W3 – 2nd Workshop on AI-Driven Connectivity for Vehicular and Wireless Networks

Honorable Chair: Hiroki Esaki, The University of Tokyo, Japan
Honorable Chair: Tarik Taleb, Ruhr University Bochum, Germany

Co-organizer’s: Tommaso Melodia, Northeastern University, USA
Co-organizer’s: Rui Dinis, University Lisbon, Portugal
Co-organizer’s: Celimuge Wu, The University of Electro-Communications, Japan
Co-organizer’s: Francesca Cuomo, Sapienza University of Rome, Italy
Co-organizer’s: Jin Nakazato, Tokyo University of Science, Japan

Publicity Chair: Kazuki Maruta, Tokyo University of Science, Japan

Keynote Speaker: Jakob Hoydid, Research Scientist, NVIDIA
Keynote Speaker: Megumi Kaneko, Professor, University of Tokyo

Program:

Date: 9 June 2026
Time: 09:00 – 17:30
Room: Nicea

08:50~09:00                         Opening Address: Prof. Rui Dinis, Instituto de Telecomunicações, Nova University Lisbon

09:00-10:30                          Technical Paper I: 5 Papers

10:30-11:00                          Coffee Break

11:00-11:50                          Keynote I: Prof. Megumi Kaneko, University of Tokyo

11:50-12:44                          Technical Paper II: 3 Papers

12:44-14:00                          Lunch

14:00-14:50                      Keynote II: Dr. Jakob Hoydid, Research Scientist, NVIDIA

14:50-15:26                      Technical Paper III: 2 Papers

15:30-16:00                      Coffee Break

16:00-18:06                      Technical Paper IV: 7 Papers

18:06-18:15                      Closing   Prof. Jin Nakazato, Tokyo University of Science

Note: Each presenter has 15mins presentation and 3 mins Q&A

Technical Paper I: 5 Papers

1. Characterizing the Computational Feasibility of AI Video Analytics Across Edge, Fog, and MEC in Urban ITS
2. TinyML-Enabled Priority-Aware V2X Communication for Fog–Edge Emergency Vehicles
3. A Dynamic Caching Method for Named Data Networking in Vehicular Ad Hoc Networks
4. Diffusion-Based Covert Semantic Communication over Time-Varying Channels
5. Propagation Delay-Based Localization for mmWave Distributed MIMO Systems in Multipath Environments

Technical Paper II: 3 Papers

6. Dynamic Channel Prediction Method Based on Multi-Scale Transformer
7. UE Count Forecasting via Transformer-Based Mobility Decomposition and Cross-Cell Propagation Modeling
8. AI-Driven Multi-Layer Federated Split Learning for Hardware-Impaired Multi-Cell 6G Edge Networks with Dynamic zCDP\

Technical Paper III: 2 Papers

9. Fast Weight Derivation for Phase-Controlled Massive MIMO Null-Space Expansion with Analog Beamforming
10. Null-Space Expansion for OTFS-Based Downlink MU-MIMO Transmission

Technical Paper IV: 7 Papers

11. UAV Flight Trajectory Planning for Wireless Power Transfer Using Cooperative Beamforming
12. UAV Trajectory Planning Based on Centroids of Ground Device Positions for SAGIN
13. Experimental Evaluation of High-Frame-Rate OCC Using Clock Offsets in Image Sensor Arrays
14. Deep Reinforcement Learning-based MLO Traffic Allocation for OFDMA Transmission in IEEE 802.11be Networks
15. Comparative Study of High-Speed Ising Machines for Optimization to Wireless Resource Allocation Problems
16. SNR-Adaptive Optimal Threshold Design for Energy Detection in Dynamic Spectrum Access
17. Estimating Timing Advance for Sub-THz Distributed Systems from Sub-10 GHz CSI9. Fast Weight Derivation for Phase-Controlled Massive MIMO Null-Space Expansion with Analog Beamforming

– End – 

Abstract: As the 6G era approaches, integrating AI into Vehicular and Wireless Access Networks (AI-VWAN) is expected to revolutionize network performance through improved efficiency, adaptability, and intelligence. This workshop focuses on addressing key challenges such as optimizing limited resources like energy and spectrum, essential for sustainable and high-performing 6G networks. It will explore AI applications in frameworks like Open RAN and LoRAWAN, highlighting AI’s role in resource allocation, network interoperability, and adaptive decision-making across diverse deployment scenarios. The workshop aims to bridge theory and practice by fostering collaboration among researchers, industry professionals, and technologists through discussions on cutting-edge AI techniques, including reinforcement learning and federated learning. By addressing resource management and performance optimization, the event seeks to advance sustainable and intelligent 6G networks, enabling AI and RAN to work seamlessly to meet future connectivity demands.

