models for visible and infrared wavelengths, free space optical communication, optical turbulence, visible light communications (indoor, outdoor, and underwater), performance analysis over fading channels and time-varying channels, channel estimation and equalization, and channel modeling. He has authored over 70 publications in reputable journals and conferences, with 1300+ Google Scholar Citations and an H-index of 20.

Dr. Elamassie's major distinctions include the Best Paper Award at the IEEE INTERNATIONAL BLACK SEA CONFERENCE ON COMMUNICATIONS AND NETWORKING 2019. He is also the recipient of the 2020 IEEE Turkey Doctoral Dissertation Award.

Salama Said Ikki (Lakehead University, Canada)

Salama Ikki (Senior Member, IEEE) received his Ph.D. degree in Electrical Engineering from Memorial University, St. Johns, NL, Canada, in 2009. From February 2009 to February 2010, he was a Postdoctoral Researcher at the University of Waterloo, ON, Canada. From February 2010 to December 2012, he was a Research Assistant with the INRS at the University of Quebec, Montreal, QC, Canada. He is currently a Professor of Wireless Communications at Lakehead University, Thunder Bay, ON, Canada. He is the author of more than 100 journal and conference papers and has more than 7000 citations and an H-index of 38. His research group has made substantial contributions to 4G and 5G wireless technologies. His group’s current research interests include massive MIMO, cell-free massive MIMO, visible light communications, and wireless sensor networks. He was a recipient of several awards for research, teaching, and services. Dr. Ikki served on the Editorial Board for IEEE Communications Letters and the Institution of Engineering and Technology Communications. Furthermore, he also served as a Technical Program Committee member for various conferences, including the IEEE International Conference on Communications, the IEEE Global Communications Conference, the IEEE Wireless Communications and Networking Conference, the IEEE Spring/Fall Vehicular Technology Conference, and the IEEE International Symposium on Personal, Indoor, and Mobile Communications. Dr. Ikki received the Best Paper Award for what he published in the EURASIP Journal on Advanced Signal Processing. He also received IEEE Communications Letters, IEEE Wireless Communications Letters, IEEE Transactions on Vehicular Technology, and IEEE Transactions on Communications exemplary reviewer certificates for 2012, 2013, and 2014, respectively.

TUT-10: Multi-carrier Waveforms and Channel State Information for 6G

Location: 512 G

Speakers: Ana Garcia Armada (Universidad Carlos III de Madrid, Spain); Kun Chen-Hu (Aalborg University, Denmark)

Abstract: The waveform used to transmit information over the air is one of the key elements in the radio access network (RAN). It constrains the RAN architecture, the scheduling of resources and users, and the key performance indicators (KPIs) that are attainable. Since it is now the time to define the RAN for the Sixth Generation (6G) of mobile communications, it is the right time to discuss waveforms. This tutorial will provide a detailed description of different multi-carrier waveforms (both classical and new ones) and their suitability for several of the new scenarios and requirements envisaged for the 6G. They are compared according to how they can help to achieve different KPIs, such as complexity, peak-to-average-power ratio (PAPR), resistance to different types of channel impairments, self-interference and out-of-band emissions, among others. Additionally, since channel state information (CSI) acquisition is a must to perform coherent detection, also impacting multi-user scheduling and spatial multiplexing, the ways to obtain it for each waveform are also examined. Its suitability and the required overhead are examined for the specific scenarios/applications. Given that the number of resources devoted to the transmission of reference signals to track the variations of the channel may produce a significant overhead, we show that some waveforms may be considered as promising under idealistic CSI conditions and finally not be feasible under realistic assumptions in the 6G scenarios. Finally, non-coherent demodulation is discussed and a feasible scheme when combined with multi-carrier waveforms is presented as an alternative way to the coherent approaches, fully avoiding the transmission of reference signals in those scenarios where it is problematic. This tutorial provides a full assessment of the different multi-carrier waveforms and their implications in the RAN design. It will provide useful information for those that are in the position to influence or define the waveform for the next 6G, as well as to those that will design the RAN components on top of it.

Biographies:

Ana Garcia Armada (Universidad Carlos III de Madrid, Spain)

Prof. Dr. Ana García-Armada is a Professor and head of the Communications Research Group at University Carlos III of Madrid (UC3M), Spain. She is an IEEE Fellow and Fellow of the AAIA. She has been a visiting scholar at Stanford University, Bell Labs and University of Southampton. She has participated in more than 70 national and international research projects and contracts with the industry, all of them related to wireless communications. She is the co-author of eight book chapters on wireless communications and signal processing. She has published more than 250 papers in international journals and conference proceedings and she holds six granted patents. She is a member of the expert group of NetworldEurope European Technology Platform and has been the Vice-Chair of the advisory committee 5JAC of the ESA as expert appointed by Spain on 5G. She has served on several editorial boards: IEEE Commun. Letters, IEEE Trans. Communications, IEEE Open Journal of the Communications Society (now associate editor-in-chief since 2024). She has served on the TPC of more than 50 conferences and she has been a member of the organizing committee of IEEE WCNC 2024, IEEE MeditCom 2024 (General Chair), IEEE Globecom 2022, IEEE Globecom 2021 (General Chair), IEEE Globecom 2019, IEEE Vehicular Technology Conference (VTC) Fall 2018, Spring 2018 and 2019, among others. She has been a Member at Large of the Board of Governors, Director of Online Content and member of several management committees in the IEEE Communications Society, where she is now the VP of Member and Global Activities. She has received the Young Researchers Excellence Award from UC3M. She was awarded the third place Bell Labs Prize 2014 for shaping the future of information and communications technology. She received the Outstanding service award from the IEEE ComSoc Signal Processing and Communications Electronics technical committee in 2019 and the Outstanding service award from the IEEE ComSoc Women in Communications Engineering Standing Committee in 2020. She received the IEEE ComSoc/KICS Exemplary Global Service Award in 2022.

Kun Chen-Hu (Aalborg University, Denmark)

Kun Chen-Hu received his Ph.D. degree in Multimedia and Communications in 2019 from Universidad Carlos III de Madrid (Spain). He has worked as a post-doctoral researcher in the same institution for 3 years. Currently, he is a researcher at Aalborg University (Denmark). He was awarded by UC3M in 2019 recognizing his outstanding professional career after graduation. He visited Eurecom (France), Vodafone Chair TU Dresden (Germany) and other research institutions as a guest researcher. He also participated in different research projects in collaboration with several top companies in the area of mobile communications. He served as the Web Chair for Globecom 2021 and Meditcom 2024, Madrid (Spain), online content editor for IEEE ComSoc and organizing talks in SPPC. He was awarded an Exemplary Reviewer by IEEE Trans. on Communications in 2019 and 2020, and IEEE Communications Letters in 2019. His research interests are related to signal processing techniques for both communications and localization, such as waveform design, non-linear reconfigurable intelligent surfaces, non-coherent massive MIMO and channel estimation. Additionally, he is also researching integrating quantum communications in classical networks.

TUT-11: Fluid Antenna System (FAS): Fundamentals and Recent Advances

Location: 512 H

Speakers:Kai-Kit Wong (University College London, UK), Kin-Fai (Kenneth) Tong (Hong Kong Metropolitan University, China), Hao Xu (Southeast University, China), Wee Kiat (Aven) New (Huawei, Singapore)

Abstract: The upcoming sixth-generation (6G) wireless networks are expected to provide extremely high capacity, reliability, massive connectivity, and services beyond communications. In compliance with this trend, fluid antenna system (FAS), representing any software-controllable fluidic, dielectric or conductive structures, such as mechanical liquid-based antennas, radio-frequency (RF) pixel-based antennas, movable antennas, or metasurface, etc., that can reconfigure the shape, size, position, orientation, and other radiation characteristics, has been proposed in recent years for enabling flexible and adaptive wireless communications. Unlike the traditional antenna techniques where multiple antennas are discretely deployed at fixed positions with sufficient separation, the very fine spatial resolution and dynamic shape of FAS enable it to capitalize on the full range of spatial variations and flexibilities, resulting in significantly improved performance. Moreover, recent findings show that FAS is closely related to holographic MIMO system and reconfigurable intelligent surface (RIS). As a result, interesting discoveries can be obtained to advance the development of FAS from holographic MIMO or RIS and vice versa. FAS also offers a new capability to exploit the spatial opportunity where the interference suffers from deep fades for multiuser communication, leading to the formation of new multiple access. This tutorial will provide in-depth discussions on a wide range of FAS techniques and numerous potential applications that can be enhanced through FAS.

Speakers:

Kai-Kit Wong (University College London, UK)

Kai-Kit Wong received the BEng, the MPhil, and the PhD degrees, all in Electrical and Electronic Engineering, from the Hong Kong University of Science and Technology, Hong Kong, in 1996, 1998, and 2001, respectively. After graduation, he took up academic and research positions at the University of Hong Kong, Lucent Technologies, Bell-Labs, Holmdel, the Smart Antennas Research Group of Stanford University, and the University of Hull, UK. He is Chair in Wireless Communications at the Department of Electronic and Electrical Engineering, University College London, UK. His current research centers around 5G and beyond mobile communications. He is a co-recipient of the 2013 IEEE Signal Processing Letters Best Paper Award and the 2000 IEEE VTS Japan Chapter Award at the IEEE Vehicular Technology Conference in Japan in 2000, and a few other international best paper awards. He is Fellow of IEEE and IET and is also on the editorial board of several international journals. He served as the EIC for IEEE Wireless Communications Letters between 2020 and 2023.

Kin-Fai (Kenneth) Tong (Hong Kong Metropolitan University, China)

Kin-Fai (Kenneth) Tong is a Chair Professor of Antennas and Applied Electromagnetics at Hong Kong Metropolitan University, having previously served at UCL for 20 years. During his PhD research, he was among the first to introduce the concept of embedding microstrip patch antennas into mobile phone handsets. In 2000, as an Expert Researcher in the Photonic and Millimetre-wave Devices Group at Japan's National Institute of Information and Communications Technology, he worked on developing novel wideband photonic antennas operating at 38 GHz and 60 GHz. Prof. Tong is a Fellow of the IEEE, a Chartered Engineer with the UK Engineering Council, and a Fellow of both the Electromagnetics Academy in the US and the Higher Education Academy in the UK. His project funded by Innovate UK was rated "OUTSTANDING," placing it in the top 5% of all funded projects. Recently, his AgriTech Internet of Things (IoT) Hub project, supported by the EPSRC, has led to the establishment of two start-up companies and earned the UCL Provost’s Spirit of Enterprise Award. Prof. Tong served as the general chairman of the IEEE iWEM 2017 conference held in the UK, Lead Guest Editor of the IEEE OJAP Special Section, Subject Editor of IET Electronics Letters, and Associate Editor of IEEE AWPL.

Hao Xu (Southeast University, China)

Hao Xu received the B.S. degree in communication engineering from Nanjing University of Science and Technology, Nanjing, China, in 2013, and the Ph.D. degree in information and communication engineering with the National Mobile Communications Research Laboratory, Southeast University, Nanjing, China, in 2019. From 2019 to 2021, he worked as an Alexander von Humboldt (AvH) Post-Doctoral Research Fellow at the Faculty of Electrical Engineering and Computer Science, Technical University of Berlin, Germany. From 2021 to 2025, he worked as a Marie Skłodowska-Curie Actions (MSCA) Individual Fellow at the Department of Electronic and Electrical Engineering, University College London, UK. He is currently a professor with the National Mobile Communications Research Laboratory, Southeast University, Nanjing, China. His research interests mainly include communication theory, information theory, mathematical optimization, MIMO systems, and privacy and security. He has been serving as an Associate Editor for IEEE Transactions on Communications since August 2024 and IET Communications since August 2021. He was the recipient of the 2024 IEEE ISTT Best Paper Award and the 2024 IEEE MAPE Best Paper Award.

Wee Kiat (Aven) New (Huawei, Singapore)

Wee Kiat (Aven) New received his Ph.D in Electrical Engineering from Universiti Teknologi Malaysia, M.Eng.Sc in Electrical Engineering from University of Malaya and B.IT in Data Communications and Networking from Multimedia University. He was a visiting researcher at Lancaster University and University of Cyprus. He was a Research Fellow at the Department of Electronic and Electrical Engineering, University College London, UK. He is a wireless researcher at Huawei, Singapore. His research interests include information theory, optimization, stochastic processes, machine learning, and their applications in emerging areas of communications. He serves as an Associate Editor for IEEE Transactions on Vehicular Technology and as a Guest Editor for the IEEE Journal on Selected Areas in Communications on Fluid Antenna System and Other Next-Generation Reconfigurable Antenna Systems for Wireless Communications. He was also the TPC cochair for the 2024 ICC Workshop on Fluid Antenna Systems for 6G. He was the recipient of the 2021 IEEE Malaysia Comsoc/VTS Best Paper Award, the IEEE Malaysia AP/MTT/EMC Best Paper Awards in 2020, 2021, and 2022, the 2024 IEEE ISTT Best Paper Award, and the 2024 IEEE MAPE Best Paper Award.

