Scopes and Topics:
Previous and current wireless systems were designed based on the postulate that the wireless propagation environment is uncontrollable that may impair the signal quality due to the unwanted reflections and refractions, and deleterious interference. Various physical layer (PHY) techniques (such as modulation, channel coding and beamforming) have been developed that passively adapt to the environment. It is undeniable that a certain level of saturation has been reached in terms of various performance metrics. Consequently, the current existing PHY techniques may not be able to meet the requirements of future wireless networks, which are envisioned to support the upcoming applications, i.e., multisensory augmented and virtual reality applications, wireless brain computer interactions due to their huge demand on high data rate, ultra-low latency and ultra-high reliability. Instead, significant performance gains are anticipated to be achieved when treating the wireless propagation environment as additional variable to be optimized. There is a need for a technology that can transform the stochastic and uncontrollable wireless propagation environment into a stable, reliable, and efficient communication system entity. This is made possible thanks the recent advent of Reconfigurable Intelligent Surface (RIS), also known as intelligent reflection surface (IRS) and large intelligent surface (LIS), which enables the proactive control of the amplitude and phase shift of the radio wave impinging on it by overcoming the inherent drawback of wireless environment.
This workshop aims for bringing together academic and industrial researchers to share the recent breakthroughs related to RIS and discuss the major technical challenges arising in RIS-aided networks. The topic of interest include, but not limited to
- Channel estimation for RIS-aided wireless networks
- Channel modeling for RIS-aided wireless networks
- Robust transmission design for RIS-aided networks with imperfect/partial CSI
- Theoretical performance analysis for RIS -aided networks
- Transceiver design and optimization for RIS-aided networks
- Deployment optimization for RIS-aided networks
- Cross-layer design for RIS-aided communications
- Radio localization and sensing with RISs
- Application of RIS in high-frequency communications, such as mmWave/Terahertz communication and visible light communication
- AI-empowered RIS-aided communication systems
- Testbeds, experimental measurements in RIS-aided wireless communications
- Integration of RIS into emerging wireless communication applications such as massive MIMO, wireless power transfer, mobile edge computing, physical layer security, unmanned aerial vehicle communications, NOMA, cognitive radio, etc
Workshop Organizers:
Workshop Organizers
Cunhua Pan (lead), Queen Mary University of London, UK, c.pan@qmul.ac.uk
Qingqing Wu, University of Macau, Macao, qingqingwu@um.edu.mo
Marco Di Renzo, Universit´e Paris-Saclay, France, marco.di.renzo@gmail.com
Yuanwei Liu, Queen Mary University of London, UK, yuanwei.liu@qmul.ac.uk
Ertugrul Basar, Koç University, Turkey, ebasar@ku.edu.tr
Shi Jin, Southeast University, China, jinshi@seu.edu.cn
Chau Yuen, Singapore University of Technology and Design, Singapore, yuenchau@sutd.edu.sg
Derrick Wing Kwan Ng, University of New South Wales, Sydney, Australia, w.k.ng@unsw.edu.au
Steering Committee Members
Lajos Hanzo, University of Southamption, UK
Lee Swindlehurst, University of California at Irvine, USA
Ying-Chang Liang, University of Electronic Science and Technology of China, China
Jinhong Yuan, University of New South Wales, Australia
Sumei Sun, Institute for Infocomm Research, Singapore
Robert Schober, Friedrich-Alexander University of Erlangen-Nuremberg, Germany
Important Dates:
paper submission deadline: June 10 June 20 (firm deadline)
notification of acceptance: July 10