Title: Resource-Constrained Specific Emitter Identification Method Using End-to-End Sparse Feature Selection
The code corresponds to the paper
pytorch 1.10.2 python 3.6.13
Experiments are conducted on ADS-B [25], WiFi [26] and LoRa [27] datasets.
[25] Y. Tu, Y. Lin, H. Zha, J. Zhang, Y. Wang, G. Gui, and S. Mao, “Large scale real-world radio signal recognition with deep learning,” Chinese J. Aeronaut., vol. 35, no. 9, pp. 35–48, Sept. 2022.
[26] K. Sankhe, M. Belgiovine, F. Zhou, S. Riyaz, S. Ioannidis, and K. Chowdhury, “ORACLE: Optimized radio classification through convolutional neural networks,” in IEEE Conference on Computer Communications (ICCC), 2019, pp. 370–378.
[27] G. Shen, J. Zhang, A. Marshall, and J. R. Cavallaro, “Towards scalable and channel-robust radio frequency fingerprint identification for LoRa,” IEEE Trans. Inf. Forensics Security, vol. 17, no. 14, pp.774–787, 2022.
utils-->functions used for training and testing
model-->functions for building model
data_load-->load dataset
optimizer-->functions for optimizer (SGD and APGD)
config-->hyperparameters and paths
main-->train and test
If you have any question, please feel free to contact us by e-mail (1022010435@njupt.edu.cn).