TUT-12: Distributed Integrated Sensing and Communications: Foundations, Opportunities, and Challenges

Location: 514 A

Speakers: Henk Wymeersch (Chalmers University of Technology, Sweden); Hui Chen (Chalmers University of Technology, Sweden); George C. Alexandropoulos (University of Athens, Greece)

Abstract: Integrating sensing and communications can enhance real-time data transmission and environmental awareness, serving as a core function for future 6G systems. With an increased number of connected devices and ubiquitous coverage requirements, distributed integrated sensing and communication (DISAC) adopts a distributed architecture and a goal-oriented framework. Such a DISAC system enables large-scale and energy-efficient tracking of connected users and passive objects to facilitate communications and enable sensing services. These advancements will enable new applications in fields, like autonomous vehicles, smart cities, and industrial automation, where situational awareness and precision are crucial. This tutorial provides a comprehensive overview of the state-of-the-art in DISAC, discussing various technical challenges and practical solutions, including cooperative localization, resource optimization, and the integration of semantic communications via artificial intelligence (AI) with sensing. Three sections will be covered within this tutorial: (i) Fundamentals of DISAC operations and systems, (ii) Distributed communication-aided sensing, and (iii) Distributed sensing-aided communication. With detailed discussions on the DISAC architecture, high-resolution distributed processing, and AI-based semantic approaches, this tutorial offers background knowledge for newcomers to the field as well as advanced insights for experienced researchers looking to expand their expertise in emerging 6G technologies.

Biographies:

Henk Wymeersch (Chalmers University of Technology, Sweden)

Henk Wymeersch obtained the Ph.D. degree in Electrical Engineering/Applied Sciences in 2005 from Ghent University, Belgium. He is currently a Professor of Communication Systems with the Department of Electrical Engineering at Chalmers University of Technology, Sweden. Prior to joining Chalmers, he was a postdoctoral researcher from 2005 until 2009 with the Laboratory for Information and Decision Systems at the Massachusetts Institute of Technology. Prof. Wymeersch served as Associate Editor for IEEE Communication Letters (2009-2013), IEEE Transactions on Wireless Communications (since 2013), and IEEE Transactions on Communications (2016-2018) and is currently Senior Member of the IEEE Signal Processing Magazine Editorial Board. During 2019-2021, he was an IEEE Distinguished Lecturer with the Vehicular Technology Society. His current research interests include the convergence of communication and sensing, in a 5G and Beyond 5G context. He is a Fellow of the IEEE.

Hui Chen (Chalmers University of Technology, Sweden)

Bio coming soon.

George C. Alexandropoulos (University of Athens, Greece)

George C. Alexandropoulos received the Engineering Diploma (Integrated M.S.c), M.A.Sc., and Ph.D. degrees in Computer Engineering and Informatics from the School of Engineering, University of Patras, Greece in 2003, 2005, and 2010, respectively. He has held senior research positions at various Greek universities and research institutes, and he was a Senior Research Engineer and a Principal Researcher at the Mathematical and Algorithmic Sciences Lab, Paris Research Center, Huawei Technologies France, and at the Technology Innovation Institute, Abu Dhabi, United Arab Emirates, respectively. He is currently an Associate Professor with the Department of Informatics and Telecommunications, School of Sciences, National and Kapodistrian University of Athens (NKUA), Greece and an Adjunct Professor with the Department of Electrical and Computer Engineering, University of Illinois Chicago, Chicago, IL, USA. His research interests span the general areas of algorithmic design and performance analysis for wireless networks with emphasis on multi-antenna transceiver hardware architectures, full duplex radios, active and passive RISs, ISAC, millimeter wave and THz communications, as well as distributed machine learning algorithms. He currently serves as an Editor for IEEE Transactions on Communications, IEEE Transactions on Green Communications and Networking, IEEE Wireless Communications Letters, Frontiers in Communications and Networks, and the ITU Journal on Future and Evolving Technologies. Prof. Alexandropoulos is a Senior Member of the IEEE Communications, Signal Processing, Vehicular Technology, and Information Theory Societies, the Chair of the EURASIP Technical Area Committee on Signal Processing for Communications and Networking, as well as a registered Professional Engineer of the Technical Chamber of Greece. He has served as a Distinguished Lecturer of the IEEE Communications Society in 2022-2024. He has participated and/or technically managed more than 15 European Union, international, and Greek research, innovation, and development projects, including the H2020 RISE 6G, SNS JU TERRAMETA, SNS JU 6G-DISAC, and ESA PRISM projects dealing with RIS-empowered smart wireless environments, THz RISs, distributed ISAC, and RIS demonstration for localization and mapping, respectively. He has received the best Ph.D. thesis award 2010, the IEEE Communications Society Best Young Professional in Industry Award 2018, the EURASIP Best Paper Award of the Journal on Wireless Communications and Networking 2021, the IEEE Marconi Prize Paper Award in Wireless Communications 2021, the Best Paper Award from the IEEE GLOBECOM 2021, the IEEE Communications Society Fred Ellersick Prizes 2023 and 2024, and the IEEE Communications Society Leonard G. Abraham Prize 2024. More information is available at www.alexandropoulos.info.

TUT-13: Integrated Security, Privacy, and Trust Provisioning for Effective Collaboration in 6G-Enabled Systems

Location: 514 B

Speakers: Xianbin Wang (Western University, Canada); Botao Zhu (University of Western Ontario, Canada); He Fang (Fujian Normal University, China); Stefano Tomasin (University of Padova, Italy)

Abstract: To support a wide variety of applications with limited resources, future connected vertical systems rely on highly effective distributed collaborations. One fundamental hurdle in 6G-enabled vertical systems is how to guarantee tailored security, privacy and trust with extremely high efficiency and effectiveness while meeting the stringent collaboration requirements by leveraging distributed resources and capabilities. However, due to existing design constraints, independent provisioning of services, and the lack of a unified, quantifiable metric for evaluating integrated operations, achieving effective collaboration remains a significant challenge. The goal of this tutorial is to analyze the need for integrated security, privacy and trust provision in the 6G-enabled systems, identify the key enabling technologies, and present the ongoing research activities and future directions. Specifically, we will first identify critical technical gaps and promising directions for integrating security, privacy, and trust provisioning. Then, we will present integrated provisioning of security and communications based on the unified physical layer design. Recent studies on integrated provisioning of security, privacy, and emerging services will be discussed by presenting a unified platform using multi-dimensional multiple access. Furthermore, trust in 6G-enabled systems will be explored, including trust definition, integration of dynamic trust evaluation for collaborator selection and efficient task completion.

Biographies:

Xianbin Wang (Western University, Canada)

Xianbin Wang (Fellow, IEEE) received his Ph.D. degree in electrical and computer engineering from the National University of Singapore in 2001. He is a Professor and a Tier-1 Canada Research Chair in 5G and Wireless IoT Communications with Western University, Canada. Prior to joining Western University, he was with the Communications Research Centre Canada as a Research Scientist/Senior Research Scientist from 2002 to 2007. From 2001 to 2002, he was a System Designer at STMicroelectronics. His current research interests include 5G/6G technologies, Internet of Things, digital twin, machine learning, communications security, and intelligent communications. He has over 600 highly cited journals and conference papers, in addition to over 30 granted and pending patents and several standard contributions. Dr. Wang is a Fellow of the Canadian Academy of Engineering and a Fellow of the Engineering Institute of Canada. He has received many prestigious awards and recognitions, including the 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 ten Best Paper Awards. He is currently a member of the Senate, Senate Committee on Academic Policy and Senate Committee on University Planning at Western. He also serves on NSERC Discovery Grant Review Panel for Computer Science. He has been involved in many flagship conferences, including IEEE GLOBECOM, ICC, VTC, PIMRC, WCNC, CCECE, and ICNC, in different roles, such as General Chair, TPC Chair, Symposium Chair, Tutorial Instructor, Track Chair, Session Chair, and Keynote Speaker. He serves/has served as the Editor-in-Chief, Associate Editor-in-Chief, Area Editor, and editor/associate editor for over ten journals. He was the Chair of the IEEE ComSoc Signal Processing and Computing for Communications (SPCC) Technical Committee and is currently serving as the Central Area Chair of IEEE Canada.

Botao Zhu (University of Western Ontario, Canada)

Botao Zhu (Member, IEEE) received the PhD degree in electrical engineering from the University of Saskatchewan, Canada. He is currently a postdoctoral associate with the Department of Electrical and Computer Engineering, Western University, London, Canada. His current research interests include cooperative computing systems, distributed resource orchestration for coordinated task completion, integrated security, privacy and trust provisioning, and AI for network operation.

He Fang (Fujian Normal University, China)

He Fang received her Ph.D. degree in Electrical and Computer Engineering from Western University, Canada, in 2020, and Ph.D. degree in Applied Mathematics from Fujian Normal University, China, in 2018. She is currently a Full Professor with Fujian Normal University, China. Her research interests include intelligent security provision, trust management, machine learning, distributed optimization and collaboration techniques. She has over 60 peer-reviewed journals and conference papers. She serves as an Associate Editor of IEEE Transactions on Information Forensics and Security and China Communications, and served as a Guest Editor for several journals, including IEEE Wireless Communications and IEEE IoT Magazine. She was involved in many IEEE conferences including IEEE ICC, GLOBECOM, VTC, and ICCC, in different roles such as Lead Track Chair, Symposium Chair, Session Chair, Workshop Chair, and TPC member. She also served as the Vice-Chair of Communication/Broadcasting Chapter, IEEE London Section, Canada, from Sep. 2019 to Aug. 2021. She has received several awards, including the Best Paper Award from IEEE GLOBECOM 2023.

Stefano Tomasin (University of Padova, Italy)

Stefano Tomasin received the Ph.D. degree from the University of Padova, Italy, in 2003. During his studies he did internships with IBM Research (Switzerland) and Philips Research (Netherlands). He joined the University of Padova where he has been Assistant Professor (2005-2015), Associate Professor (2016-2022), and Full Professor (since 2022). He was visiting faculty at Qualcomm, San Diego (CA) in 2004, the Polytechnic University in Brooklyn (NY) in 2007 and the Mathematical and Algorithmic Sciences Laboratory of Huawei in Paris (France) in 2015. His current research interests include physical layer security, security of global navigation satellite systems, signal processing for wireless communications, synchronization, and scheduling of communication resources. He is a senior member of IEEE since 2011 (member since 1999) and a member of EURASIP since 2011. He is or has been an Editor of the IEEE Transactions on Vehicular Technologies (2011-2016), of the IEEE Transactions on Signal Processing (2017-2020), of the EURASIP Journal of Wireless Communications and Networking (since 2011) and of the IEEE Transactions on Information Forensics and Security (since 2020). He serves also as a Deputy Editor-in-Chief of the IEEE Transactions on Information Forensics and Security since January 2023.

TUT-14: Integrated and intelligent Connectivity for 6G and Beyond: Latest Advances & the Road Ahead

Location: 514 C

Speakers: Aryan Kaushik (Manchester Metropolitan University, United Kingdom (Great Britain); Marco Di Renzo (Paris-Saclay University, France)

Abstract: Following the recently adopted IMT-2030 framework by ITU-R, two major technologies of integrated sensing and communications (ISAC), intelligent metasurfaces (IM), i.e., RIS, holographic MIMO (H-MIMO) and stacked/flexible IM, herald a new era of 6G connectivity by transcending conventional communication networks to highly energy efficient and ultra-high data rates for smart radio environment, with exploration of frequency bands such as cmWave and sub-terahertz, and multiple use cases for 6G such as simultaneous imaging, mapping and localization, smart healthcare, etc. Furthermore, considering recent 3GPP Rel. 19, ISAC will play a vital role in 6G wireless standards, while H-MIMO, stacked IM, electromagnetic signal and information theory (ESIT) are some of the technologies expected in future 3GPP Rel. 20+. This tutorial will present a comprehensive overview of emerging ISAC and IM (particularly holographic, stacked and flexible IM) based 6G and beyond wireless communications including vision, standardization, fundamentals, challenges, use cases, and synergies between ISAC and IM technologies, and new opportunities. In terms of emerging designs, this tutorial will focus on RF chain and quantization optimization, wave domain signal processing for holographic/stacked/flexible IM, first-ever stacked IM prototype for ISAC, ESIT capabilities, index modulation, and IM-aided ISAC for non-terrestrial networks (NTN), and related applications.

