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AI RAN and 6G: An Open Source Perspective
Time : July 2nd (WED.) 09:55-10:20
Speaker : Ray-Guang Cheng(Distinguished Professor, Director of Computer Center, National Taiwan University of Science and Technology)
Abstract :
This talk explores how open-source platforms are accelerating the development of AI-native RAN and paving the way for 6G. It highlights recent standardization efforts from 3GPP and the O-RAN ALLIANCE, as well as the current status of open-source communities, including the O-RAN Software Community (OSC) and OpenAirInterface (OAI). The showcase also features practical work from the OSC Asia Pacific Lab, utilizing both open source and commercial products. The talk concludes by elaborating on the importance of open collaboration in bridging research, implementation, and deployment of intelligent RAN systems.
Ray-Guang Cheng
Ray-Guang Cheng received the B.E., M.E., and Ph.D. degrees in communication engineering from the National Chiao-Tung University, Hsinchu, Taiwan, in 1991, 1993, and 1996, respectively. He led the 3G Protocol Project Computer and Communication Laboratories, Advanced Technology Center, Industrial Technology Research Institute (ITRI), Hsinchu, from 1997 to 2000; and join BenQ Mobile System Inc., Hsinchu as the Senior Manager from 2000 to 2003. He is currently a Director of the Computer Center and a Distinguished Professor at the Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology (NTUST), Taipei, Taiwan. He holds 18 U.S. patents; and has published more than 30 IEEE/3GPP standard contributions. He has been the Head of the Joint NTUST-EURECOM Open5G Lab since 2019 and the Head of the OSC Asia Pacific Lab since 2022.
Network Evolution Towards 6G
Time : July 2nd (Wed.) 13:40-14:05
Speaker : Chi-Yu Li (Professor, Computer Science Department, National Yang Ming Chiao Tung University)
Abstract :
The evolution from 5G to 6G marks a transformative journey in mobile networking, driven by changes in architecture, intelligence, and system integration. 5G has introduced key enablers such as network slicing, service-based architecture, and edge computing, allowing networks to support diverse services including enhanced mobile broadband (eMBB), ultra-reliable low-latency communication (URLLC), and massive machine-type communication (mMTC). It has also initiated a shift toward open and programmable infrastructures, breaking away from traditional closed mobile systems. This openness has invited non-traditional cellular vendors into the ecosystem, catalyzing the development of new core network solutions and Open RAN (O-RAN) technologies.
As we look toward 6G, the vision expands to a globally connected, intelligent fabric that unifies terrestrial, aerial, and satellite networks. New paradigms such as joint sensing-communication, as well as emerging applications like digital twins, are expected to drive the next wave of innovation. Realizing this vision will demand rethinking network functions, enhancing architectural modularity, and addressing critical challenges from various aspects. This talk will examine the key drivers and technological milestones from 5G to 6G, highlight global research trends, and share our contributions and future directions in advancing the next generation of mobile networks.
Chi-Yu Li
Dr. Chi-Yu Li is a Professor in the Department of Computer Science at National Yang Ming Chiao Tung University (NYCU), where he also serves as the Deputy Director of the IT Center. He received his Ph.D. in Computer Science from the University of California, Los Angeles (UCLA) in 2015. Dr. Li’s research interests span wireless networking, network security, and edge AI. He has published extensively in top-tier conferences in the fields of networking and cybersecurity, including ACM MobiCom, IEEE INFOCOM, and ACM CCS. His work has been recognized with numerous honors and awards, such as the ACM SIGMOBILE Research Highlights (2023, 2025), the Y. Z. Hsu Technology Invention Award (2022), the K. T. Li Cornerstone Award (2022), the Best Community Paper Award Runner-Up at ACM MobiCom 2022, and the Best Paper Award at IEEE CNS 2018. He has also received NSTC FutureTech Awards for three consecutive years (2020-2022) and NSTC Young Scholar Research Grants in 2017, 2020, and 2023.
