TY - GEN
T1 - Modulation Pattern Recognition Based on Wavelet Approximate Coefficient Entropy
AU - Zuo, Xiaoya
AU - Xu, Donghuan
AU - Wang, Peng
AU - Yao, Rugui
AU - Yang, Junjie
AU - Pan, Lulu
N1 - Publisher Copyright:
© 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
PY - 2021
Y1 - 2021
N2 - Aiming at the modulation pattern recognition of multiple signals in complex electromagnetic environments, a modulation pattern recognition method based on wavelet approximate coefficient entropy is proposed. Based on the traditional wavelet entropy, an improved wavelet entropy, wavelet approximate coefficient entropy, is proposed, which has strong ability to represent the modulation signal characteristics and has good noise suppression effect. The simulation results verify the correctness of the theoretical analysis, and show that the proposed method can effectively realize the modulation pattern recognition of multiple signals at low signal to noise ratio.
AB - Aiming at the modulation pattern recognition of multiple signals in complex electromagnetic environments, a modulation pattern recognition method based on wavelet approximate coefficient entropy is proposed. Based on the traditional wavelet entropy, an improved wavelet entropy, wavelet approximate coefficient entropy, is proposed, which has strong ability to represent the modulation signal characteristics and has good noise suppression effect. The simulation results verify the correctness of the theoretical analysis, and show that the proposed method can effectively realize the modulation pattern recognition of multiple signals at low signal to noise ratio.
KW - Modulation pattern recognition
KW - Recognition rate
KW - Signal to noise ratio
KW - Wavelet approximate coefficient entropy
UR - http://www.scopus.com/inward/record.url?scp=85101394510&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-67514-1_53
DO - 10.1007/978-3-030-67514-1_53
M3 - 会议稿件
AN - SCOPUS:85101394510
SN - 9783030675134
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 673
EP - 684
BT - IoT as a Service - 6th EAI International Conference, IoTaaS 2020, Proceedings
A2 - Li, Bo
A2 - Li, Changle
A2 - Yang, Mao
A2 - Yan, Zhongjiang
A2 - Zheng, Jie
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th EAI International Conference on IoT as a Service, IoTaaS 2020
Y2 - 19 November 2020 through 20 November 2020
ER -