Research Article
A Novel Individual Radio Identification Algorithm Based on Multi-dimensional Features and Gray Relation Theory
@INPROCEEDINGS{10.1007/978-3-319-73317-3_16, author={Hui Han and Jingchao Li and Xiang Chen}, title={A Novel Individual Radio Identification Algorithm Based on Multi-dimensional Features and Gray Relation Theory}, proceedings={Advanced Hybrid Information Processing. First International Conference, ADHIP 2017, Harbin, China, July 17--18, 2017, Proceedings}, proceedings_a={ADHIP}, year={2018}, month={2}, keywords={Individual radio recognition Hilbert transform Integral envelope theory PCA analysis Gray relation theory}, doi={10.1007/978-3-319-73317-3_16} }- Hui Han
Jingchao Li
Xiang Chen
Year: 2018
A Novel Individual Radio Identification Algorithm Based on Multi-dimensional Features and Gray Relation Theory
ADHIP
Springer
DOI: 10.1007/978-3-319-73317-3_16
Abstract
With the advent of the Internet of Things, the number of mobile, embedded, and wearable devices are on the rising nowadays, which make us increasingly faced with the limitations of traditional network security control. Hence, accurately identifying different wireless devices through Hybrid information processing method for the Internet of things becomes very important today. To this problem, we design, implement, and evaluate a robust algorithm to identify the wireless device with fingerprints features through integral envelope and Hilbert transform theory based PCA analysis algorithm. Integral envelope theory was used respectively to process the signals first, then the principal component features can be extracted by PCA analysis algorithm. At last, gray relation classifier was used to identify the signals. We experimentally demonstrate effectiveness of the proposed algorithm ixin differentiating between 500 numbers of wireless device with the accuracy in excess of 99%. The approach itself is general and will work with any wireless devices’ recognition.
