Since 2008 from
AWAT, NCKU
The Radio Access Network (RAN) in cellular systems provides wireless connections to individual user equipment (UE) or machines. As the key component of cellular systems, RAN handles numerous tasks, such as signal processing, interference mitigation, and resource allocation. The joint optimization of all these tasks can offer the best user experience but the complexity is extremely high. In 6G, it is foreseen that more diverse use cases will be supported that dramatically complicates the optimization and operation of RAN. Recent advances on Artificial Intelligence (AI)/Machine Learning (ML) can be of great help to enable exciting 6G applications through intelligentizing RAN. Our group looks at potential AI/ML solutions to make smart RAN possible for 6G.
Multi-access mobile edge computing (MEC) allows users/devices to offload computational-heavy tasks, such as training for machine learning models, mobile Augmented Reality (AR)/Virtual Reality (VR), and so on, to the servers installed at the edge of wireless networks. Due to limited radio spectrum, offloading a large volume of data from many users/devices to the edge serves is challenging using existing wireless technologies. Our group is interesting in studying advanced technologies to support MEC.
RIS is a meta-surface consisting of a large number of low-cost passive reflecting elements. The phase of each element can be electronically controlled to reflect the radio signals in a controllable manner. In this way, RIS opens the opportunity of smartly improving the radio propagation particularly when a direct communication link is not available. In order to make a good use of RIS, the reflecting phases for RIS elements need to be tuned properly, resulting in high complexity and overhead. Our group has developed low-complexity and robust approaches to configure RIS in real time.
Energy harvesting (EH) is an emerging technique that captures energy from external sources, e.g., thermal energy, solar radiation, changes in magnetic field, and radio-frequency (RF). By charging from ambient sources, low-power electronics can operate without frequent battery replacement. It is expected that EH technique will be the key enabler of internet of things (IoT) for ubiquitous environment monitoring and smart factories. The main challenge of EH is that the harvested energy is much weaker than the required energy for operating IoT devices. Our group focuses on designing novel communications strategies to support zero energy air interfaces.
2021/8-至今
國立清華大學電機工程系教授
2017/8-2021/8
國立成功大學電機工程系教授
2013/8-2017/7
國立成功大學電機工程系副教授
2008/8-2013/8
國立成功大學電機工程系助理教授
2008/5-2008/6
加拿大滑鐵盧大學電機系博士後
2004/1-2008/4
加拿大滑鐵盧大學電機博士
1998-2000
國立中興大學電機碩士
1998-2000
台灣西門子吉悌電信研發工程師
2018
科技部優秀年輕學者研究計畫
2017
成功大學教學傑出教師獎
2015
WOCC 最佳論文獎
2015
IEEE Tainan Section Best GOLD Member Award
2014
成功大學電資學院教學優良教師獎
2010
IEEE WCNC 最佳論文獎
2005-2007
加拿大滑鐵盧大學 傑出研究生獎學金
2004-2007
加拿大滑鐵盧大學 國際研究生獎學金
無線接取技術
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