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.

在本文中，我们提出了一种基于环境背向散射通信的智能5G IoT网络。该网络由两部分组成，即基于环境背向散射通信的实时数据传输系统和基于浅层神经网络和深层神经网络相结合的实时大数据分析系统。基于环境后向散射通信的实时数据传输系统可以延长数据采集设备的待机时间，减小设备尺寸，提高佩戴舒适度。结合了浅层神经网络和深层神经网络的实时大数据分析系统，可以大大降低频繁进行MEC的深层神经网络计算所带来的压力，并大大降低MEC用于远程实时监控的能耗。