Research Article
An Intelligent Wireless Signal Detection and Recognition Platform
@INPROCEEDINGS{10.1007/978-3-031-37139-4_16, author={Haoyu Zhao and Yan Zhang and Wancheng Zhang and Guangchuan Cao and Jiupeng Song and Shanping Yu}, title={An Intelligent Wireless Signal Detection and Recognition Platform}, proceedings={IoT as a Service. 8th EAI International Conference, IoTaaS 2022, Virtual Event, November 17-18, 2022, Proceedings}, proceedings_a={IOTAAS}, year={2023}, month={7}, keywords={Radio frequency (RF) signal acquisition time-frequency map analysis signal detection and recognition deep learning YOLO target detection}, doi={10.1007/978-3-031-37139-4_16} }- Haoyu Zhao
Yan Zhang
Wancheng Zhang
Guangchuan Cao
Jiupeng Song
Shanping Yu
Year: 2023
An Intelligent Wireless Signal Detection and Recognition Platform
IOTAAS
Springer
DOI: 10.1007/978-3-031-37139-4_16
Abstract
The detection and recognition of wireless signals play an essential role in the communications security of the Internet of Things (IoT). In order to monitor wireless signals, a platform that can detect and recognize wireless signals in real time is needed. This paper describes an intelligent wireless signal detection and recognition platform. The platform can monitor the presence or absence of wireless signals in real time and perform parameter analysis and modulation classification of wireless signals. We design and implement an integrated detection and recognition scheme based on the You Only Look Once for Signal Detection (YOLO-SD) and the Convolutional Neural Networks (CNN). The YOLO-SD algorithm has a fast running speed, thus the platform can work in real-time. The platform is designed and implemented on Field Programmable Gate Array (FPGA) platform. The result shows that our proposed platform achieves a detection accuracy of 80% and recognition accuracy of 93%, thus demonstrating the significant potential for analyzing RF spectral activity with high accuracy.