Topics of interest include, but are not limited to:
•⁠  ⁠6G (e.g.,  ISAC, Quantum Computing, etc.)
•⁠  ⁠AI-based V2X
•⁠  ⁠Vehicular and Wireless Access Network
•⁠  ⁠Open RAN, O-RAN
•⁠  ⁠LoRAWAN
•⁠  ⁠Mobility Network (e.g., UAV, QoS/QoE handover management, NLoS avoidance, wireless power transmitter)
•⁠  ⁠Digital Twin

 

Keynote bios:

Jakob Hoydis is a Distinguished Research Scientist at NVIDIA working on the intersection of machine learning and wireless communications. Prior to this, he was Head of a research department at Nokia Bell Labs, France, and co-founder of the social network SPRAED. He obtained the diploma degree in electrical engineering from RWTH Aachen University, Germany, and the Ph.D. degree from Supéléc, France. From 2019-2021, he was chair of the IEEE COMSOC Emerging Technology Initiative on Machine Learning as well as Editor of the IEEE Transactions on Wireless Communications.

He is recipient of the 2019 VTG IDE Johann-Philipp-Reis Prize, the 2019 IEEE SEE Glavieux Prize, the 2018 IEEE Marconi Prize Paper Award, the 2015 IEEE Leonard G. Abraham Prize, the IEEE WCNC 2014 Best Paper Award, the 2013 VDE ITG Förderpreis Award, and the 2012 Publication Prize of the Supéléc Foundation. He has received the 2018 Nokia AI Innovation Award, as well as the 2018 and 2019 Nokia France Top Inventor Awards. He is a co-author of the textbook “Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency” (2017). He is a 2023 Distinguished Industry Speaker of the IEEE Signal Processing Society as well as an IEEE Fellow.

He is one of the maintainers and core developers of Sionna, a GPU-accelerated open-source link-level simulator for next-generation communication systems.

 

Megumi Kaneko received her Diplôme d’Ingénieur from Télécom SudParis, Institut Polytechnique de Paris, France, in 2004, jointly with a MSc. degree from Aalborg University, Denmark, where she received her Ph.D. degree in 2007. In May 2017, she obtained her HDR degree (French Doctoral Habilitation for Directing Researches at Professor position) from Paris-Saclay University, France. She was a JSPS post-doctoral fellow at Kyoto University (2008-2010), an Assistant Professor in the Department of Systems Science, Graduate School of Informatics, Kyoto University (2010-2016), and an Associate Professor at the National Institute of Informatics (NII) as well as the Graduate University for Advanced Studies (Sokendai), Tokyo, Japan (2016-2024). Since 2024, she has been a Professor at NII and at the Department of Computer Science, The University of Tokyo. Her research interests include wireless networks, energy efficiency and Edge AI for wireless communications and sensing. She serves as an Executive Editorial Committee (EEC) member of IEEE Transactions on Wireless Communications, as a Senior Editor of IEEE Communications Letters, and as an Associate Editor of IEEE Wireless Communications Letters. She is a member of the Advisory Board for Promoting Science and Technology Diplomacy at the Ministry of Foreign Affairs of Japan. She has received the IEEE Globecom 2009 Best Paper Award, the 2011 Funai Young Researcher’s Award, the WPMC 2011 Best Paper Award, the 2012 Telecom System Technology Award, the 2019 Young Scientist Prize from the Minister of Education, Culture, Sports, Science and Technology (MEXT) of Japan, the 2020 IEEE Communications Letters Exemplary Editor Award, the 2021 KDDI Foundation Contributions Award, and the 2025 JSPS Prize. She is a Senior Member of IEEE.

 

Co-organizer’s Bios:

Tommaso Melodia:

