Drones may soon be responsible for sending digital data signals back from senders to receivers, according to a new collection of peer-reviewed research papers on the role of reconfigurable intelligent surfaces (RIS) in advancing wireless communications.
Organized worldwide by an international editorial board, this special issue was published on April 29 in Intelligent and converged networksa journal published jointly by Tsinghua University Press and the International Telecommunication Union, the United Nations specialized agency for information and communication technologies.
“RIS is a new emerging physical layer technology in wireless communication,” said Linglong Dai, associate professor of electronic engineering at Tsinghua University in China and editor of the special issue. Dai is also affiliated with the Beijing National Research Center for Information Science and Technology.
In basic wireless communications, a transmitter sends a signal encoded with information on a specific frequency to a receiver, such as local news to a specific radio station. The signal, however, may be blocked, scrambled, or lost over the distance between the start and the intended end of the communication. More advanced wireless communications improve on this by bouncing signals: a signal travels from a base transceiver – which both transmits and receives messages – to a mobile transceiver, which bounces it at an angle defined towards the customer, bypassing obstacles. Now in 5G, transceivers can contain multiple antennas to transmit and receive multiple signals over multiple channels for multiple clients while minimizing interference between them.
RIS, a thin-plate array of individually programmable and controllable components, customizes the efficiency and clarity of 5G, according to Dai. Each piece of the RIS can be adjusted independently to achieve the exact bounce angle required by the signals.
“RIS promises a paradigm shift for wireless communications, where the wireless propagation environment can be dynamically controlled, which is significantly different from the conventional design that focuses only on the transmitter and receiver,” said Dai said. “But, although the number of publications on SIFs has increased sharply, there are still many problems that are difficult to study in depth.”
To highlight potential solutions to barriers to SIF progress, the researchers selected eight research papers for inclusion.
“After a strict review process, we selected the included papers – submitted by some of the best-known groups in this field – based on their technical relevance and merits in advancing the practicality of this technology,” Dai said. “In this special issue, many hot topics on RIS technology and techniques have been well studied, such as performance analysis and optimization, channel strength and security, integration into systems current wireless devices and an overview of current RIS hardware and potential system prototyping.”
According to Dai, the editors intend for the special issue to provide insight into the breadth and depth of current research on SIFs.
“We hope that through the efforts of our special issue, researchers will be inspired to continue advancing RIS technology, bringing a paradigm shift to developing 6G wireless communications for the foreseeable future,” Dai said.
Other editors for the special issue include Chan-Byoung Chai, School of Integrated Technology, Yonsei Institute of Convergence Technology, Yonsei University, Korea; Shi Jin, National Mobile Communications Research Laboratory, Southeastern University, China; Marco Di Renzo, Paris-Saclay University, CNRS, CentraleSupélec, Signals and Systems Laboratory; and Rui Zhang, Department of Electrical and Computer Engineering, National University of Singapore. Dai, Chai, Di Renzo, and Zhang are members of the Institute of Electrical and Electronics Engineers, and Jin is a senior member.
The articles accepted by this special number are listed below: Reconfigurable smart surfaces for wireless communications: overview of hardware designs, channel models, and estimation techniques. DOI: https://doi.org/10.23919/ICN.2022.0005. Intelligent and Converged Networks, April 29, 2022.  Reconfigurable Intelligent Surface-Assisted Wireless Communications: An Overview. DOI: https://doi.org/10.23919/ICN.2022.0007. Intelligent and Converged Networks, April 29, 2022.  Maximized dirty paper encoding rate of RIS-assisted multi-user MIMO broadcast channels. DOI: https://doi.org/10.23919/ICN.2022.0004. Intelligent and Converged Networks, April 29, 2022.  Performance analysis of reconfigurable intelligent surface-assisted systems under channel aging. DOI: https://doi.org/10.23919/ICN.2022.0002. Smart and Converged Grids, Apr 229. 2022.  User cooperation for secure MIMO systems assisted by IRS. DOI: https://doi.org/10.23919/ICN.2022.0001. Intelligent and Converged Networks, April 29, 2022.  Massive reconfigurable smart surface assisted access without subsidy. DOI: https://doi.org/10.23919/ICN.2022.0009. Intelligent and Converged Networks, April 29, 2022.  Reconfigurable intelligent surface-based hybrid precoding for THz communications. DOI: https://doi.org/10.23919/ICN.2022.0003. Intelligent and Converged Networks, April 29, 2022.  Aerial intelligent reflective surface for secure wireless networks: privacy capability and optimal trajectory strategy. DOI: https://doi.org/10.23919/ICN.2022.0020. Intelligent and Converged Networks, April 29, 2022.
These articles are also available on SciOpen (https://www.sciopen.com/home) by Tsinghua University Press.
On Intelligent and converged networks
Intelligent and converged networks is an international specialist journal that focuses on the latest developments in communication technologies. The journal is co-published by Tsinghua University Press and the International Telecommunication Union (ITU), the United Nations specialized agency for information and communication technology (ICT). Intelligent and converged networks takes its name from the accelerated convergence of different areas of communication technology and the growing influence of artificial intelligence and machine learning.
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