Biographies:

Aryan Kaushik (Manchester Metropolitan University, United Kingdom (Great Britain)

Prof. Aryan Kaushik is currently Associate Professor at Manchester Met, UK, since 2024. Previously he has been with University of Sussex, University College London, University of Edinburgh, Hong Kong University of Science and Technology, and held visiting appointments at Imperial College London, University of Bologna, University of Luxembourg, Athena RC, and Beihang University. He has been External PhD Examiner internationally such as at UC3M, Spain (2023). He has been an Invited Panel Member at the UK EPSRC ICT Prioritisation Panel in 2023, Editor of four books on ISAC (2024 Edition), 6G NTN (2025 Edition), ESIT (2025 Edition) all by Elsevier, Intelligent Metasurfaces (2025 Edition) by Wiley, and several journals such as IEEE Transactions on Communications, IEEE Transactions on Mobile Computing, IEEE Communications Surveys & Tutorials, IEEE OJCOMS (Best Editor Award 2024 and 2023), IEEE Communications Letters (Exemplary Editor 2024 and 2023), IEEE IoT Magazine, IEEE CTN, and several special issues such as in IEEE Wireless Communications, IEEE Network, IEEE Communications Standards Magazine, etc. He has been invited/keynote and tutorial speaker for over 90 academic and industry events, and conferences globally such as at IEEE ICC 2025 (Two Tutorials), IEEE ICASSP 2025, IEEE ICC 2024, IEEE GLOBECOM 2024 and 2023, etc., has been chairing in Organizing and Technical Program Committees of over 10 flagship IEEE conferences such as IEEE ICC 2026, 2025 and 2024, etc., and has been General Chair of over 25 workshops such as at IEEE ICC 2025 and 2024, etc. For full profile, visit Prof. Aryan Kaushik's website: https://sites.google.com/view/aryankaushik

Marco Di Renzo (Paris-Saclay University, France)

Marco Di Renzo (Fellow, IEEE) received the Laurea (cum laude) and Ph.D. degrees in electrical engineering from the University of L’Aquila, Italy, in 2003 and 2007, respectively, and the Habilitation à Diriger des Recherches (Doctor of Science) degree from University Paris-Sud (currently Paris-Saclay University), France, in 2013. Currently, he is a CNRS Research Director (Professor) and the Head of the Intelligent Physical Communications group with the Laboratory of Signals and Systems (L2S) at CNRS \& CentraleSupélec, Paris-Saclay University, Paris, France, as well as a Chair Professor in Telecommunications Engineering with the Centre for Telecommunications Research -- Department of Engineering, King’s College London, London, United Kingdom. He was a France-Nokia Chair of Excellence in ICT at the University of Oulu (Finland), a Tan Chin Tuan Exchange Fellow in Engineering at Nanyang Technological University (Singapore), a Fulbright Fellow at The City University of New York (USA), a Nokia Foundation Visiting Professor at Aalto University (Finland), and a Royal Academy of Engineering Distinguished Visiting Fellow at Queen’s University Belfast (U.K.). He is a Fellow of the IEEE, IET, EURASIP, and AAIA; an Academician of AIIA; an Ordinary Member of the European Academy of Sciences and Arts, an Ordinary Member of the Academia Europaea; an Ambassador of the European Association on Antennas and Propagation; and a Highly Cited Researcher. His recent research awards include the Michel Monpetit Prize conferred by the French Academy of Sciences and the IEEE Communications Society Marconi Prize Paper Award in Wireless Communications. He served as the Editor-in-Chief of IEEE Communications Letters from 2019 to 2023. His current main roles within the IEEE Communications Society include serving as a Voting Member of the Fellow Evaluation Standing Committee, as the Chair of the Publications Misconduct Ad Hoc Committee, and as the Director of Journals.

THURSDAY, JUNE 12- MORNING SESSION (9:00 - 12:30)

T15: At the Dawn of 6GenAI: Generative Models and Multi-Modal LLMs for 6G Wireless Intelligence

Location: 512 B

Speakers: Abdulkadir Celik (King Abdullah University of Science & Technology, Saudi Arabia); Asmaa Abdallah (King Abdullah University of Science and Technology, Saudi Arabia); Ahmed Alkhateeb (Arizona State University, USA); Ahmed M. Eltawil (King Abdullah University of Science and Technology, Saudi Arabia)

Abstract: 6GenAI represents the rendezvous of 6G and Generative AI (GenAI) technologies to shape the future technology landscape that will bring once-futuristic visions into life. Although analytical models lay the foundations and offer systematic insights, the field has recently witnessed a noticeable surge in research efforts suggesting that machine learning (ML) and artificial intelligence (AI) can efficiently deal with complex problems by complementing or replacing model-based approaches. The majority of data-driven wireless research leans heavily on discriminative AI (DAI) that requires vast real-world datasets. Unlike DAI, generative AI (GenAI) pertains to generative models (GMs) capable of discerning the underlying data distribution, patterns, and features of the input data. Therefore, GenAI can complement DAI methods in various capacities, including data augmentation/imputation, disentanglement, and anomaly detection, among others. This makes GenAI a crucial asset in the wireless domain, where real-world data is often scarce, incomplete, or costly to acquire. This tutorial starts with preliminaries of 6G and wireless intelligence by outlining candidate 6G applications and services, presenting a taxonomy of state-of-the-art DAI models, exemplifying prominent DAI use cases, and elucidating the multifaceted ways through which GenAI enhances DAI. Subsequently, we present seminal GM examples such as generative adversarial networks, variational autoencoders, denoising diffusion probabilistic models, normalizing flows, attention mechanisms and generative transformers, and multi-modal large language models, to name a few. By distilling more than 150 technical papers, we will demonstrate to the audience how the scope of GenAI research spans core wireless research areas, including physical layer design; network optimization, organization, and management; network traffic analytics; cross-layer network security; and localization. Furthermore, we outline the central role of GMs in pioneering areas of 6G network research, including semantic communications, integrated sensing and communications, extremely large antenna arrays and near-field communications, non-terrestrial networks, digital twins, mobile edge computing and edge AI, adversarial ML, and trustworthy AI. Lastly, we shed light on the challenges ahead, suggesting potential strategies and promising remedies. Given its depth and breadth, we are confident that this tutorial will serve as a valuable resource for researchers and professionals planning to delve into this dynamic and promising domain.

Bios

Abdulkadir Celik (King Abdullah University of Science & Technology, Saudi Arabia)

Abdulkadir Celik (Senior Member, IEEE) received an M.S. in electrical engineering in 2013, an M.S. in computer engineering in 2015, and the Ph.D. in co-majors of electrical engineering and computer engineering in 2016, all from Iowa State University, Ames, IA, USA. He was a Postdoctoral Fellow with the King Abdullah University of Science and Technology, Thuwal, KSA, from 2016 to 2020, where he is currently a Senior Research Scientist with the Communications and Computing Systems Laboratory. Dr. Celik is the recipient of IEEE Communications Society's 2023 Outstanding Young Researcher Award for Europe, Middle East, and Africa (EMEA) region. He currently serves as an editor for IEEE Communications Letters, IEEE Wireless Communication Letters, and Frontiers in Communications and Networks. His research interests are in the broad areas of next-generation wireless communication systems and networks.

Asmaa Abdallah (King Abdullah University of Science and Technology, Saudi Arabia)

Asmaa Abdallah is a Research Scientist at King Abdullah University of Science and Technology (KAUST). From 2021 till 2024, she was a Post-Doctoral Fellow at KAUST. In 2020, she received the Ph.D. degree in Electrical and Computer Engineering at the American University of Beirut (AUB), Beirut, Lebanon. She received the M.S degree and B.S. degree (with High Distinction) in Computer and Communications Engineering from Rafik Hariri University (RHU), Lebanon in 2013 and 2015, respectively. Through her academic years, Dr. Abdallah was the recipient of a scholarship from the Lebanese National Counsel for Scientific Research (CNRS-L/AUB) to support her doctoral studies and received the Academic Excellence Award at RHU in 2013 for ranking first in the graduating class. In 2023, Dr. Abdallah has been selected by MIT technology review as one of the leading 15 Innovators under 35 in the MENA area. Her research interests include communication theory, stochastic geometry for wireless communications, machine learning for wireless communications, array signal processing, with emphasis on energy and spectral efficient algorithms for emerging wireless communication technologies. During her time at AUB, she served as an executive committee member of many societies including the Institute of Electrical and Electronics Engineers (IEEE), IEEE Young Professionals, and IEEE Women in Engineering, where she was instrumental in organizing national conferences and outreach events for young engineers. She is currently serving as an associate editor for IEEE communications letter.

Ahmed Alkhateeb (Arizona State University, USA)

Ahmed Alkhateeb received his B.S. and M.S. degrees in Electrical Engineering from Cairo University, Egypt, in 2008 and 2012, and his Ph.D. degree in Electrical Engineering from The University of Texas at Austin, USA, in August 2016. In Sept. 2016- Dec. 2017, he was a Wireless Communications Researcher at the Connectivity Lab, Facebook, in Menlo Park, CA. He joined Arizona State University (ASU) in Spring 2018, where he is currently an Associate Professor in the School of Electrical, Computer, and Energy Engineering. His research interests are in the broad areas of wireless communications, communication theory, signal processing, machine learning, and applied math. Dr. Alkhateeb is the recipient of the 2012 MCD Fellowship from The University of Texas at Austin, the 2016 IEEE Signal Processing Society Young Author Best Paper Award for his work on hybrid precoding and channel estimation in millimeter-wave communication systems, and the NSF CAREER Award in 2021.

Ahmed M. Eltawil (King Abdullah University of Science and Technology, Saudi Arabia)

Ahmed M. Eltawil is a Professor of Electrical and Computer Engineering and Associate Dean of Research at King Abdullah University of Science and Technology (KAUST) where he joined the Computer, Electrical and Mathematical Science and Engineering Division (CEMSE) in 2019. At KAUST, he is the founder and director of the Communication and Computing Systems Laboratory (CCSL). Prior to that he was with the Electrical Engineering and Computer Science Department at the University of California, Irvine (UCI) from 2005-2021, where he was the founder of the Wireless Systems and Circuits Laboratory (WSCL). Professor Eltawil’s research is in the area of efficient architectures for computing and communications systems in general, and wireless systems in particular, spanning the application domains of low-power mobile systems, machine learning platforms, sensor networks, body area networks and critical infrastructure networks. He received the Doctorate degree from the University of California, Los Angeles, in 2003 and the M.Sc. and B.Sc. degrees (with honors) from Cairo University, Giza, Egypt, in 1999 and 1997, respectively. Professor Eltawil has been on the technical program committees and steering committees for numerous conferences in the areas of low power computing and wireless communication system design, and is currently an editor for the IEEE Transactions on machine learning in communication and networking. He received several meritorious awards and grants, including the NSF CAREER grant supporting his research in low power computing and communication systems. He was an IEEE COMSOC distinguished lecturer (2023/24). In 2021, he was elected as “Innovator of the Year” by the Henry Samueli School of Engineering at the University of California, Irvine. He received two US congressional recognition awards for his contributions to innovations in wireless systems in 2021. Professor Eltawil is a veteran of multiple startups in the area of communication technology, all of which have had significant translational research impact.

T16: Optical Wireless Communication: From Fundamentals to Future Directions

Location: 512 C

Speakers: Mohammed Elamassie (Özyeğin Üniversitesi, Turkey); Murat Uysal (NYU Abu Dhabi, United Arab Emirates)

Abstract: Optical Wireless Communication (OWC) is a fast-growing field that uses light to provide high-speed, secure communication. This tutorial covers both fundamental concepts and advanced developments in OWC. It introduces key optical concepts, including optics, photonics, and quantum optics, and explains Lightwave signal modeling. Attendees will explore ray and wave optics principles such as reflection, refraction, and optical components like prisms, lenses, and fiber optics. Photon optics, including photon flux and arrival rate, will also be discussed, comparing ray, wave, and photon behaviors.

The second part focuses on OWC system design, covering light-emitting diodes (LEDs), laser diodes (LDs), and modulation techniques (direct and external). Optical receivers and detection methods, such as photodetectors and coherent detection, will be explained in detail. Channel modeling will be discussed, considering key challenges like atmospheric attenuation (due to rain, fog, and snow), Geometric losses (Plane waves, Gaussian beam, …), turbulence (beam wander, beam jitter, scintillation, and spectrum model), and diffraction. Strategies to mitigate these effects and optimize system performance will be discussed. Emerging topics like quantum communication, Quantum Key Distribution (QKD), and their applications in Free-Space Optical (FSO) and Visible Light Communication (VLC) systems will also be presented.

