Design and Implementation of a Novel Interconnection Architecture from WiFi to ZigBee

Abstract

AbstractThe signal layer heterogeneous communication technology is a cross-technology communication (CTC) technology, which is a direct communication technology between different wireless devices. Since ZigBee and WiFi have overlapping spectrum distribution, the ZigBee transmission will affect the CSI sequence. We propose a CTC technology based on machine learning and neural network, from Zigbee to WiFi, leveraging only WiFi channel state information (CSI). By classifying WiFi CSI, we can distinguish whether there is ZigBee signal transmission in WiFi signal. This paper uses the machine learning method and neural network method to classify CSI sequence analyzes the importance of CSI sequence features to the classifier, improves the accuracy of machine learning classifier by extracting multiple CSI sequence features, and improves the classification accuracy by neural network classifier. In our experimental data set, the highest accuracy can reach 95%. The evaluation results show that our accuracy is higher than the existing methods.