Toward 6G: AI/ML Platform for AI-RAN
Time : July 2nd (Wed.) 14:05-14:30
Speaker : Jenq-Shiou Leu (Dean, College of Electrical Engineering and Computer Science(EECS), NTUST, Professor, Department of Electronic and Computer Engineering(ECE), NTUST)
Abstract :
In the Toward 6G vision, wireless access networks (RAN) need stronger support from AI and machine learning (AI/ML). An AI/ML platform with model management and MLOps features is essential for improving the performance and reliability of RAN AI applications.
However, building the pipelines required for AI/ML workflows is often challenging and prone to errors. This has become a key barrier to scaling up and increasing the efficiency of AI applications.
To solve this problem, our platform provides tools that help users build and check pipelines more quickly and accurately.
These features make it easier to manage tasks like model training, deployment, and configuration for RAN AI applications, which improves overall work efficiency.
As a result, this AI/ML platform can effectively address the difficulties of deploying AI workflows and offers a practical solution for advancing AI-driven RAN development in the 6G era.
Jenq-Shiou Leu
Jenq-Shiou Leu received his B.S. in mathematics and M.S. in computer science from National Taiwan University in 1991 and 1993. He earned his Ph.D. in computer science from National Tsing Hua University in 2006. He worked in the telecommunication industry until 2007. In 2007, he joined NTUST as an Assistant Professor, becoming an Associate Professor from 2011 to 2014 and a Professor since 2014. He served as the Department of ECE Chairperson from 2017 to 2020 and NTUST Secretary General from 2021 to 2024. Since 2024, he has been the Dean of CEECS at NTUST. His research interests include Heterogeneous Network Integration, Mobile Service and Platform Design, Distributed Computing, and Green and Orange Technology Integration. He has published extensively with 116 SCI-indexed journal papers and 77 international conference papers. He is a senior member of IEEE.
100 GHz 4D Radar Using Heterogeneous Integration Techniques
Time : July 2nd (Wed.) 16:30-16:55
Speaker : Zuo-Min Tsai (Professor, Institute of Communications Engineering, National Yang Ming Chiao Tung University)
Abstract :
A 4D radar using heterogeneous integration techniques is introduced. This 4D radar integrates CMOS, Glass, GaN, and PCB process to achieve high quality radar performance. Using CMOS and low loss glass substrate, this radar have 8 transmitter and 8 receiver, and have 7 degree angle resolution. This radar has good distance resolution (< 1.5 cm) because of the wide bandwidth. The detection distance can achieve to 1.5 m. This radar is expected to detect not only 3D image of the object (distance, azimuth angle, and elevation angle but also vital sign of the object (breath, and heart beat).
Zuo-Min Tsai
Zuo-Min Tsai was born in Maioli, Taiwan, in 1979. He received his B.S. and Ph.D. degrees in Communication Engineering from the Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan, in 2001 and 2006, respectively. In 2019, he joined the insitute of communications Engineering, National Yang Ming Chiao Tung University, Taiwan, as a professor.
THz Electronics for Sensing and Communication Applications
Time : July 2nd (Wed.) 16:55-17:20
Speaker : Chun-Hsing Li (Professor, Department of Electrical Engineering, National Taiwan University, Taiwan)
Abstract :
THz science and technology have been considered potential candidates for the 6G wireless communication systems. THz electronics using CMOS technologies can provide low-cost and high-integration solutions, but face the challenges of low supply voltages and low-speed transistors. This talk will show our efforts to address the issues mentioned above from the device-level design up to the system-level demonstrations, including EM-optimized transistor layout for 302.5-GHz 30.9-dB amplifier design, a 340-GHz –4.4-dBm LO source supporting a 360° phase shifting range, a 324-to-360-GHz –6-dBm CMOS PLL, a THz heterogeneous integration platform, and a 240-GHz 12-Gbps I/Q transmitter.