The tutorial will also cover applications of OWC in non-terrestrial networks (NTNs), including High Altitude Platform Stations (HAPS), Unmanned Aerial Vehicles (UAVs), and satellites. Practical applications, such as FSO for smart cities and VLC for the Internet of Things (IoT) and vehicular networks, will be explored alongside challenges in implementing these technologies.

Bios

Mohammed Elamassie (Özyeğin Üniversitesi, Türkiye)

Dr. Elamassie’s major distinctions include the Best Paper Award at the IEEE INTERNATIONAL BLACK SEA CONFERENCE ON COMMUNICATIONS AND NETWORKING 2019. He is also the recipient of the 2020 IEEE Turkey Doctoral Dissertation Award.

Murat Uysal (NYU Abu Dhabi, United Arab Emirates)

Murat Uysal (Fellow, IEEE) received the B.Sc. and the M.Sc. degrees in electronics and communication engineering from Istanbul Technical University, Turkey, in 1995 and 1998, respectively, and the Ph.D. degree in electrical engineering from Texas A&M University, College Station, USA, in 2001. Dr. Uysal began his academic career as an Assistant Professor at the University of Waterloo, Canada in 2002 and was promoted to Associate Professor with tenure in 2007. In 2011, he joined Ozyegin University, Turkey where he served as the Department Chair of Electrical and Electronics Engineering and the Founding Director of Center of Excellence in Optical Wireless Communication Technologies (OKATEM). Since 2023, he has been with New York University Abu Dhabi as a Professor of Electrical Engineering.

Dr. Uysal's research interests are in the broad area of communication theory with a particular emphasis on the physical layer aspects of wireless communication systems in radio and optical frequency bands. On these topics, he has authored some 400 journal and conference papers and received more than 23.000 citations with an h-index of 67. Dr. Uysal is an IEEE Fellow and the former Chair of IEEE Turkey Section. He currently serves as an Area Editor for IEEE TRANSACTIONS ON COMMUNICATIONS. In the past, he served as an Editor for IEEE TRANSACTIONS ON COMMUNICATIONS, IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, and IEEE COMMUNICATIONS LETTERS. He was involved in the organization of several IEEE conferences at various levels. In particular, he served as the Technical Program Committee Chair of major IEEE conferences including WCNC 2014, PIMRC 2019 and VTC-Fall 2019. Between 2011-2015, he was the Chair of EU COST Action OPTICWISE, a high-profile consolidated European scientific platform which brought together more than 150 researchers in the research area of optical wireless communication.

Dr. Uysal’s major distinctions include NSERC Discovery Accelerator Award in 2008, University of Waterloo Engineering Research Excellence Award in 2010, Turkish Academy of Sciences Distinguished Young Scientist Award in 2011, Ozyegin University Outstanding Researcher Award in 2014, National Instruments Engineering Impact Award in 2017, Elginkan Foundation Technology Award in 2018, IEEE COMMUNICATIONS SOCIETY Best Survey Paper Award in 2019, IEEE Turkey Section Outstanding Service Award in 2021, Mustafa Prize and Tubitak Science Award in 2023.

T17: B5G/6G Network Slicing for V2X Services: Technics, Standards, and Challenges

Location: 512 D

Speakers: Jiajia Liu (Northwestern Polytechnical University, China); Jiadai Wang (Northwestern Polytechnical University, China); Nei Kato (Tohoku University, Japan); Lei Zhao (University of Victoria)

Abstract: With B5G/6G technology, vehicular networks can achieve a full range of vehicle-to-everything (V2X) connections, providing users with intelligent, comfortable, safe, and efficient services. Network slicing is widely regarded as the key enabler of B5G/6G, which can divide the physical network into multiple logical networks as needed, transforming the network form from “one-size-fits-all” to “one-size-per-service” to meet differentiated performance metrics, which has received a lot of attention in the field of intelligent vehicular networks. We provide in this tutorial a comprehensive review of recent research works concerning B5G/6G network slicing for V2X services from three aspects: technics, standards, and challenges. Slicing technics lay the foundation for realizing end-to-end logical isolation and V2X service provision, which involves multiple technical domains such as radio access network (RAN), core network (CN), edge/cloud, and slicing management system. Since ubiquitous intelligence is one of the B5G/6G’s most striking features, we especially emphasize the artificial intelligence (AI)-assisted slicing technics for V2X services. Cross-domain and cross-vendor standards can provide technical guidance for network slicing, which is also the prelude to its widespread commercialization. Finally, we highlight the challenges of network slicing for V2X services and envision its future evolution.

Bios

Jiajia Liu (Northwestern Polytechnical University, China)

Jiajia Liu (F’25) is a full professor (Vice Dean) at the School of Cybersecurity, Northwestern Polytechnical University, and was a Full Professor (2013-2018) at the School of Cyber Engineering, Xidian University. He has published more than 200 peer-reviewed papers in many high quality publications, including prestigious IEEE journals and conferences. He received 2020 IEEE ComSoc Best YP Award in Academia, 2019 IEEE VTS Early Career Award, IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award in 2017, the Best Paper Awards from many international conferences including IEEE flagship events, such as IEEE GLOBECOM in 2022, 2019 and 2016, IEEE ICC in 2023, IEEE WiMob in 2019, IEEE WCNC in 2012 and 2014, IEEE IC-NIDC in 2018. His research interests cover a wide range of areas including wireless and mobile ad hoc networks, space-air-ground integrated networks, intelligent and connected vehicles, mobile/edge/cloud computing and storage, Internet of things security. He is the Chair of IEEE IOT-AHSN TC (2022- 2023), and is a Distinguished Lecturer of the IEEE Communications Society and Vehicular Technology Society.

Jiadai Wang (Northwestern Polytechnical University, China)

Jiadai Wang (S’18, M’22) is currently an associate professor with the School of Cybersecurity, Northwestern Polytechnical University, Xi’an, China. She has authored or co-authored more than 40 peer-reviewed papers in many high-quality publications, including prestigious IEEE journals and conferences. Her research interests cover network slicing, software-defined networking, connected vehicles, and 5G/6G communications.

Nei Kato (Tohoku University, Japan)

Bio coming soon.

Lei Zhao (University of Victoria)

Lei Zhao (S’18, M’22) received the B.S. and M.A.Sc. degrees in computer science and technology from Xidian University, Xi'an, China, in 2015 and 2018, respectively, and earned his Ph.D. in Electrical and Computer Engineering from the University of Victoria in 2023. He is currently a Post-Doctoral Fellow in the ECE Department at the University of Victoria. His research focuses on network virtualization, FL and optimization with applications in finance.

TUT-18: Six-Dimensional Movable Antenna for 6G: Opportunities and Challenges

Location: 512 E

Speakers: Xiaodan Shao (University of Waterloo, Canada); Rui Zhang (National University of Singapore, Singapore); Derrick Wing Kwan Ng (University of New South Wales, Australia); Lipeng Zhu (National University of Singapore, Singapore); Weidong Mei (University of Electronic Science and Technology of China, China)

Abstract: To meet the demand for increasingly higher data rates with a growing population of IoT devices in 6G wireless network, the current trend of MIMO technologies is to equip transceivers with drastically more antennas, such as extremely large antenna arrays. However, their performance improvement by using more fixed-position antennas comes at the cost of increasing hardware cost and energy consumption. In addition, the wireless network with fixed-position antennas cannot allocate its antenna resources flexibly based on the user spatial distribution. To address these challenges, six-dimensional movable antenna (6DMA) has been recently proposed as an innovative and transformative technology for 6G wireless network.

6DMA offers unprecedented flexibility and reconfigurability in antenna 3D position, 3D rotation (orientation), radiation, and polarization, thereby fundamentally improving antenna agility and adaptability, and providing additional degrees of freedom (DoFs) for designing more efficient transceivers in wireless communication and sensing applications. Through the intelligent exploitation of adaptive mechanisms at transmitters/receivers and advanced signal processing techniques, 6DMA fundamentally improves antenna agility and adaptability to allocate antenna resources, reconfigure wireless channels between transceivers in dynamic environments, and dramatically enhance communication and sensing capabilities without the need to add more antennas. Thus, it holds the promise of overcoming the hardware and software limitations of existing technologies such as large-scale MIMO. In this tutorial, we first present the signal and channel models of 6DMA by taking into account its hardware constraints. We then highlight its performance advantages as compared to other existing technologies such as fixed-position antennas, fluid antennas, antenna selection, and other reconfigurable MIMO. Next, we discuss the main challenges in designing 6DMA-aided wireless networks, including antenna position and rotation optimization, channel estimation, resource allocation, path planning, hardware imperfection, and so on. Moreover, we discuss two special cases of 6DMA, namely, rotatable 6DMA with fixed antenna position and positionable 6DMA with fixed antenna rotation, by highlighting their respective design issues and applications. We also present experiments and related industry/standardization activities. Finally, several future research directions are pointed out.

Bios

Xiaodan Shao (University of Waterloo, Canada)

Xiaodan Shao (IEEE Member) received the Ph.D. degree in information and communication engineering from Zhejiang University, China, in 2022. From June 2017 to June 2018, she was a Member of Technical Staff with China Resources Microelectronics Ltd., China. From 2021 to 2022, she was a Visiting Research Scholar with National University of Singapore, Singapore. From 2022 to 2024, she was a Humboldt Research Fellow with the Institute for Digital Communications, Friedrich-Alexander-University Erlangen-Nuremberg (FAU), Erlangen, Germany. She is currently a Postdoctoral Fellow at University of Waterloo, Waterloo, ON, Canada. Her current research interests include six-dimensional movable antenna (6DMA), integrated sensing and communications, massive access, statistical signal processing and optimization methods. Dr. Shao was a recipient of the Best Ph.D. Thesis Award of China Institute of Communications in 2023, and the IEEE International Conference on Wireless Communications and Signal Processing (WCSP) Best Paper Award in 2020. She serves as a guest editor for Electronics and as an Associate Editor for IEEE Wireless Communications Letters.

Rui Zhang (National University of Singapore, Singapore)

Dr. Rui Zhang (Fellow of IEEE, Fellow of the Academy of Engineering Singapore) received the Ph.D. degree from Stanford University in electrical engineering in 2007. He is currently with the School of Science and Engineering, Shenzhen Research Institute of Big Data, The Chinese University of Hong Kong, Shenzhen, as a X. Q. Deng Presidential Chair Professor. He is also with the Department of Electrical and Computer Engineering, National University of Singapore. His current research interests include wireless information and power transfer, UAV/satellite communications, intelligent reflecting surfaces and reconfigurable MIMO. He has published over 500 papers, which have been cited more than 10,000 times with the h-index over 140. He has been listed as a Highly Cited Researcher by Thomson Reuters/Clarivate Analytics since 2015. He was the recipient of the IEEE Communications Society Asia-Pacific Region Best Young Researcher Award in 2011, the Young Researcher Award of National University of Singapore in 2015, the Wireless Communications Technical Committee Recognition Award in 2020, the IEEE Signal Processing and Computing for Communications (SPCC) Technical Recognition Award in 2021, and the IEEE Communications Society Technical Committee on Cognitive Networks (TCCN) Recognition Award in 2023. His woks received 18 IEEE Best Journal Paper Awards, including the IEEE Marconi Prize Paper Award in Wireless Communications (twice), the IEEE Communications Society Heinrich Hertz Prize Paper Award (thrice), the IEEE Communications Society Stephen O. Rice Prize, the IEEE Signal Processing Society Best Paper Award, etc. He has served as an Editor for several IEEE journals, including TWC, TCOM, JSAC, TSP, TGCN, etc., and as TPC co-chair or organizing committee member for over 30 international conferences. He served as an IEEE Distinguished Lecturer of IEEE Communications Society and IEEE Signal Processing Society.

Derrick Wing Kwan Ng (University of New South Wales, Australia)

Derrick Wing Kwan Ng (IEEE Fellow) received the Ph.D. degree from The University of British Columbia, Vancouver, BC, Canada, in November 2012. He was a senior postdoctoral fellow at the Institute for Digital Communications, Friedrich-Alexander-University Erlangen-Nurnberg (FAU), Germany. He is currently a Scientia Associate Professor with the University of New South Wales, Sydney, NSW, Australia. His research interests include global optimization, ISAC, and physical layer security. Dr. Ng has been recognized as a Highly Cited Researcher by Clarivate Analytics since 2018. He was the recipient of the Australian Research Council (ARC) Discovery Early Career Researcher Award 2017, IEEE Communications Society Leonard G. Abraham Prize 2023, IEEE Communications Society Stephen O. Rice Prize 2022, Best Paper Awards at the WCSP 2020, 2021, Best Paper Awards at IEEE ICC 2018, 2021, 2023, 2024, Best Paper Awards at IEEE Globecom 2011, 2021, 2023, IEEE TCGCC Best Journal Paper Award 2018, etc. He is also an Area Editor of the IEEE TRANSACTIONS ON COMMUNICATIONS, an Associate Editor-in-Chief of the IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, and a member of the IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS executive editorial committee.

