EURASIP Journal on Wireless Communications and Networking | |
Ambient backscatter communication-based smart 5G IoT network | |
Songlin Sun1  Qiang Liu1  Yang’an Zhang2  Xueguang Yuan2  | |
[1] School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, 100876, Beijing, China;State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, 100876, Beijing, China; | |
关键词: 5G; IoT; Machine learning; Ambient backscatter communication; | |
DOI : 10.1186/s13638-021-01917-3 | |
来源: Springer | |
【 摘 要 】
In this paper, we propose an ambient backscatter communication-based smart 5G IoT network. The network consists of two parts, namely a real-time data transmission system based on ambient backscatter communication and a real-time big data analysis system based on the combination of shallow neural networks and deep neural networks. The real-time data transmission system based on ambient backscatter communication can extend the standby time of data collection equipment, reduce the size of the equipment, and increase the comfort of wearing. The real-time big data analysis system combining the shallow neural network and the deep neural network can greatly reduce the pressure caused by the frequent deep neural network calculations of the MEC and greatly reduce the energy consumed by the MEC for remote real-time monitoring.
【 授权许可】
CC BY
【 预 览 】
Files | Size | Format | View |
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RO202106296543303ZK.pdf | 1730KB | download |