Chun-Hsing Li
Chun-Hsing Li received the Ph.D. degree in electronics engineering from National Chiao Tung University, Hsinchu, Taiwan, in 2013. He is currently a Professor at the Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan. His research interests include the design of RF, millimeter-wave, and terahertz integrated circuits and systems. Dr. Li has been a member of the TC-21 Terahertz Technology and Applications Committee of the IEEE Microwave Theory and Technology Society since 2022. He was a recipient of the Exploration Research Award, Pan Wen Yuan Foundation 2023, the Excellence in Teaching Award, National Taiwan University 2023, the Academic Contribution Award, EECS College, National Taiwan University 2022, the Outstanding Youth Electrical Engineer Award from the Chinese Institute of Electrical Engineering 2022, and the Outstanding Young Scholar Award from the Taiwan IC Design Society 2020.
Recent Advances on AI-assisted Self-organizing Networks
Time : July 3rd (Thu.) 10:20-10:45
Speaker : Ming-Chun Lee (Associate Professor, Institute of Communications Engineering, National Yang Ming Chiao Tung University)
Abstract :
Over the past decades, wireless networks have evolved into highly complex systems. As a result, manual management of wireless networks has become increasingly impractical. To address this challenge, self-organizing networks (SONs) have emerged as a vital solution. Recently, advancements in AI technologies have further enhanced the effectiveness and efficiency of key SON functions. In this talk, we focus on two critical tasks within SONs: fault detection and fast deployment. We will begin by introducing the fundamental concepts underlying these tasks. Then, several advanced approaches that incorporate the AI techniques for fault detection and fast deployment are discussed.
Ming-Chun Lee
Ming-Chun Lee received the B.S. and M.S. degrees in Electrical and Computer Engineering from National Chiao Tung University, Hsinchu, Taiwan, in 2012 and 2014, respectively, and the PhD from the Ming Hsieh Department of Electrical Engineering at University of Southern California in 2020. From 2014 to 2016, he was a research assistant in Wireless Communications Lab in the Research Center for Information Technology Innovation, Academia Sinica, Taiwan. He is now the Associate Professor of Institute of Communications Engineering at National Yang Ming Chiao Tung University. He received USC Annenberg Fellowship from 2016 to 2020. He was awarded the exemplary reviewer of IEEE Transactions on Communications in 2019. He is an Editor of IEEE Transactions on Wireless Communications. His research interest includes signal processing, design, modeling, and analysis in wireless systems and networks. He is especially working on topics relevant to caching, computing, and communication in wireless networks and integrated sensing and communication systems in recent years.
End-User MIMO Evolution toward 6G
Time : July 3rd (Thu.) 13:40-14:05
Speaker : Chao-Kai Wen (Professor, Institute of Communications Engineering, National Sun Yat-sen University)
Abstract :
In 6G, the trend of transitioning from massive antenna elements to even more massive ones is continued. However, installing additional antennas in the limited space of user equipment (UE) is challenging, resulting in limited capacity scaling gain for end users, despite network side support for increasing numbers of antennas. To address this issue, we propose an end-user-centric collaborative MIMO (UE-CoMIMO) framework that groups several fixed or portable devices to provide a virtual abundance of antennas. This talk outlines how advanced L1 relays and conventional relays enable device collaboration to offer communication, localization, and sensing enhancements.
Chao-Kai Wen
Dr. Chao-Kai Wen, a professor at the National Sun Yat-sen University's Institute of Communication Engineering, is an IEEE Fellow and a Highly Cited Researcher by Clarivate Analytics. He served as the Director of the Institute of Communication Engineering at National Sun Yat-sen University from 2018 to 2021 and as the Vice Dean of the College of Engineering from 2020 to 2023. Prior to joining the university, he worked as an engineer at the Industrial Technology Research Institute (ITRI) and MediaTek (MTK) from 2004 to 2009.
