Enabling Reconfigurable Intelligent Surfaces (RIS) for 6G Cellular Networks

Dear Colleagues, 

The future of wireless communications looks exciting with potential new use cases and challenging requirements of future 6th generation (6G) wireless networks. Since the development of traditional wireless communications, the propagation medium has been perceived as a randomly behaving entity between the transmitter and the receiver, which degrades the quality of the received signal due to the uncontrollable interactions of the transmitted radio waves with the surrounding objects. The recent advent of reconfigurable intelligent surfaces (RIS) in wireless communications, on the other hand, enables network operators to control the radio waves (scattering, reflection, and refraction characteristics) to eliminate the negative effects of natural wireless propagation. Recent results have revealed that multiple antenna systems, unmanned aerial vehicles (UAVs), cognitive radio, non-orthogonal multiple access (NOMA), and physical layer security benefit from the RIS mechanism which can effectively provide effective and secure transmissions.

In fact, the research community of communications engineering must conduct extensive research to meet the above challenges. This Special Issue aims at bringing together academic researchers to introduce and share their recent works on the technical protocol and approaches to drawing recent advances of RIS-aided wireless networks and beyond communication networks. 

Potential topics include but are not limited to:

• Energy efficiency in RIS-aided networks;
• RIS-assisted UAV communications;
• Passive beamforming design in RIS-assisted systems;
• Physical layer security for RIS-aided networks;
• RIS-aided networks with signal detection and joint transceiver design;
• Low-complexity channel estimation in RIS-aided networks;
• RIS-aided networks for the Internet of Things (IoT);
• Non-orthogonal multiple access (NOMA) in RIS-assisted communications;
• Multiple-input multiple-output (MIMO) solutions in RIS-aided networks;
• Cognitive radio in RIS-aided networks;
• Design of backscatter transmission for RIS-aided networks;
• RIS-assisted two-way relaying communications;
• Full-duplex communications in RIS-aided networks;
• New architectures and communication protocols for RIS-aided networks;
• RIS-aided networks and testbed designed along with emerging networks;
• Applications of deep learning to RIS-aided networks;
• Other emerging networks beat with RIS-aided networks.

Prof. Dinh-Thuan Do
Prof. Alagan Anpalagan
Prof. Fatemeh Afghah
Prof. Evangelos Pallis
Guest Editors

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• Non-orthogonal multiple access (NOMA)
• Machine learning
• Unmanned aerial vehicle (UAV)
• Internet of Things
• UAV-assisted RIS communications
• Multiple-input multiple-output (MIMO)