Adaptive wireless-powered network based on CNN near-field positioning by a dual-band metasurface.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 39609441.
- Also identified by DOI 10.1038/s41467-024-54800-2 and PMC identifier 11604785.
- Licence recorded as CC BY-NC-ND.
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Abstract
With the improvement of industry, the connectivity of electronic devices gradually shift from wired to wireless. As a solution for power delivery, the non-contact power transfer holds promising ways to charge for moving terminals, enabling battery-free sensing, processing, and communication. Based on a dual-band metasurface, this study proposes an adaptive wireless-powered network (AWPN) to realize the simultaneous wireless localization and non-contact power supply. It first achieves localization with 3 cm resolution on a single-input single-output (SISO) system, by combining space-time-coding (STC) and convolutional neural network (CNN). With precise position information, AWPN real-time aligns power beams to the terminals for stable energy transmission. Then, battery-free terminals enable to perceive the environmental data and uploads the results. From the measurement results, AWPN gets more than 98% CNN classification accuracy and can tolerate certain environmental changes. Thus, being adaptive and contactless, our study will propel the advancement in Internet of Things (IoT), intelligent metasurface, and the robot industry.