News Release

Prepare for the foreseeable future of 6G

Energy efficient solution proposed for energy hungry phased arrays in THz communications

Peer-Reviewed Publication

Tsinghua University Press

With 5G wireless service becoming available and 6G systems on the horizon, scientists are working to address the high energy consumption issues related to communication in the Terahertz (THz) bandwidth, which will be crucial for the future 6G technology development. A team of researchers had undertaken a study of a reconfigurable intelligent surface technique, exploring its potential for addressing the high energy consumption problem for THz communication.


The team, with researchers from China and the United Kingdom, published their findings on April 29, 2022, in the journal Intelligent and Converged Networks at DOI:


THz communication generally refers to frequencies above 100 gigahertz (GHz). With its tremendous bandwidth, the THz band holds promise for its ability to support future 6G wireless systems with their high data rates. Where 5G wireless systems typically require several GHz of bandwidth in the millimeter-wave band, the THz band is capable of providing tens of GHz bandwidth. At the higher frequency rate of the THz band, one of the major obstacles is the severe propagation attenuation, where the signal loses its strength during transmission. Massive multiple-input multiple-output (MIMO) can be used to compensate for the path loss that occurs at higher frequencies. But the existing THz communication with massive MIMO has high energy consumption requirements. Reconfigurable intelligent surfaces (RIS) offer a possible solution to these high energy challenges.


An RIS is a programmable structure where the electric and magnetic properties of the surface can be changed. By changing these properties on the RIS, researchers can control communication channels. The research team addressed the high energy consumption problem in THz communication by proposing a RIS-hybrid precoding architecture, that combines analog and digital precoding, to achieve the analog beamforming.  In beamforming the wireless signal is focused at a specific receiving device, instead of being broadcast in all directions, resulting in faster, more reliable connections. This RIS technique proves to be more energy efficient than the phased array technique typically used.


“Phased array-based hybrid precoding in THz communication requires a large number of analog phase shifters to realize the analog beamforming, which results in very high energy consumption. In our work, to reduce energy consumption, the energy-hungry phased array in the conventional hybrid precoding architecture is replaced by the energy-efficient RIS to realize the analog beamforming,” said Yu Lu, a Ph.D. candidate at Tsinghua University.


The team’s next step was to create a low-complexity algorithm based on deep learning to solve the analog beamforming problem and to maximize the sum-rate of the users. In deep learning, computers are taught to learn by example, similar to the way humans learn. Their simulation results showed that their proposed algorithm has a much lower runtime than the traditionally used algorithm with about the same sum-rate performance. The scientists hope that their work will motivate others toward more research involving RIS for possible application in future 6G communications.


In their research, the team only looked at the one possible scenario for RIS application, where it is used as an alternative to the traditional energy-hungry phased array at the transmitter. Looking ahead, the research team sees other possible uses for RIS. “For example, if a RIS is employed between the transmitter and receiver, RIS is able to overcome the signal blockage problem in a wireless propagation environment by providing an extra propagation path. In the future, we plan to do some in-depth research on exploiting RIS on the receiver side to enhance the received signal power,” Lu said.


Other members of the research team include Mo Hao, with Tsinghua SEM Advanced ICT Laboratory at Tsinghua University, and Richard Mackenzie, with BT Technology, Ipswich, United Kingdom. The research is funded by the National Key Research and Development Program of China and the National Natural Science Foundation of China.


The paper is also available on SciOpen ( by Tsinghua University Press.




About Intelligent and Converged Networks 


Intelligent and Converged Networks is an international specialized journal that focuses on the latest developments in communication technology. 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 draws its name from the accelerating convergence of different fields of communication technology and the growing influence of artificial intelligence and machine learning.


About SciOpen 


SciOpen is a professional open access resource for discovery of scientific and technical content published by the Tsinghua University Press and its publishing partners, providing the scholarly publishing community with innovative technology and market-leading capabilities. SciOpen provides end-to-end services across manuscript submission, peer review, content hosting, analytics, and identity management and expert advice to ensure each journal’s development by offering a range of options across all functions as Journal Layout, Production Services, Editorial Services, Marketing and Promotions, Online Functionality, etc. By digitalizing the publishing process, SciOpen widens the reach, deepens the impact, and accelerates the exchange of ideas.

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