New research out of South Korea offers enormous opportunities to improve efficiency and integrated sensing for water utilities.
Researchers at Pusan National University have developed a new backscatter communication system that is 40% more energy-efficient than conventional backscattering systems and enables integrated sensing and communication technology. This innovation has the potential to significantly improve the efficiency and functionality of wireless communication for water industry applications.
Backscatter communication (BackCom) is a promising low-power method for wireless communication in IoT applications. In BackCom, devices reflect and modulate existing signals to transmit data rather than generating their own signals. This makes it ideal for battery-powered devices, such as those used in water distribution networks.
The new system addresses a key challenge in BackCom – accurately predicting the optimal reflection coefficient to achieve low bit error rates and high data rates. The researchers used a technique called transfer learning to develop a model that can accurately predict reflection coefficients based on input bias voltages. This allows for the selection of optimal modulation schemes, such as Quadrature Amplitude Modulation (QAM).
The new system’s improved efficiency and accuracy could benefit water utilities, including reduced battery consumption for wireless sensor devices, improved data transmission rates, and enhanced integration of sensing and communication.
Overall, the new backscatter communication system has the potential to revolutionize wireless communication for water industry applications. By improving efficiency, accuracy, and data rates, the system could enable water utilities to collect and transmit more data than ever before, leading to improved decision-making and operational efficiency.
The system is still under development but has the potential to be deployed in a range of water industry applications. This includes smart water metering, leak detection and remote monitoring of water quality. The research team is working to commercialise the technology and hopes to have the technology ready in the next few years.
The paper, titled Polarization Diversity and Transfer Learning Based Modulation Optimization for High-Speed Dual Channel MIMO Backscatter Communication, was published in the IEEE Internet of Things Journal. The article can be found at https://ieeexplore.ieee.org/document/10477275
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