Dr. Wen's primary research focus is on communication signal processing. He currently serves as an editor, associate editor, and guest editor for several IEEE journals. He has received multiple awards, including the 2016 GLOBECOM and 2022 ICC Best Paper Awards, the 2023 Jack Neubauer Memorial Award, and the Best Editor Award for both IEEE Wireless Communications Letters and IEEE Communications Letters.
Advancing 5G-Advanced and Paving the Way to 6G: Our 3GPP Contributions and Future Directions
Time : July 3rd (Thu.) 14:05-14:30
Speaker : Shin-Lin Shieh (Professor, Institute of Communications Engineering, National Tsing Hua University)
Abstract :
Our team is actively engaged in 3GPP standardization, focusing on three key areas toward 6G: Non-Terrestrial Networks (NTN), Integrated Sensing and Communication (ISAC), and AI/ML for the air interface.
In NTN, we contribute to uncoordinated access design for satellite-based IoT systems, targeting enhanced reliability and adaptability under diverse traffic and user conditions, with ongoing support from national projects and international collaboration.
For ISAC, we are developing a software-defined platform to integrate sensing and communication functions, enabling applications such as UAV detection through waveform design, sensing-data fusion, and interference mitigation.
In the AI/ML domain, our work explores feature extraction, data fusion, and model optimization to improve NG-RAN operation and air interface performance. These efforts are aligned with 3GPP's roadmap toward AI-native networks.
Together, our contributions aim to bridge theoretical research and system implementation, driving practical innovations and future standardization in the 6G era.
Shin-Lin Shieh
Shin-Lin Shieh received the B.Sc. and M.Sc. degrees in Electrical Engineering from National Tsing Hua University (NTHU), Hsinchu, Taiwan, in 1999 and 2001, respectively, and the Ph.D. degree from the Department of Communication Engineering, National Chiao Tung University in 2008.
He began his career at the Industrial Technology Research Institute (ITRI) in 2002, focusing on baseband communication algorithms, and later joined Sunplus Technology in 2005, contributing to the design of EDGE, WCDMA, HSDPA, and LTE baseband systems.
In 2010, he joined the Department of Communication Engineering at National Taipei University, where he served as Professor and Chair. Since 2024, he has been with the Department of Electrical Engineering at National Tsing Hua University as Professor. His current research interests include 5G/6G standardization, Non-Terrestrial Networks (NTN), Integrated Sensing and Communication (ISAC), and AI/ML for the air interface.
Multi-Functional and AI-Enhanced RIS/Antenna Design for 6G communication
Time : July 3rd (Thu.) 15:40-16:05
Speaker : Shih-Cheng Lin (Professor, Department of Electrical Engineering, National Chung Cheng University)
Abstract :
This presentation explores the advancement of Reconfigurable Intelligent Surface (RIS) and antenna technologies toward multi-functional capabilities and AI-enhanced design for next-generation wireless communication. Building upon our prior RIS development, we are extending RIS functionality beyond reflection to include absorption, transmission, and subarray architectures. These innovations offer greater adaptability for diverse deployment scenarios and system requirements. Additionally, we demonstrate how artificial intelligence and machine learning are leveraged to automatically generate antenna structures tailored to specific radiation patterns, significantly accelerating the design process and enabling highly optimized, performance-driven hardware. The adoption of AI/ML not only shortens development cycles but also introduces new design paradigms that are difficult to achieve through conventional approaches. Through these innovations, our goal is to develop scalable and intelligent RIS/antenna systems that are well-suited for the dynamic demands of 6G and beyond.