Tommaso Melodia is the William Lincoln Smith Chair Professor with the Department of Electrical and Computer Engineering at Northeastern University in Boston. He is also the Founding Director of the Institute for the Wireless Internet of Things and the Director of Research for the PAWR Project Office. He received his Laurea (integrated BS and MS) from the University of Rome – La Sapienza and his Ph.D. in Electrical and Computer Engineering from the Georgia Institute of Technology in 2007. He is an IEEE Fellow and recipient of the National Science Foundation CAREER award. He was named a College of Engineering Faculty Fellow in 2017 and received the Søren Buus Outstanding Research Award in 2018 – the highest research award in the College of Engineering at Northeastern University. Prof. Melodia has served as Associate Editor fo IEEE Transactions on Wireless Communications, IEEE Transactions on Mobile Computing, Elsevier Computer Networks, among others. He has served as Technical Program Committee Chair for IEEE Infocom 2018, General Chair for IEEE SECON 2019, ACM Nanocom 2019, and ACM WUWnet 2014. Prof. Melodia is the Director of Research for the Platforms for Advanced Wireless Research (PAWR) Project Office, a $100M public-private partnership to establish 4 city-scale platforms for wireless research to advance the US wireless ecosystem in years to come. The PAWR Project Office is co lead by Northeastern University and US Ignite and is overseeing the overall deployment and operation of the PAWR Program. Prof. Melodia’s research on modeling, optimization, and experimental evaluation of Internet-of-Things and wireless networked systems has been funded by the National Science Foundation, the Air Force Research Laboratory the Office of Naval Research, DARPA, and the Army Research Laboratory.

Rui Dinis:

Rui Dinis received the Ph.D. degree from the Instituto Superior Técnico (IST), Technical University of Lisbon, Portugal, in 2001, and the Habilitation degree in telecommunications from the Faculdade
de Ciências e Tecnologia (FCT), Nova University of Lisbon, in 2010. He was a Researcher with the Centro de Análise e Processamentode Sinal (CAPS), IST, from 1992 to 2005, and a Researcher
with the Instituto de Sistemas e Robótica (ISR), from 2005 to 2008. In 2003, he was an Invited Professor with Carleton University, Ottawa, Canada. Since 2009, he has been a Researcher with the Instituto de Telecomunicações (IT). He is currently an Full Professor with the FCT, Nova University of Lisbon. His main research activities are on modulation and transmitter design, nonlinear effects on digital communications and receiver design (detection, equalization, channel estimation and carrier synchronization), with emphasis on frequency domain implementations, namely for MIMO systems and/or OFDM and SC-FDE modulations. He is also working on cross-layer design and optimization involving PHY, MAC, and LLC issues, and positioning-assisted communications. He is or was with the Organizing Committee of multiple IEEE conferences, including several VTC and GLOBECOM. He is also the President of VTS Portugal Chapter, since 2016 and a member of several technical committees of the IEEE Communications Society. He is an Editor of IEEE Transactions on Wireless Communications, Open Journal on Communications, IEEE Transactions on Communications, IEEE Transactions on Vehicular Technology and Physical Communication (Elsevier).

Celimuge Wu: 

Celimuge Wu received his PhD degree from The University of Electro-Communications, Japan. He is currently a professor and the director of Meta-Networking Research Center, The University of
Electro-Communications. His research interests include Vehicular Networks, Edge Computing, IoT, and AI for Wireless Networking and Computing. He serves as an associate editor of IEEE Transactions on Networking, IEEE Transactions on Cognitive Communications and Networking, IEEE Transactions on Network Science and Engineering, and IEEE Transactions on Green
Communications and Networking. He is Vice Chair (Asia Pacific) of IEEE Technical Committee on Big Data (TCBD). He is a recipient of 2021 IEEE Communications Society Outstanding Paper Award, 2021 IEEE Internet of Things Journal Best Paper Award, IEEE Computer Society 2020 Best Paper Award and IEEE Computer Society 2019 Best Paper Award Runner-Up. He is an IEEE Vehicular Technology Society Distinguished Lecturer. He is a Fellow of Asia-Pacific Artificial Intelligence Association (AAIA).

Francesca Cuomo:

FRANCESCA CUOMO received the Ph.D. in Information and Communications Engineering in 1998 from Sapienza University of Rome. From 2005 to October 2020 she was Associate Professor and
from November 2020 she joined “Sapienza” as Full Professor teaching courses in Telecommunication Networks. Prof. Cuomo has advised numerous master students in computer in computer engineering, and has been the advisor of 11 PhD students in Networking. From November 2021 she is the Chair of the Master’s Degree in Data Science of Sapienza. Her current research interests focus on: Vehicular networks and Sensor networks, Low Power Wide Area Networks and IoT, 5G Networks, Multimedia Networking, Energy saving in the Internet and in the wireless system. She has participated in several National and European projects on wireless network systems such as the RAMON, VICOM, INSYEME, IST WHYLESS, IST EPERSPACE, IST CRUISE, H2020 symbIoTe, H2020 Elegant. She has authored over 156 peer-reviewed papers published in prominent international journals and conferences.

Jin Nakazato: