标题：DBN Based Automatic Modulation Recognition for Ultra-low SNR RFID Signals
作者：Ma Liang; Yang Yang; Wang Hongjun
作者机构：[Ma Liang; Yang Yang; Wang Hongjun] Shandong Univ, Sch Informat Sci & Engn, Jinan 250100, Peoples R China.
会议名称：35th Chinese Control Conference (CCC)
会议日期：JUL 27-29, 2016
来源：PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016
关键词：DBN; modulation recognition; RFID; noise robust recognition; low SNR
摘要：Deep belief network (DBN) is a powerful tool for extracting high level features of sequential data. This paper proposes a DBN based automatic modulation recognition method of RFID signals in ultra-low signal-to-noise ratio (SNR) conditions. First, we perform FFT with simulated data to get its spectrum. The spectrum and amplitude of the original signal are then used as features to train a DBN. After the training, the DBN is deployed to process modulated signals with low SNR. Experiments were conducted to calculate the performance of the proposed method with simulated ASK, single subcarrier modulation, dual subcarrier modulation, PSK, carrier wave and white Gaussian noise signals. We found that the proposed DBN based scheme is able to achieve better performance with ultra-low SNR signal (around-10dB) than traditional BP artificial neural networks.