TY - GEN
T1 - Short-time modulation classification of complex wireless communication signal based on deep neural network
AU - Yin, Ruirui
AU - Huang, Jingxuan
AU - Fei, Zesong
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - Modulation classification of communication signal is one of the key technologies for realizing non-cooperative communication tasks, multi system communication interconnection and software radio. Therefore, when the decision process cannot wait for more data to increase certainty, how to effectively classify the modulation type in a short time is an unavoidable and challenging topic. In this paper, we make a performance comparison of traditional feature-based neural network and deep neural network (DNN) with complex digital modulation signal datasets. The results indicate that DNN has a stronger ability to extract classification features. Then we demonstrate two novel architectures based on DNN, which disentangle more meaning hidden features from the short-time signal and perform superiorly under limited signal length. Finally, we test the generalization ability of neural network models to signal-to-noise radio (SNR).
AB - Modulation classification of communication signal is one of the key technologies for realizing non-cooperative communication tasks, multi system communication interconnection and software radio. Therefore, when the decision process cannot wait for more data to increase certainty, how to effectively classify the modulation type in a short time is an unavoidable and challenging topic. In this paper, we make a performance comparison of traditional feature-based neural network and deep neural network (DNN) with complex digital modulation signal datasets. The results indicate that DNN has a stronger ability to extract classification features. Then we demonstrate two novel architectures based on DNN, which disentangle more meaning hidden features from the short-time signal and perform superiorly under limited signal length. Finally, we test the generalization ability of neural network models to signal-to-noise radio (SNR).
KW - Modulation classification
KW - machine learning
KW - neural network
KW - short-time
KW - wireless communication
UR - http://www.scopus.com/inward/record.url?scp=85062882183&partnerID=8YFLogxK
U2 - 10.1109/APCC.2018.8633576
DO - 10.1109/APCC.2018.8633576
M3 - Conference contribution
AN - SCOPUS:85062882183
T3 - 2018 24th Asia-Pacific Conference on Communications, APCC 2018
SP - 520
EP - 524
BT - 2018 24th Asia-Pacific Conference on Communications, APCC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 24th Asia-Pacific Conference on Communications, APCC 2018
Y2 - 12 November 2018 through 14 November 2018
ER -