Efficient Training of Deep Classifiers for Wireless Source Identification Using Test SNR Estimates

• Published in: IEEE wireless communications letters Vol. 9; no. 8; pp. 1314 - 1318
• Main Authors: Wang, Xingchen, Ju, Shengtai, Zhang, Xiwen, Ramjee, Sharan, Gamal, Aly El
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.08.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Algorithms; Boosting; channel identification; Computer architecture; Deep learning; Deep learning for wireless; Greedy algorithms; Kernel; Machine learning; Modulation; modulation classification; Signal processing; Signal to noise ratio; SNR bagging; SNR boosting; Training; Wireless communication

We study efficient deep learning training algorithms that process received wireless signals, if a test Signal to Noise Ratio (SNR) estimate is available. We focus on two tasks that facilitate source identification: 1- Identifying the modulation type, 2- Identifying the wireless technology and channe...