KEYNOTE 1: Prof. Nei Kato
Title: Emerging WLANs Technology: Future Directions and Open Challenges
Abstract：
The 802.11 IEEE standard aims to update current Wireless Local Area Network (WLAN) standards to meet the high demands of future applications, such as 8K videos, augmented/virtual reality (AR/VR), the Internet of Things, telesurgery, and more. Two of the latest developments in WLAN technologies are IEEE 802.11be and 802.11ay, also known as Wi-Fi 7 and WiGig, respectively. These standards aim to provide Extremely High Throughput (EHT) and lower latencies. IEEE 802.11be includes new features such as 320 MHz bandwidth, multi-link operation, Multi-user Multi-Input Multi-Output (MIMO), orthogonal frequency-division multiple access, and Multiple-Access Point (multi-AP) cooperation (MAP-Co) to achieve EHT. With the increase in the number of overlapping Access Points (APs) and inter-AP interference, researchers have focused on studying MAP-Co approaches for coordinated transmission in IEEE 802.11be, making MAP-Co a key feature of future WLANs. Additionally, the high overlapping AP densities in EHF bands, due to their smaller coverage, must be addressed in future standards beyond IEEE 802.11ay, specifically with respect to the challenges of implementing MAP-Co over 60GHz bands. In this talk, the state-of-the-art in MAP-Co features and their drawbacks concerning emerging WLAN, several novel future directions and open challenges will be provided.
Bio:
Nei Kato is a full professor and the Dean with Graduate School of Information Sciences, Tohoku University. He has researched on computer networking, wireless mobile communications, satellite communications, ad hoc & sensor & mesh networks, UAV networks, AI, IoT, and Big Data. He is the Editor-in-Chief of IEEE Internet of Things Journal, the fellow committee chair of IEEE VTS. He is a Fellow of the Engineering Academy of Japan, a Fellow of IEEE, and a Fellow of IEICE.
KEYNOTE 2: Prof. Shiwen Mao
Title: AIGC for Wireless Data
Abstract：
There has been a surge on deep learning for wireless communications and networking. However, the performance of DL empowered wireless communications, networking, and sensing all depends on the availability of sufficient high-quality radio frequency (RF) data, which is more difficult and expensive to collect than other types. To overcome this obstacle, we proposal several AIGC approaches to generate synthetic RF data labeled with specified human activities for multiple wireless sensing platforms, such as WiFi, RFID, mmWave radar, including a conditional Recurrent Generative Adversarial Network (R-GAN) approach and diffusion model based approaches. The high quality of the generated RF data is validated two representative downstream tasks of human activity recognition (HAR), where the model trained with sufficient synthesized data outperforms the model trained by real data.
Bio:
Shiwen Mao (S’99-M’04-SM’09-F’19) is a Professor and Earle C. Williams Eminent Scholar, and Director of the Wireless Engineering Research and Education Center at Auburn University. Dr. Mao’s research interest includes wireless networks, multimedia communications, and smart grid. He is the editor-in-chief of IEEE Transactions on Cognitive Communications and Networking, ComSoc Technical Committee Board Director, and VP of Technical Activities of IEEE RFID Council. He received the 2023 SEC Faculty Achievement Award for Auburn, the NSF CAREER Award in 2010, and several service awards from IEEE ComSoc. He is a co-recipient of several best paper and demo awards from the IEEE.
KEYNOTE 3: Prof. Tony Q.S. Quek
Title: A Pathway towards Future Network Intelligence: RAN Intelligent Controller meets Digital Twin Networks
Abstract：
The RAN intelligent controller (RIC) is cloud native and a central component of an AI and virtualized RAN network. The RIC enables to deployment of machine learning and AI techniques to optimize resources and services in the RAN. Thus, it is an important component that brings intelligence, agility, and programmability to the radio access network. On the other hand, digital twin networks (DTW) are real-time replicas of physical networks. They are emerging as a powerful technology for design, diagnosis, simulation, what-if-analysis, and AI-driven real-time optimization and control of 6G wireless networks. In this talk, we will share our journey in building up AI RAN networks that allow us to bring together RIC and DTW to better understand how to design future wireless networks. Furthermore, we will also share Singapore’s first national Future Communications Research and Development Programme (FCP), which funds our work in this area.
Bio：
Tony Q.S. Quek received the B.E. and M.E. degrees in Electrical and Electronics Engineering from Tokyo Institute of Technology, respectively. At Massachusetts Institute of Technology, he earned the Ph.D. in Electrical Engineering and Computer Science. Currently, he is the Cheng Tsang Man Chair Professor with Singapore University of Technology and Design (SUTD) and ST Engineering Distinguished Professor. He also serves as the Head of ISTD Pillar, Director for Future Communications R&D Programme, Sector Lead for SUTD AI Program, and the Deputy Director of SUTD-ZJU IDEA. His current research topics include wireless communications and networking, 6G, network intelligence, non-terrestrial networks, and open radio access network.
Dr. Quek is currently serving as an Area Editor for the IEEE Transactions on Wireless Communications. He was an Executive Editorial Committee Member of the IEEE Transactions on Wireless Communications, an Editor of the IEEE Transactions on Communications, and an Editor of the IEEE Wireless Communications Letters. He received the 2008 Philip Yeo Prize for Outstanding Achievement in Research, the 2012 IEEE William R. Bennett Prize, the 2016 IEEE Signal Processing Society Young Author Best Paper Award, the 2017 CTTC Early Achievement Award, the 2017 IEEE ComSoc AP Outstanding Paper Award, the 2020 IEEE Communications Society Young Author Best Paper Award, the 2020 IEEE Stephen O. Rice Prize, the 2020 Nokia Visiting Professorship, and the the 2022 IEEE Signal Processing Society Best Paper Award. He is a Fellow of IEEE and a Fellow of the Academy of Engineering Singapore.