Large-scale electromagnetic signal recognition based on deep learning

ZHANG Zhen; LI Yibing; ZHA Haoran

doi:10.11805/tkyda2021217

[3] HALL T A,CAROMI R,SOURYAl M,et al. Reference datasets for training and evaluating RF signal detection and classification models[C]// 2019 IEEE Globecom Workshops(GC Wkshps). Hawaii,USA:IEEE, 2019:1-5.

[6] ZHA H,TIAN Q,LIN Y. Real-world ADS-B signal recognition based on Radio Frequency fingerprinting[C]// 2020 IEEE 28th International Conference on Network Protocols(ICNP). Madrid,Spain:IEEE, 2020:1-6.

[9] VO-HUU T D,VO-HUU T D,NOUBIR G,et al. Fingerprinting WiFi devices using software defined radios[C]// Proceedings of the 9th ACM Conference on Security & Privacy in Wireless and Mobile Networks. Darmstadt,Germany:ACM, 2016:3-14.

[10] GUI G,LIU M,KATO N,et al. 6G:opening new horizons for integration of comfort,security,and intelligence[J]. IEEE Wireless Communications, 2020,27(5):126-132.

[11] DONG P,ZHANG H,LI G Y,et al. Deep CNN-based channel estimation for mm wave massive MIMO systems[J]. IEEE Journal of Selected Topics in Signal Processing, 2019,13(5):989-1000.

[12] LIANG F,SHEN C,YU W,et al. Towards optimal power control via ensembling deep neural networks[J]. IEEE Transactions on Communications, 2019,68(3):1760-1776.

[13] SHE C,DONG R,GU Z,et al. Deep learning for ultra-reliable and low-latency communications in 6G networks[J]. IEEE Network, 2020,34(5):219-225.

[14] RAJENDRAN S,MEERT W,GIUSTINIANO D,et al. Deep learning models for wireless signal classification with distributed low-cost spectrum sensors[J]. IEEE Transactions on Cognitive Communications and Networking, 2018,4(3):433-445.

[15] ALI A,FAN Yangyu. Automatic modulation classification using deep learning based on sparse autoencoders with nonnegativity constraints[J]. IEEE Signal Processing Letters, 2017,24(11):1626-1630.