.png){kind=icon}
Return
Deep Learning Based Identification Method for Signal-Level Wireless Protocol
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2022.3220769.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Electromagnetic spectrum surveillance is the basis of space environment monitoring and management, while protocol identification is one of the most important methods. Protocol identification has been applied in many fields, such as target recognition, anomaly detection, security management and information countermeasure. In the past decade, a lot of deep learning based protocol identification methods have been proposed, based on the data-level protocol. However, the data needs to be demodulated and decoded, depending on the prior information of the target system. In this paper, we focus on signal-level protocol, and introduce the deep learning based identification method. We first develop a multi-dimensional convolutional neural network based method for feature extraction of signal-level protocol. Then, a spatial pooling convolutional neural network is introduced for variable length protocol identification. At last, an unsupervised training network is proposed for feature extraction of unlabelled signal-level protocol. The proposed methods are evaluated by using the practical wireless protocols, and the effectiveness is verified by simulation results.
Keywords:
Protocol identification
signal-level protocol
convolutional neural network
spatial pyramid pooling
correlation coefficient loss function
Journal
IF:
3.6
Papers:
9.8W
Citations:
29.4W
Organization
No organization information available
Cited Papers
ShareSaveComparative study of layer by layer assembled multilayer films based on graphene oxide and reduced graphene oxide on flexible polyurethane foam: flame retardant and smoke suppression properties.png)
RSC Advances
RSC AdvancesIF0
PREAI
ShareSaveShareSaveShareSave
View more