Lipeng Zhu (National University of Singapore, Singapore)

Lipeng Zhu (Member, IEEE) received the B.S. degree in the Department of Mathematics and System Sciences from Beihang University in 2017, and the Ph.D. degree in the Department of Electronic and Information Engineering from Beihang University in 2021. He is currently a Research Fellow with the Department of Electrical and Computer Engineering, National University of Singapore. His current research interests include movable antenna (MA)-enabled wireless communications, intelligent reflecting surface (IRS), millimeter-wave communications, unmanned aerial vehicle (UAV) communications, and non-orthogonal multiple access (NOMA). He was a recipient of the Best Ph.D. Thesis Award from China Education Society of Electronics in 2022, the Best Ph.D. Thesis Award from Beijing in 2022, the First Prize of Natural Science from Chinese Institute of Electronics in 2021, the Second Prize of the IEEE Communications Society Student Competition as the team leader in 2020, and the Exemplary Reviewer of the IEEE Transactions on Communications in 2022. He has been listed in the single-year ranking of World’s Top 2% Scientists by Stanford University since 2021. He served as the lead guest editor for the IEEE Wireless Communications Special Issue on “Movable and Reconfigurable Antennas-Empowered Wireless Networks”, the guest editor for the China Communications Special Issue on “LEO satellite access network (LEO-SAN)”, and the chair for Workshop on “Intelligent Movable and Reconfigurable Antennas for Future Wireless Communication and Sensing” at Globecom 2024 and ICC 2025. He has also served as the TPC member for many IEEE conferences/workshops. He serves as an Associate Editor for the IEEE Transactions on Mobile Computing, the IEEE Open Journal of the Communications Society, and the IEEE Open Journal of Vehicular Technology.

Weidong Mei (University of Electronic Science and Technology of China, China)

Weidong Mei (IEEE Member) received the B.Eng. degree in communication engineering and the M.Eng. degree in communication and information systems from the University of Electronic Science and Technology of China, Chengdu, China, in 2014 and 2017, respectively, and the Ph.D. degree from the NUS Graduate School, National University of Singapore, in 2021 under the Integrative Sciences and Engineering Programme (ISEP) Scholarship. He was a Research Fellow with the Department of Electrical and Computer Engineering, National University of Singapore, from July 2021 to January 2023. He is currently a Professor with the University of Electronic Science and Technology of China. His research interests include reconfigurable MIMO, intelligent reflecting surface, wireless drone communications, and convex optimization techniques. Dr. Mei has been listed in World's Top 2% Scientists by Stanford University since 2021. He was the recipient of the Outstanding Master's Thesis Award from the Chinese Institute of Electronics in 2017, and the Best Paper Award from the IEEE International Conference on Communications in 2021. He was honored as the Exemplary Reviewer of various IEEE journals and the Exemplary Editor of the IEEE Open Journal of the Communications Society in 2024. He serves as an Associate Editor for the IEEE Open Journal of the Communications Society and the Co-Chair for the Workshop on Intelligent and Reconfigurable Antennas for Future Wireless Communication and Sensing in IEEE Globecom 2024 and IEEE ICC 2025.

T19: Signal Processing Techniques for 6G Sensing: Recent Progress and Future Directions

Location: 512 F

Speakers: Liang Liu (The Hong Kong Polytechnic University, Hong Kong); Wei Yu (University of Toronto, Canada)

Abstract: According to IMT-2030 Framework, integrated sensing and communication (ISAC) has been defined as one of the six usage scenarios in the sixth-generation (6G) cellular network. It is expected that besides the conventional communication services, the 6G technology can also support sensing applications such as highprecision localization, high-resolution imaging, long-distance tracking, and real-time 3D-mapping. However, although the above functions have been realized in radar systems, there is still a long way to go before we can truly embed sensing functionality into 6G communication network. This is because the waveform of the communication signals is quite different from that of the radar signals, and the anchors in cellular network have different properties compared to radars. In this tutorial, we aim to present a thorough overview about the stateof- the-art progress for 6G sensing from a signal processing perspective, including the estimation methods that can efficiently extract range, angle, and Doppler information from orthogonal frequency division multiplexing (OFDM) signals, and the localization and tracking methods that can leverage various types of anchors in 6G network such as base stations (BSs), user equipments (UEs), and reconfigurable intelligent surfaces (RISs). We will also present out mmWave sensing platform. We believe that such a timely tutorial can be useful to inspire more interesting ideas from academia and industry on the important topic of 6G ISAC.

Bios

Liang Liu (The Hong Kong Polytechnic University, Hong Kong)

Liang Liu received the Ph.D. degree from the National University of Singapore, Singapore, in 2014. He is currently an Associate Professor with the Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University. His research interests lie in the next generation cellular technologies such as machine-type communications for the Internet of Things, integrated sensing and communication, etc. He was a recipient of the 2021 IEEE Signal Processing Society Best Paper Award, the 2017 IEEE Signal Processing Society Young Author Best Paper Award, the Best Student Award of 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), and the Best Paper Award of the 2011 International Conference on Wireless Communications and Signal Processing. He was recognized by Clarivate Analytics as a Highly Cited Researcher in 2018. He is an Editor of IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS. He was a Leading Guest Editor of IEEE WIRELESS COMMUNICATIONS Special Issue on Massive Machine-Type Communications for IoT. He is a co-author of the book ”Next Generation Multiple Access” published at Wiley-IEEE Press. He is an IEEE ComSoc Distinguished Lecturer.

Wei Yu (University of Toronto, Canada)

Wei Yu received the B.A.Sc. degree in computer engineering and mathematics from the University of Waterloo, Waterloo, ON, Canada, and the M.S. and Ph.D. degrees in electrical engineering from Stanford University, Stanford, CA, USA. He is currently a Professor in the Electrical and Computer Engineering Department at the University of Toronto, Toronto, ON, Canada, where he holds a Canada Research Chair (Tier 1) in Information Theory and Wireless Communications. He is a Fellow of IEEE, a Fellow of the Canadian Academy of Engineering and a member of the College of New Scholars, Artists, and Scientists of the Royal Society of Canada. Prof. Wei Yu served as the President of the IEEE Information Theory Society in 2021, as the Vice Chair of the Communication Theory Technical Committee of IEEE Communications Society in 2025, and as the Chair of the Signal Processing for Communications and Networking Technical Committee of the IEEE Signal Processing Society in 2017-2018. He was an IEEE Communications Society Distinguished Lecturer in 2015-2016. Prof. Wei Yu received the IEEE Communications Society and Information Theory Society Joint Paper Award in 2024, the IEEE Signal Processing Society Best Paper Award in 2021, 2017, and 2008, the IEEE Marconi Prize Paper Award in Wireless Communications in 2019, the IEEE Communications Society Award for Advances in Communication in 2019, the Journal of Communications and Networks Best Paper Award in 2017, the IEEE Communications Society Best Tutorial Paper Award in 2015, and the Steacie Memorial Fellowship in 2015. He is a Clarivate Highly Cited Researcher.

T20: From 1 to 100: Standardization in the Communications Industry

Location: 512 G

Speakers: Ruiqi Liu (ZTE Corporation, China); Tianqi Mao (Beijing Institute of Technology, China); Leyi Zhang (ZTE, China)

Abstract: Standardization is shaping the way the communication industry moves forward, and is the key to research and development of current and future networks. Despite the fact that many researchers devoted lots of efforts in bridging the scientific society and the industry, there still exists a gap in between, making it challenging for scientific researchers to correctly understand where the industry is heading as well as creating impact to the industry with their work. This gap is largely due to the fact that communication technologies are evolving in an unprecedented pace and the standards are getting more complicated for freshmen to comprehend. In this tutorial, the instructor aims to provide the audience with basic knowledge to be able to find, read and understand standard documents when needed, and even try to impact the standards with their work.

Bios

Ruiqi Liu (ZTE Corporation, China)

Ruiqi (Richie) Liu (S’14-M’20-SM’24) is a master researcher in the wireless and computing research institute of ZTE Corporation, responsible for long-term research as well as standardization. His main research interests include reconfigurable intelligent surfaces, integrated sensing and communication and wireless positioning. He is the author or co-author of several books and book chapters. He has made significant contributions to standardization of 5G / 5G-advanced in 3GPP by authoring and submitting more than 500 technical documents with over 100 approved, and serving as a rapporteur. He served as the chair of multiple correspondence groups in ITU-R WP5D towards 6G. He currently serves as the Vice Chair of ISG RIS in the ETSI. He is involved in organizing committees of international conferences and is invited to give multiple talks, including the keynote speech at IEEE Globecom 2024. He takes multiple leadership roles in the committees and boards in IEEE ComSoc and VTS, including the voting member of the ComSoc industry communities board. He served as the Deputy Editor-in-Chief of IET Quantum Communication, the Associate Editor for IEEE Communications Letters, the Editor of ITU Journal of Future and Evolving Technologies (ITU J-FET) and Guest Editor or Lead Guest Editor for a series of special issues. His recent awards include the 2022 SPCC-TC Outstanding Service Award and the Beijing Science and Technology Invention Award (Second Prize, 2023).

Tianqi Mao (Beijing Institute of Technology, China)

Bio coming soon.

Leyi Zhang (ZTE, China)

Leyi Zhang received the B.S. and M.S. degree (with honors) in electronic engineering from the Department of Electronic Information Engineering, Beihang University in 2020 and 2023 respectively. She is working as a researcher with the technology planning department of ZTE Corporation, responsible for long-term research as well as standardization. Her research interests include network security and quantum communication. She has many peer-reviewed publications. She took part in many international academic conferences as the session chair, invited speaker, and tutorial instructor. She participated in national key research projects as the research assistant or researcher. She actively participates in global standardization activities through platforms such as ITU-T, 3GPP, ETSI and CCSA. She currently serves as the chief delegate of ZTE to ITU-T SG17.

T21: QoS-Driven Digital Twins Over 6G Mobile Wireless Networks

Location: 512 H

Speakers: Xi Zhang (Texas A&M University, USA); Qixuan Zhu (Texas A&M University, USA)

Abstract: Digital Twin (DT) has been widely envisioned as a major intelligent application of 6G wireless networks in creating highly real-time and reliable wireless-connected environments to support efficient interactions and interplays between physical and virtual objects. On the other hand, DT has been increasingly recognized as a promising 6G wireless technique to efficiently realize the practical implementation of metaverse featured by various powerful virtual realities. As a digital representation of an intended real-world physical object and process, a DT needs to be timely and reliably updated by and synchronized with the corresponding physical systems. As a result, the stringent Quality-of-Service (QoS) guaranteed mobile wireless networks play the crucial role in efficiently supporting DT’s systems designing and performance modeling and analyses. Correspondingly, a large number of 6G wireless techniques have been identified and developed to enable the QoS-provisioning for implementing and supporting DT’s. However, how to efficiently integrate the various advanced 6G wireless techniques for supporting DT’s QoS guarantees over 6G mobile networks has imposed many new open-problems/issues not encountered before. To conquer these challenges, a great deal of efforts have been made in developing various 6G key promising-candidate techniques in terms of principle, theory, architecture, protocol, technologies, etc. Towards the above ends, in this tutorial we will address a number of architectures, theories, and techniques for supporting the QoS-driven Digital Twins over distributed computing systems based 6G mobile networks, which include: (1) Statistical-QoS theory; (2) massive Ulrta-Low Latency Communications (mURLLC); (3) Metaverse, VR, and XR; (4) Integrated Sensing, and Communications (ISAC); (5) Multi-Tier Computing; (6) Finite Blocklength Coding (FBC); (7) Wireless Caching; (8) massive-MIMO; (9) network functions virtualization (NFV); (10) information-centric network (ICN); (11) software defined networks (SDN); (12) Full Duplex (FD); (13) Device-to-Device (D2D), (14) mmWAVE; (15) THz + NANO Networks, (16) AI + ML, etc. and how these techniques can be integrated to efficiently support the statistical delay and error-rate bounded QoS provisioning for supporting/implementing DT over 6G mobile wireless networks. Furthermore, we will also discuss several future research directions, obstacles, and open problems in the general areas for DT over 6G mobile wireless networks.

Bios

Xi Zhang (Texas A&M University, USA)

Xi Zhang (IEEE Fellow, IEEE ComSoc Distinguished Lecturer, IEEE VTS Distinguished Lecturer) received the B.S. and M.S. degrees from Xidian University, Xi’an, China, the M.S. degree from Lehigh University, Bethlehem, PA, USA, all in electrical engineering and computer science, and the Ph.D. degree in electrical engineering and computer science (Electrical Engineering — Systems) from the University of Michigan, Ann Arbor, MI, USA.

