Intelligent wireless communications and high-accuracy positioning systems
About the project
It indeed consists of two sub-projects. Firstly, as the most promising technology in achieving 10 Gbs peak data rates, millimetre-wave (mmWave) communications have received remarkable attention from both academia and industry. Thus, in the project of intelligent wireless communications, we aim to develop several machine learning-based beam tracking algorithms for mobile mmWave communications, which can work efficiently without relying on a priori knowledge of the channel dynamics. While in the project of high-accuracy positioning systems, we aim to leverage mmWave signals along with other techniques such as intelligent reflecting surface to achieve centimetre-level localization accuracy.
Driven by the ever-increasing mobile data traffic, 5G-and-beyond (B5G) networks are envisioned as a key enabler to support a variety of novel use cases, such as autonomous cars, industrial automation, multisensory extended reality (XR), e-health, etc. Considering the emergence of these use cases and the more and more complicated network structure, artificial intelligence is expected to be essential to assist in making the B5G version conceivable.
With regard to high-accuracy localization, it will play a critical role in almost all use cases of the B5G networks. Specifically, for smart factory applications, depending on the usage scenarios, the requirement for localization accuracy ranges from 1 cm to 10 cm. However, most current localization services can at best achieve meter-level localization accuracy, and therefore cannot meet the centimetre-level localization accuracy requirements of the emerging use cases in the B5G era, which emphasizes the need for more advanced localization techniques.
About the Digital Futures Postdoc Fellow
Deyou Zhang is a Digital Futures Postdoc at the School of Electrical Engineering and Computer Science of KTH, supervised by Dr Ming Xiao, Prof. Lihui Wang, and Dr Zhibo Pang. Before joining KTH, he obtained his PhD degree at the University of Sydney, Australia. His research interests include millimetre-wave communications, intelligent reflecting surfaces, and wireless federated learning.
Ming Xiao, Associate Professor, Division of ISE, EECS School, KTH
Zhibo Pang, Senior Principal Scientist, Department of Automation Technology, ABB Corporate Research Sweden and Adjunct Professor, Department of Intelligent Systems, EECS, KTH
Lihui Wang, Professor and Chair of Sustainable Manufacturing, KTH
PhD degree from the University of Sydney, Australia, Digital Futures Postdoctoral Fellowdeyou@kth.se
Associate Professor, Division of ISE at KTH EECS, Supervisor for Postdoc project Intelligent wireless communications and high-accuracy positioning systems, Working group Learn, Digital Futures Faculty+46 8 790 65 77
Senior Principal Scientist, Department of Automation Technology, ABB Corporate Research Sweden, Adjunct Professor, Department of Intelligent Systems, EECS, KTHzhibo@kth.se
Professor and Chair of Sustainable Manufacturing at KTH, Co-supervisor for Postdoc project Intelligent wireless communications and high-accuracy positioning systems, Co-PI of research project Towards Safe Smart Construction: Algorithms, Digital Twins and Infrastructures, Digital Futures Facultylihuiw@kth.se