Shih-Cheng Lin
Lin Shih-Cheng (Member, IEEE) received the B.S. degree in electrical engineering from National Sun Yat-sen University, Kaohsiung, Taiwan, in 2003, and the Ph.D. degree in communication engineering from National Taiwan University, Taipei, Taiwan, in 2007. In 2007, he joined Taiwan Semiconductor Manufacturing Company, Hsinchu, Taiwan, as an RF-Modeling Engineer. In 2008, he joined Sunplus Technology Company Ltd., Hsinchu, as an Advanced Engineer. In 2009, he joined the Department of Electrical Engineering, National Chiayi University, Chiayi, Taiwan. Since 2020, he has been with the Department of Electrical Engineering, National Chung Cheng University, Chiayi, where he is currently a Professor. His research interests include the development and design of microwave passive components, RF/microwave integrated circuits, and phased-array antennas
Air-Interface Design for Life Cycle Management and Interoperability of AI/ML Models in Wireless Communication Systems
Time : July 3rd (Thu.) 16:05-16:30
Speaker : Chu-Hsiang Huang(Assistant Professor, National Taiwan University)
Abstract :
The performance improvement by adapting AI models in the communication systems is widely recognized by the research communities, and it leads to the standardization of air-interface design enabling wider and more efficient application of AI models in the communication system. During the standardization discussion, performance guarantee for AI models operating in different communication conditions/configurations is intensively studied. Model size limitation due to the storage and processing capability constraints of the mobile devices brings additional concerns of the generalizability of the AI models against the changing environments. Therefore, life cycle management (LCM) becomes essential for AI-model-based transceiver algorithms to manage model adaptation and updating based on different monitoring and statistical analysis functionalities, and guarantee the transceiver algorithm performance across various environments and configurations. When considering two-sided model, in which the AI models in BS and UE collaborate to implement the desired functionalities, interoperability across BS and UE side models is brought into the model management discussion. Since the AI models on the BS and the UE are interacting with each other, matching the AI models to ensure the correct execution of the designated functionalities becomes a new challenge when the AI models on the two sides are independently developed by different entities. In this talk, we provide an overview of 3GPP standardization progress on the general framework for LCM functionality development, and the preliminary air-interface design of functionalities like monitoring for specific use cases. In addition, we cover the interoperability perspective of model management focusing on two-sided model by going through the evaluations of specification-aided collaborative development process and verification/testing procedures. We conclude the talk by reviewing potential future directions of the LCM development and interoperable design from the air-interface specification perspective.
Chu-Hsiang Huang
Chu-Hsiang Huang received B.S. and M.S. degrees in Electrical Engineering from National Taiwan University, Taiwan in 2007 and 2009, respectively. and his Ph.D. degree in Electrical Engineering from University of California, Los Angeles in 2015. He is now with National Taiwan University (NTU) as an assistant professor. Before join NTU, he was working in Qualcomm Technologies, Inc. as a RAN working group delegate for 3GPP Standard Organization. Besides representing Qualcomm in 3GPP standard meetings, he was working on product development projects including multi-user interference mitigation, energy efficient receiver and demodulation algorithm for Qualcomm flagship modems as a senior staff engineer. He was a research assistant for NTU-INTEL research center in Taiwan in 2010. His research interest includes next generation wireless communication system design, communication system standardization, artificial intelligence and machine learning, statistical communication theory .
Qualcomm vision and priorities for 6G RAN
Time : July 3rd (Thu.) 16:30-16:55
Speaker : Yi Huang (Principal Engineer, Qualcomm Inc.)
Abstract :
Qualcomm view 6G as a generation of cellular ecosystem with improved spectrum efficiency, cost effective design and implementation, unified and streamlined air interface to support various of devices. In this presentation, various building blocks such as evolved LDPC, modulation shaping, Giga-MIMO, smarter antenna management, coverage native uplink design, AI native design, are introduced and integrated to achieve the above KPIs.
Yi Huang
Yi Huang received a Ph.D. in electrical engineering from University of California, Riverside in 2010. He worked for Qualcomm research center from 2010 to 2014 on LTE advanced UE receiver design. He worked for Qualcomm product department from 2014-2017 on modem design and implementation. Since 2017, he worked for Qualcomm standards department on 5G/6G research and standardization
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