He is currently a Full Professor and the Founding Director of the Networking and Information Systems Laboratory, Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA. He is a Fellow of the IEEE for contributions to Quality of Service (QoS) Theory in Mobile Wireless Networks. He was with the Networks and Distributed Systems Research Department, AT&T Bell Laboratories, Murray Hill, NJ, USA, and AT&T Laboratories Research, Florham Park, NJ, USA, in 1997. He was a Research Fellow with the School of Electrical Engineering, University of Technology, Sydney Australia, and the Department of Electrical and Computer Engineering, James Cook University, Australia. He has published more than 430 research articles (receiving more than 13257+ citations, with h-index: 57 and i10-index: 199) on wireless networks and communications systems, network protocol design and modeling, statistical communications, random signal processing, information theory, and control theory and systems. He received the U.S. National Science Foundation CAREER Award in 2004 for his research in the areas of mobile wireless and multicast networking and systems. He received seven Best Paper Awards at IEEE GLOBECOM 2024, IEEE GLOBECOM 2020, IEEE ICC 2018, IEEE GLOBECOM 2014, IEEE GLOBECOM 2009, IEEE GLOBECOM 2007, and IEEE WCNC 2010, respectively. One of his IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS papers has been listed as the IEEE Best Readings Paper (receiving the highest citation rate among all IEEE TRANSACTIONS/JOURNAL articles in the area) on wireless cognitive radio networks and statistical QoS provisioning over mobile wireless networking. He is an IEEE Distinguished Lecturer of both IEEE Communications Society and IEEE Vehicular Technology Society. He received the TEES Select Young Faculty Award for Excellence in Research Performance from the College of Engineering, Texas A&M University, in 2006, and the Outstanding Faculty Award from Texas A&M University, in 2020.

Professor Zhang is serving or has served as an Editor for IEEE TRANSACTIONS ON COMMUNICATIONS, IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING, and IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, twice as a Guest Editor for IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS for two special issues on “Broadband Wireless Communications for High Speed Vehicles” and “Wireless Video Transmissions,” an Associate Editor for IEEE COMMUNICATIONS LETTERS, twice as the Lead Guest Editor for IEEE Communications Magazine for two special issues on “Advances in Cooperative Wireless Networking” and “Underwater Wireless Communications and Networks: Theory and Applications,” a Guest Editor for IEEE Wireless Communications Magazine for special issue on “Next Generation CDMA vs. OFDMA for 4G Wireless Applications,” an Editor for Wiley’s Journal on Wireless Communications and Mobile Computing, Journal of Computer Systems, Networking, and Communications, and Wiley’s Journal on Security and Communications Networks, and an Area Editor for Elsevier’s Journal on Computer Communications, among many others. He is serving or has served as the TPC Chair for IEEE GLOBECOM 2011, TPC Co-Chair for IEEE ICDCS 2026, TPC Vice Chair for IEEE INFOCOM 2010, TPC Area Chair for IEEE INFOCOM 2012, Panel/Demo/Poster Chair for ACM MobiCom 2011, General Chair for IEEE ICDCS 2024 Workshop on “Digital Twin-Enabled 6G Multi-tier Distributed Computing Systems,” General Chair for IEEE WCNC 2013, TPC Chair for IEEE INFOCOM 2017–2019 Workshops on “Integrating Edge Computing, Caching, and Offloading in Next Generation Networks,” etc. For more information on Professor Xi Zhang’s research background, please visit: https://people.engr.tamu.edu/xizhang/index.html

Qixuan Zhu (Texas A&M University, USA

Qixuan Zhu (Networking and Information Systems Laboratory, Department of Electrical and Computer Engineering, Texas A&M University, College Station, Texas 77843, USA) received the B.S. degree from the Tianjin University of Technology and Education, Tianjin, China, and the M.S. degree from The George Washington University, Washington, DC, USA, all in electrical and computer engineering. She received the Ph.D. degree under the supervision of Professor Xi Zhang in the Networking and Information Systems Laboratory, Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA. She is the recipient of the Best Paper Award from IEEE ICC 2018. She also received the Hagler Institute for Advanced Study Heep Graduate Fellowship Award and Dr. Christa U. Pandey’84 Fellowship from Texas A&M University, College Station, TX 77843, USA.

THURSDAY, 12 JUNE - AFTERNOON SESSION (14:00 - 17:30)

T22: Machine Learning for 6G Wireless Networks: Latest Advances, Fundamentals, and Applications

Location: 512 B

Speakers: Hina Tabassum (York University, Canada); Aryan Kaushik (Manchester Metropolitan University, United Kingdom (Great Britain); Ping Wang (York University, Canada)

Abstract: Faster decision-making becomes imminent in future wireless networks as they are anticipated to be more complex, heterogeneous, and experience rapid channel variations due to higher transmission frequencies, massive antenna deployments with pencil-like beams, and ultra-dense access points. In this context, machine learning (ML) techniques are gaining prominence as they offer robust, fast, and scalable wireless solutions. This tutorial will first cover the fundamentals of advanced machine learning techniques and then discuss their applications in 6G wireless networks. Specifically, the tutorial will first cover the fundamental concepts related to deep learning, deep reinforcement learning, and generative artificial intelligence models. We then delve into the deep unsupervised learning methods for network resource allocation problems with non-linear and non-convex constraints. The use of deep implicit layers and differentiable projection methods to enable zero constraint violation will be discussed with applications to beamforming, phase-shift optimization, and power allocation problems. The tutorial will then cover the concepts related to Generative AI models and their applications to semantic communications. We will present an overview of fundamentals of popular Generative AI models, including GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), transformers, and diffusion models and explain how these models contribute to advancements in semantic communications. The tutorial will then focus on case-studies demonstrating the applications of reinforcement learning in vehicular networks, and non-terrestrial networks (NTN) such as with satellite and unmanned aerial vehicles (UAVs) based global connectivity, and conclude by pointing out the existing research gaps and highlight potential research directions.

Bios

Hina Tabassum (York University, Canada)

Dr. Tabassum received the Ph.D. degree from the King Abdullah University of Science and Technology (KAUST). She is currently an Associate Professor with the Lassonde School of Engineering, York University, Canada, where she joined as an Assistant Professor, in 2018. She is also appointed as a Visiting Faculty at University of Toronto in 2024 and the York Research Chair of 5G/6G-enabled mobility and sensing applications (2023-2028). Prior to that, she was a postdoctoral research associate at University of Manitoba, Canada. She has been selected as IEEE ComSoc Distinguished Lecturer (2025-2026). She is listed in the Stanford’s list of the World’s Top Two-Percent Researchers (2021-2024). She received the Lassonde Innovation Early-Career Researcher Award in 2023 and the N2Women: Rising Stars in Computer Networking and Communications in 2022. She has been recognized as an Exemplary Editor by the IEEE Communications Letters (2020), IEEE Open Journal of the Communications Society (IEEE OJCOMS) (2023 – 2024), and IEEE Transactions on Green Communications and Networking (2023). She was recognized as an Exemplary Reviewer (Top 2% of all reviewers) by IEEE Transactions on Communications in 2015, 2016, 2017, 2019, and 2020. She is the Founding Chair of the Special Interest Group on THz communications in IEEE Communications Society (ComSoc)-Radio Communications Committee (RCC). She served as an Associate Editor for IEEE Communications Letters (2019–2023), IEEE OJCOMS (2019–2023), and IEEE Transactions on Green Communications and Networking (2020–2023). Currently, she is also serving as an Area Editor for IEEE OJCOMS and an Associate Editor for IEEE Transactions on Communications, IEEE Transactions on Wireless Communications, and IEEE Communications Surveys and Tutorials.

Aryan Kaushik (Manchester Metropolitan University, United Kingdom (Great Britain)

Prof. Aryan Kaushik is currently Associate Professor at Manchester Met, UK, since 2024. Previously he has been with University of Sussex, University College London, University of Edinburgh, Hong Kong University of Science and Technology, and held visiting appointments at Imperial College London, University of Bologna, University of Luxembourg, Athena RC, and Beihang University. He has been External PhD Examiner internationally such as at UC3M, Spain (2023). He has been an Invited Panel Member at the UK EPSRC ICT Prioritisation Panel in 2023, Editor of four books on ISAC (2024 Edition), 6G NTN (2025 Edition), ESIT (2025 Edition) all by Elsevier, Intelligent Metasurfaces (2025 Edition) by Wiley, and several journals such as IEEE Transactions on Communications, IEEE Transactions on Mobile Computing, IEEE Communications Surveys & Tutorials, IEEE OJCOMS (Best Editor Award 2024 and 2023), IEEE Communications Letters (Exemplary Editor 2024 and 2023), IEEE IoT Magazine, IEEE CTN, and several special issues such as in IEEE Wireless Communications, IEEE Network, IEEE Communications Standards Magazine, etc. He has been invited/keynote and tutorial speaker for over 90 academic and industry events, and conferences globally such as at IEEE ICC 2025 (Two Tutorials), IEEE ICASSP 2025, IEEE ICC 2024, IEEE GLOBECOM 2024 and 2023, etc., has been chairing in Organizing and Technical Program Committees of over 10 flagship IEEE conferences such as IEEE ICC 2026, 2025 and 2024, etc., and has been General Chair of over 25 workshops such as at IEEE ICC 2025 and 2024, etc. For full profile, visit Prof. Aryan Kaushik’s website: https://sites.google.com/view/aryankaushik

Ping Wang (York University, Canada)

Ping Wang is a Professor at the Department of Electrical Engineering and Computer Science, York University, and a Tier 2 York Research Chair. Prior to that, she was with Nanyang Technological University, Singapore, from 2008 to 2018. Her recent research interests focus on integrating Artificial Intelligence (AI) techniques into communications networks. Her scholarly works have been widely disseminated through top-ranked IEEE journals/conferences and received the IEEE Communications Society Best Survey Paper Award in 2023, and the Best Paper Awards from IEEE prestigious conference WCNC in 2012, 2020 and 2022, from IEEE Communication Society: Green Communications & Computing Technical Committee in 2018, from IEEE flagship conference ICC in 2007. She has been serving as the associate editor-in-chief for IEEE Communications Surveys & Tutorials and an editor for several reputed journals, including IEEE Transactions on Wireless Communications. She is a Fellow of the IEEE and a Distinguished Lecturer of the IEEE Vehicular Technology Society (VTS). She is also the Chair of the Education Committee of IEEE VTS.

T23: Sustainable Agriculture Productivity with IoT, AI, and Blockchain Through Advanced Networking

Location: 512 C

Speakers: Nidal Nasser (Alfaisal University, Saudi Arabia); Asmaa Ali (Western University, Canada)

Abstract: This tutorial delves deeply into the pivotal role of network and communication protocols and standards in transforming greenhouse productivity through the seamless integration of the Internet of Things (IoT), Artificial Intelligence (AI), and Blockchain technologies. Emphasizing the critical importance of robust and reliable communication frameworks, it guides through the setup of IoT devices, leveraging standardized protocols for real-time environmental monitoring. It further explores how adhering to communication standards enhances the application of AI for in-depth data analysis, offering precise insights into crop performance. The tutorial underscores the utilization of blockchain technology within these communication protocols to secure the supply chain, guarantee product quality, and boost consumer confidence. By adhering to established network standards and protocols, greenhouse operators can significantly elevate crop quality and yield, cut down costs, and minimize manual oversight, thereby upgrading their operations to be more efficient, productive, and sustainable. Moreover, the tutorial sheds light on the commercial viability of adopting such an integrated system, underpinned by reliable communication practices, to satisfy the growing demands of the greenhouse industry and spur revenue generation.

Bios

Nidal Nasser (Alfaisal University, Saudi Arabia)

Nidal Nasser, SMIEEE, is a distinguished academic and researcher in wireless communication networks. He holds B.Sc. and M.Sc. degrees in Computer Engineering from Kuwait University and a Ph.D. from Queen’s University, Canada. He is a Professor of Software Engineering at Alfaisal University, where he also served as Dean of Engineering (2014-2017). Dr. Nasser has over 190 publications and has received numerous awards, including Best Research Paper Awards and the Faculty Award for Research Excellence. Recognized by Stanford University as one of the "World’s Top 2% Scientists," he is also an IEEE ComSoc Distinguished Lecturer (2023-2024). He serves as an associate editor for Wiley's International Journal on Communication Systems and Frontiers in Communications and Networks. His expertise spans mobile applications, big data, IoT, AI, and blockchain. With leadership roles in IEEE conferences, Dr. Nasser continues to shape advancements in wireless networks and systems. He is an IEEE Senior member.

