Researchers at Nagoya Institute of Technology have developed a metasurface that distinguishes wireless signals based on frequency and pulse width. Published in Nature Communications last month, this breakthrough offers a solution to enhance communication capacity.
A team of researchers from Japan, led by Associate Professor Hiroki Wakatsuchi from Nagoya Institute of Technology, along with co-authors Ashif Aminulloh Fathnan and Associate Professor Shinya Sugiura of the University of Tokyo, has designed a metasurface that can distinguish wireless signals based on their frequency and pulse width.
The researchers project a substantial increase in wireless devices per square kilometer, from a million in 5G to 10 million in 6G by 2030. This surge will strain existing frequency bands. However, metasurfaces offer a novel solution, capable of distinguishing wireless signals and enabling the operation of numerous IoT sensors and communication devices without severe interference.
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This advancement holds significant implications for next-generation communication services, including autonomous driving, smart factories, digital twins, cyber-physical systems, and behavior recognition systems.
Wireless demand surges as communication systems evolve, driven by the proliferation of mobile phones, Internet of Things (IoT) devices, and smart sensors. However, this surge leads to congestion within available frequency bands.
Wireless communication signals
Metasurfaces, engineered to manipulate electromagnetic waves, enable the differentiation of signals, reducing congestion-related issues. The team’s metasurface effectively expands signal separation possibilities, enhancing traditional methods. By employing several unit cells responsive to specific frequencies, the metasurface can handle signals across multiple bands, similar to frequency-hopping.
“Going ahead, this could help in more wireless communication signals and devices being made available even with limited frequency resources,” said Dr. Wakatsuchi.
This innovation drastically increases the number of distinguishable signals from a linear to a factorial relationship with available frequencies. For example, with four or five frequencies, the distinguishable signals surge from four or five to 24 or 120, respectively. This exponential growth in signal handling could alleviate strain on existing frequency bands, crucial as the number of connected devices is projected to soar in future wireless networks.
Applications for this technology span various sectors, including autonomous driving, smart factories, and behavior recognition systems. With metasurfaces, the next generation of communication services can thrive, leveraging limited frequency resources more efficiently.