Adaptive wireless-powered network based on CNN near-field positioning by a dual-band metasurface

Xia De Xiao, Jia Qi Han, Ya Jie Mu, Lei Guan, Xin Wang, Xiang Jin Ma, Li Hao Zhu, Tian Guang Lv, Hai Xia Liu, Yan Shi, Long Li () and Tie Jun Cui ()
Additional contact information
Xia De Xiao: Xidian University
Jia Qi Han: Xidian University
Ya Jie Mu: Xidian University
Lei Guan: Xidian University
Xin Wang: Xidian University
Xiang Jin Ma: Xidian University
Li Hao Zhu: Xidian University
Tian Guang Lv: Xidian University
Hai Xia Liu: Xidian University
Yan Shi: Xidian University
Long Li: Xidian University
Tie Jun Cui: Southeast University

Nature Communications, 2024, vol. 15, issue 1, 1-11

Abstract: 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.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-024-54800-2 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-54800-2

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-024-54800-2

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().