Asmaa Ali (Western University, Canada)

Dr. Asmaa Ali received her B.Sc. and M.Sc. in Electrical Engineering from Kuwait University, State of Kuwait, in 2000 and 2004, respectively. She received another M.Sc. in Engineering System and Computing from the University of Guelph, Guelph, Ontario, Canada, in 2015. She completed her Ph.D. in the School of Computing at Queen’s University, Kingston, Ontario, Canada, in 2020. She is currently a postdoc in the IoT Research Lab at Alfaisal University. She received the Best Paper Award at the IEEE International Conference on Smart Applications, Communications, and Networking (SmartNets 2019). Her current research interests are computer vision and pattern recognition, communication, robotics, control system, engineering analysis, artificial intelligence, machine/deep learning, data science, and wireless sensor network.

T24: Delay-Doppler Domain Multi-Carrier Modulation for NextG Communications

Location: 512 D

Speakers: Jinhong Yuan (University of New South Wales, Australia); Akram Shafie (University of New South Wales, Australia); Jun Tong (University of Wollongong, Australia)

Abstract: Delay-Doppler (DD) domain multi-carrier (MC) (DDMC) modulation and chirp-based modulation schemes have been recently proposed as promising techniques for achieving reliable communications for high-mobility environments, underwater acoustic channels, and satellite systems. DDMC achieves sufficient orthogonality w.r.t. the fine-time and fine-frequency resolutions of the DD domain, enabling it to couple the information symbols with the DD channel effectively. This addresses the key challenge caused by Doppler in linear time-varying (LTV) channels and avoids some impediments of Orthogonal Time Frequency Space (OTFS). Furthermore, chirp signals are highly Doppler-resilient, allowing chirp-based modulation schemes to enable reliable demodulation in LTV channels. This tutorial will provide a timely overview of the novel DDMC scheme introduced in 2022, named orthogonal DD multiplexing (ODDM), as well as of several chirp-based modulation techniques such as Orthogonal Chirp Division Multiplexing (OCDM) and Affine Frequency Division Multiplexing (AFDM). Following a recap of the historical development of modulation techniques, the emerging use cases and challenges of B5G/6G, and typical wireless communication channels, DDMC/ODDM and its unique prototype pulse will be introduced. Subsequently, recent findings on the fundamental characteristics of ODDM will be introduced, including the spectrum/OOBE, time-frequency localization, input-output relation, implementations, and the relation between ODDM and other variants of DD modulation. State-of-the-art channel estimation and signal detection solutions for DDMC/ODDM will also be discussed, before exploring research challenges and emerging opportunities for DDMC/ODDM. Finally, the overview of OCDM and AFDM operations and how they can explore diversity and simplify equalization will be discussed. Overall, this tutorial comprehensively covers the concepts and tools for analyzing and optimizing DDMC and chirp-based modulation schemes for wireless communication and sensing applications, thereby providing the opportunity for researchers and industry to inspire new ideas and facilitate future R&D on this exciting topic.

Bios

Jinhong Yuan (University of New South Wales, Australia)

Jinhong Yuan (Fellow, IEEE) received the B.E. and Ph.D. degrees in electronics engineering in 1991 and 1997, respectively. From 1997 to 1999, he was a Research Fellow at the University of Sydney, Sydney, Australia. In 2000, he joined the School of Electrical Engineering and Telecommunications, University of New South Wales, Sydney, Australia, where he is currently Head of School. He has published two books, five book chapters, over 300 papers in telecommunications journals and conference proceedings, and 50 industrial reports. He is a co-inventor of 10 patents. He has co-authored five Best Paper Awards and one Best Poster Award. He is an IEEE Fellow and currently serving as an Associate Editor for the IEEE TCOM. He has served on IEEE Fellow Evaluation Committee for ITSoc and VTSoC. He served as the IEEE NSW Chapter Chair of Joint Communications/Signal Processions/Ocean Engineering Chapter during 2011-2014 and served as an Associate Editor for the IEEE TCOM from 2012-2017 and for IEEE TWC from 2018-2023. His current research interests include digital modulation, error control coding and information theory, communication theory, and wireless communications.

Akram Shafie (University of New South Wales, Australia)

Akram Shafie (Member, IEEE) received the B.Sc. degree from the University of Peradeniya, Sri Lanka, in 2017, and the Ph.D. degree in engineering and computer science from The Australian National University, Australia, in 2023. He is currently a Research Associate and an Associate Lecturer with the School of Electrical Engineering and Telecommunications, University of New South Wales, Australia. He was the recipient of the Best Paper Award at the 2022 IEEE GlobeCom and the 2019 Sri Lankan President’s Award for Scientific Research. His research interests include delay-Doppler modulation for high-mobility scenarios and/or underwater communications, terahertz communications, and integrated sensing and communications.

Jun Tong (University of Wollongong, Australia)

Jun Tong (Member, IEEE) received the Ph.D. degree in electronic engineering from City University of Hong Kong in 2009. Currently, he is an Associate Professor with the School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Australia. He was a Research Academic at the University of Newcastle, Australia, from June 2009 until March 2011, and an Akademischer Rat with the University of Paderborn, Germany, from April 2011 until June 2013. His current research interests include wireless communications and signal processing.

T25: Channel Estimation, Interpolation and Extrapolation in Doubly-dispersive Channels

Location: 512 E

Speakers: Zijun Gong (Hong Kong University of Science and Technology (GZ), China & Hong Kong University of Science and Technology, Hong Kong); Fan Jiang (Pengcheng Laboratory, China); Shuai Han (Harbin Institute of Technology, China)

Abstract: In the past several decades, the OFDM (Orthogonal Frequency Division Multiplexing) modulation has enjoyed a legendary success in wireless communications. However, the fundamental theories of OFDM are developed around one assumption: the wireless channels are linear time-invariant (LTI). But the channel is constantly changing over time for mobile transceivers in practice, and it is only approximately static in a short period of time, i.e., the block-fading or quasi-static model. This leads to many problems, and one of them is frequent channel estimation. As carrier frequency or device mobility increases, we will have to estimate the channel state information (CSI) more and more frequently, and the channel training overhead will eventually become unbearable. The fundamental reason for this problem is the LTI channel model, in which channel variation over time is ignored. From another perspective, channel gains in adjacent data blocks are correlated over time and frequency, and can we harness such correlation for improved performance? In recent years, with the rise of the orthogonal time frequency space modulation (OTFS) and other waveforms engineered for doubly-dispersive channels, people are paying attention to a very important characteristic of underspread time-varying channels, the predictability. That is, although the channel response is changing over time and frequency, we can actually use a small number of pilots to recover the complete channel response through interpolation. Such predictability unveils the strong correlation between channel gains in time and frequency, and it is deeply rooted in the sparsity of channel response in the delay-Doppler (D-D) domain. In this tutorial, we will systematically review the theories and techniques that can be used to harness the predictability for channel estimation, interpolation, and extrapolation.

This tutorial 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. A systematic overview of the network synchronization process and theoretical analysis of contributing factors to these performance gaps are given to shed light on potential synchronization design directions. In bridging the gaps, several recent promising synchronization techniques will be presented to achieve more accurate, intelligent, low-overhead, and secure network synchronization. Furthermore, promising research directions on synchronization over networked systems about synchronization process design and integration with vertical applications will be presented to guide researchers and industry practitioners toward effective network synchronization in the 6G era.

Bios

Zijun Gong (Hong Kong University of Science and Technology (GZ), China & Hong Kong University of Science and Technology, Hong Kong)

Zijun Gong (Member, IEEE) received the B.Eng. and M.Eng. degrees from the Harbin Institute of Technology (HIT), Harbin, China, in 2013 and 2015, respectively, and the Ph.D. degree from the Memorial University of Newfoundland, St. John’s, NL, Canada, in 2021. From May 2021 to December 2021, he worked at the University of Waterloo as a Post-Doctoral Researcher. He is currently an Assistant Professor with the IoT Thrust in Information Hub, The Hong Kong University of Science and Technology (GZ). He is also an affiliate Assistant Professor at the ECE Department, HKUST, Hong Kong. His research interests lie in statistical signal processing and optimization, including channel estimation in massive MIMO, and millimeter wave communications, mmWave radar, radio propagation modeling, localization of WSN, and localization of underwater targets and devices. He was a recipient of the Best Paper Award at the IEEE GLOBECOM’17, Singapore, in December 2017.

Fan Jiang (Pengcheng Laboratory, China)

Fan Jiang received the Ph.D. degree from Memorial University of Newfoundland (MUN), St. John’s, Canada, the M.E. degree in Communication and Information Systems from Southeast University (SEU), Nanjing, China, and the B.E. degree in Communication Engineering from University of Electronic Science and Technology of China (UESTC), Chengdu, China, in 2018, 2013, 2010, respectively. He held Postdoc positions in the Department of Electrical Engineering, Chalmers University of Technology, the Laboratory for Information and Decision Systems (LIDS), Massachusetts Institute of Technology (MIT), and the Faculty of Engineering and Applied Science, MUN, after graduation. He is now an associate researcher at Pengcheng Laboratory (PCL), Shenzhen, China, since July 2023, and was an assistant professor at Halmstad University, Sweden, before the current appointment. His research interest includes signal processing for wireless communications, reconfigurable intelligent surface technology, and integrated sensing and communications framework. He has received the Postdoctoral Fellowship from Natural Science and Engineering Research Council (NSERC) of Canada in 2019, The Governor General’s Gold Medal at MUN in 2018, and the Best Paper Award at IEEE GLOBECOM 2017, FCN 2024

Shuai Han (Harbin Institute of Technology, China)

Shuai Han (S’11–M’12–SM’17) is currently a full Professor at Department of Electronics and Communication Engineering, Harbin Institute of Technology. Shuai Han’s research interests include intelligent communications security, satellite IoT and the integrated satellite-terrestrial communication networks. Over the academic career, his students and he have contributed in various fields in wireless networks and published more than 80 journal papers. He has won the BPA award several times in WiCON, MLICOM and IWCMC. As PI, he has five national grants and more than twenty industrial grants on wireless networks and positioning. Also, he participated some major projects in national level in China. He is an associate editor of IEEE China Communications, IEEE ACCESS, Journal of Communications and Information Networks(JCIN), Journal of Telemetry, Tracking and Command, Journal of Signal Processing. And has served as guest editors for many IEEE magazines and journals. He has served as a co-chair for technical symposia of international conference IEEE GC, IEEE ICC, IEEE VTC. He has also served as the TPC Chair for some international conferences, including the IWCMC, AICON and MLICOM. He is a member of 2020-2021 R10 Awards & Recognition Committee. Also he is senior member of IEEE Communication Society, the Vice Chair of IEEE IoT-AHSN Technical committee, the Chair of IEEE BTS Harbin Chapter, the Vice Chair of IEEE Harbin ComSoc Chapter and Vice Chair of IEEE Harbin VTS Chapter.

T26: Towards 6G and B6G Communications: Wireless Channel Measurements, Characteristics Analysis, and Modeling

Location: 512 F

Speakers: Cheng-Xiang Wang (Southeast University, China & Purple Mountain Laboratories, China); Jie Huang (Southeast University, China); Chen Huang (Purple Mountain Laboratories & Southeast University, China); Junling Li (Southeast University, China); Harald Haas (University of Cambridge, United Kingdom (Great Britain)

Abstract: Channel measurements and realistic channel models with good accuracy-complexity-pervasiveness tradeoffs are essential for designing, evaluating, and optimizing wireless communication systems. The proposed tutorial aims to address recent advances and future challenges in channel measurement and modeling techniques for sixth generation (6G) and Beyond 6G (B6G) wireless systems by providing a comprehensive and in-depth course for communication professionals/academics. Network architecture and key technologies for 6G that will enable global coverage, full spectra, and full applications will be discussed first. 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. At last, some preliminary works on three dimensional (3D) continuous-space radio channel modeling will be presented. Future research challenges and trends for 6G channel measurements and models will be discussed in the end of the tutorial.

Bios

Cheng-Xiang Wang (Southeast University, China & Purple Mountain Laboratories, China)

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 over 620 papers in refereed journals and conference proceedings, including 28 highly cited papers. He has also delivered 32 invited keynote speeches/talks and 21 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 30 international conferences. He received IEEE Neal Shepherd Memorial Best Propagation Paper Award in 2024. He also received 19 Best Paper Awards from international conferences.

Jie Huang (Southeast University, China)

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, UK. Since Mar. 2019, he is a part-time researcher in Purple Mountain Laboratories, China. Since Nov. 2020, he is an Associate Professor in the National Mobile Communications Research Laboratory, Southeast University. He has authored and co-authored more than 120 papers in refereed journals and conference proceedings. He received IEEE Neal Shepherd Memorial Best Propagation Paper Award in 2024 and Best Paper Awards from WPMC 2016, WCSP 2020, WCSP 2021, and WCSP 2024. He has delivered over 10 tutorials in international conferences, including IEEE Globecom and IEEE ICC. His research interests include millimeter wave, massive MIMO, reconfigurable intelligent surface channel measurements and modeling, electromagnetic information theory, and 6G wireless communications.

Chen Huang (Purple Mountain Laboratories & Southeast University, China)

Dr. Chen Huang received the Ph.D. degree from Beijing Jiaotong University, Beijing, China, in 2021. From 2018 to 2020, he has been a Visiting Scholar with the University of Southern California (USC), Los Angeles, CA, USA and with the Universite Catholique de Louvain (UCL), Louvain-la-Neuve, Belgium. From April 2021 to April 2023, he was a Postdoctoral Research Associate in the Pervasive Communication Research Center, Purple Mountain Laboratories (PML), Nanjing, 211111, China, and also in the National Mobile Communications Research Laboratory, School of Information Science and Engineering, Southeast University (SEU), Nanjing, 210096, China. Since April 2023, he has been an research associate professor in the Pervasive Communication Research Center, PML, and an extramural supervisor in the National Mobile Communications Research Laboratory, School of Information Science and Engineering, SEU, China. He was selected in Young Elite Scientists Sponsorship Program by China Association for Science and Technology and Outstanding Postdoctoral Fellow Program in Jiangsu, received 4 times the Best Paper Award from IEEE/CIC ICCC 2024, IEEE ICCT2023, WCSP 2018, IEEE/CIC ICCC 2018, and serves as the Associate Editor for IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY and Technical Program Committee (TPC) member for several conferences, including GlobeCom, ICC, VTC-fall, VTC-spring, etc. His research interests include 6G channel measurements, characterization, and modeling, machine learning-based channel prediction, and localization. He has authored/co-authored 1 book chapters, more than 60 journal and conference papers, as well as 17 patents.

Junling Li (Southeast University, China)

Dr. Junling Li received the B.S. degree from Tianjin University, Tianjin, China, and the M.S. degree from the Beijing University of Posts and Telecommunications, Beijing, China, in 2013 and 2016, respectively. In 2020, she received the Ph.D. degree from the Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada. She was a Joint Postdoctoral Research Fellow at Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS), University of Waterloo, and the Chinese University of Hong Kong, Shenzhen from 2020 to 2022. She is currently an Associate Professor in the National Mobile Communications Research Laboratory at Southeast University, Nanjing, China. She has authored and co-authored more than 40 papers in refereed journals and conference proceedings. She received the Best Paper Awards from ICCC 2019 and ICCT 2023. Her research interests include digital twin online channel modeling, 6G channel measurements and modeling, machine learning based channel prediction.

Harald Haas (University of Cambridge, United Kingdom (Great Britain)

Prof. Harald Haas received the Ph.D. degree in wireless communications from the University of Edinburgh, Edinburgh, U.K., in 2001. He was with the University of Edinburgh and was Director of the LiFi Research and Development Centre at the University of Strathclyde. He is now with the University of Cambridge. He is also the Initiator, co-founder and Chief Scientific Officer of pureLiFi Ltd. He has authored 650 conference and journal papers with more than 50000 citations and holds more than 45 patents, 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.

T27: Digital Twin Edge Networks for 6G: architectures, efficiency and future perspectives

Location: 512 G

Speakers: Yaru Fu (Hong Kong Metropolitan University, China); Yongna Guo (KTH Royal Institute of Technology, Sweden); Yan Zhang (University of Oslo, Norway); Tony Q. S. Quek (Singapore University of Technology and Design, Singapore)

Abstract: This tutorial offers an in-depth examination of the practical issues related to Digital Twin in future intelligent 6G networks, emphasizing the deployment, synchronization, migration, and optimization of digital twins to create a reliable and efficient network. First, we introduce fundamental concepts of digital twins, including their definitions, networks, and lifecycles. Following that, we will delve into the complexities of optimizing digital twin placement and ensuring reliable synchronization within edge networks, with an emphasis on maintaining network reliability amidst fluctuations in workload and the mobility of mobile users. Then, we will examine the complexities of deploying, migrating, and synchronizing digital twins in multi-access edge computing (MEC) networks, focusing on the optimization of essential performance metrics like latency and energy efficiency. We will also highlight Age of Information as a key indicator for measuring data freshness, which is critical for determining the fidelity of digital twin networks. Next, we will introduce digital twin in promising 6G air-ground network and explore the digital twin-enabled distributed learning in this context. We will discuss the incentive mechanisms for air-ground cooperation. Finally, we conclude the tutorial with potential future research directions, challenges, and possible solutions.

Bios

Yaru Fu (Hong Kong Metropolitan University, China)

Dr. Fu currently serves as an Assistant Professor and the Head of the Centre for Research in Advanced Network Technologies (CRANT) at Hong Kong Metropolitan University. She earned her Ph.D. from the Department of Electronic Engineering at City University of Hong Kong in 2018. Then, she joined in the Institute of Network Coding (INC), The Chinese University of Hong Kong (CUHK) as a Postdoc Research Assistant. From 2018 to 2020, she served as a Research Fellow at the Singapore University of Technology and Design. From Feb. 2016 to May. 2016, she was a visiting researcher in Telecom Paris and the Laboratory of Information, Networking and Communication Sciences (Lincs). She was also a visiting researcher with Nokia Bell Labs in France. Dr. Fu’s primary research interests include B5G/6G technologies, digital twins, and machine learning. She has authored over 100 papers in prestigious IEEE journals and conferences. Dr. Fu is on the editorial boards of IEEE Transactions on Cognitive Communications and Networking (TCCN), IEEE Open Journal of the Communications Society (OJ-COMS), IEEE Internet of Things Journal (IoTJ), IEEE Wireless Communications Letter (WCL), and IEEE Networking Letter (LNET). In recognition of her contributions, Dr. Fu received the IEEE WCL Best Editor Award in 2021, the IEEE Transactions on Communications (TCOM) Exemplary Reviewer Award in 2022, the President's Award of Hong Kong Metropolitan University (being the sole recipient) in 2023, and the IEEE Global Communications Conference (GLOBECOM) Best Paper Award in 2024. Over the past three years, she has spearheaded projects totaling over HKD 10 million as a Project Principal Investigator (PI) and Co-PI. Furthermore, Dr. Fu has held positions such as Track Chair, Workshop Chair, Tutorial Leading Speaker, and Technical Program Committee Member for various international conferences including IEEE ICC, WCNC, VTC, and GLOBECOM.

Yongna Guo (KTH Royal Institute of Technology, Sweden)

Yongna Guo received the Ph.D. degree in Electrical Engineering from the City University of Hong Kong in 2023. She received the B.S. and M.S. degrees in Information and Communication Engineering from the Harbin Institute of Technology, China. She is currently a postdoc with the KTH Royal Institute of Technology. Her research interests include learning and optimization in edge computing and resource allocation in wireless networks. Dr. Guo was a recipient of the 2024 IEEE GLOBECOM Best Paper Award.

Yan Zhang (University of Oslo, Norway)

Yan Zhang is currently a Full Professor with the Department of Informatics, University of Oslo, Norway. He received the Ph.D. degree from the School of Electrical and Electronics Engineering, Nanyang Technological University, Singapore. His research interests include next-generation wireless networks leading to 6G, green and secure cyber-physical systems. Dr. Zhang is an Editor (or Area Editor, Senior Editor, Associate Editor) for several IEEE transactions/magazine. Since 2018, Prof. Zhang was a recipient of the global ``Highly Cited Researcher” Award (Web of Science top 1\% most cited worldwide). He is Fellow of IEEE, Fellow of IET, elected member of Academia Europaea (MAE), elected member of the Royal Norwegian Society of Sciences and Letters (DKNVS), and elected member of Norwegian Academy of Technological Sciences (NTVA).

Tony Q. S. Quek (Singapore University of Technology and Design, Singapore)

Bio coming soon.

T28: Localization-of-Things for Next-Generation Networks

Location: 512 H

Speakers: Moe Z. Win (Massachusetts Institute of Technology, USA); Andrea Conti (DE and CNIT, University of Ferrara, Italy)

Abstract: The availability of real-time and precise location awareness is essential for current and future wireless applications, particularly those involving Internet-of-Things and next-generation networks (beyond 5G toward 6G). The coming years will see the emergence of network localization and navigation in challenging wireless environments with sub-meter accuracy, low latency, and minimal infrastructure requirements. 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 variety of applications including connected communities, smart environments, vehicle autonomy, asset tracking, medical services, military systems, and crowd sensing. As the ability to localize devices in wireless networks becomes increasingly important, it is necessary to be aware of both the fundamentals and the state of the art in location-aware networks.

We will discuss the limitations of traditional positioning and move on to the key enablers for high-accuracy location awareness. Topics covered will include: theoretical foundations, machine-learning based algorithms, network experimentation, and performance in 3GPP standardized scenarios for 5G and beyond networks. Theoretical foundations provide performance benchmarks and blueprints for network design. Machine-learning based algorithms exploiting soft information (SI), instead of single value estimates of time and angle, are a way to achieve dramatic performance improvements compared to existing techniques. 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 performance gain in next-generation networks toward 6G.

Bios

Moe Z. Win (Massachusetts Institute of Technology, USA)

Moe Z. Win is the Robert R. Taylor 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. 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 Frank E. Perkins Award, 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.

Andrea Conti (DE and CNIT, University of Ferrara, Italy)

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.

Tutorials

SUNDAY, 08 JUNE, 9:00 AM - 12:30 PM:

SUNDAY, 08 JUNE, 2:00 PM - 5:30 PM:

THURSDAY, 12 JUNE, 9:00 AM - 12:30 PM:

THURSDAY, 12 JUNE, 2:00 PM - 5:30 PM:

Details

SUNDAY JUNE 08 - MORNING SESSION (9:00 - 12:30)

TUT-01: Generative Foundation Models (GFMs) For NextG Communication Networks: Fundamentals, Key Techniques, and Future Directions

TUT-02: The Interplay between Quantum Computing and Reinforcement Learning

TUT-03: Next Generation Multiple Access for 6G: Opportunities and Challenges

TUT-04: Reconfigurable Holographic Surfaces Enabled Communications and Sensing for 6G

TUT-05: Distributed Vision Analytics for Immersive 6G Time-Sensitive Systems

TUT-06: Theoretical Foundations for Ubiquitous Connectivity, Intelligence, and Security in the 6G Era and Beyond

TUT-07: Building Foundation Models and Generalizable AI in 6G: From Theory to Practice

SUNDAY JUNE 08 - AFTERNOON SESSION (13:30 - 17:30)

TUT-08: Generalizability and Interpretability of Deep Learning Models for Next-Generation (xG) Wireless Communications: A Tutorial

TUT-09: Advancing Optical Communication: Visible Light Communication and Multi-Layer Airborne Backhaul Networks

TUT-10: Multi-carrier Waveforms and Channel State Information for 6G

TUT-11: Fluid Antenna System (FAS): Fundamentals and Recent Advances

TUT-12: Distributed Integrated Sensing and Communications: Foundations, Opportunities, and Challenges

TUT-13: Integrated Security, Privacy, and Trust Provisioning for Effective Collaboration in 6G-Enabled Systems

TUT-14: Integrated and intelligent Connectivity for 6G and Beyond: Latest Advances & the Road Ahead

THURSDAY, JUNE 12- MORNING SESSION (9:00 - 12:30)

T15: At the Dawn of 6GenAI: Generative Models and Multi-Modal LLMs for 6G Wireless Intelligence

T16: Optical Wireless Communication: From Fundamentals to Future Directions

T17: B5G/6G Network Slicing for V2X Services: Technics, Standards, and Challenges

TUT-18: Six-Dimensional Movable Antenna for 6G: Opportunities and Challenges

T19: Signal Processing Techniques for 6G Sensing: Recent Progress and Future Directions

T20: From 1 to 100: Standardization in the Communications Industry

T21: QoS-Driven Digital Twins Over 6G Mobile Wireless Networks

THURSDAY, 12 JUNE - AFTERNOON SESSION (14:00 - 17:30)

T22: Machine Learning for 6G Wireless Networks: Latest Advances, Fundamentals, and Applications

T23: Sustainable Agriculture Productivity with IoT, AI, and Blockchain Through Advanced Networking

T24: Delay-Doppler Domain Multi-Carrier Modulation for NextG Communications

T25: Channel Estimation, Interpolation and Extrapolation in Doubly-dispersive Channels

T26: Towards 6G and B6G Communications: Wireless Channel Measurements, Characteristics Analysis, and Modeling

T27: Digital Twin Edge Networks for 6G: architectures, efficiency and future perspectives

T28: Localization-of-Things for Next-Generation Networks

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