Communication Modulation Recognition Method Based on Clustering Algorithm

The modular identification of wireless communication signals is widely used in civil and military fields. With the rapid development of modern communication technology in China, signal modulation becomes complex and diverse. How to accurately identify communication signal modulation methods has beco...

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Bibliographic Details
Published in:Journal of physics. Conference series 2021-03, Vol.1827 (1), p.12153
Main Authors: Cheng, Yuyang, Shao, Shuying
Format: Article
Language:English
Subjects:
Algorithms
Clustering
Feature recognition
Frequencies
Microwave communications
Military communications
Physics
Quadrature amplitude modulation
Satellite communications
Wireless communications
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Summary:The modular identification of wireless communication signals is widely used in civil and military fields. With the rapid development of modern communication technology in China, signal modulation becomes complex and diverse. How to accurately identify communication signal modulation methods has become a research hotspot. Among them, multi band quadrature amplitude modulation (MQAM) is widely used in microwave communication, satellite communication and network communication. It has the advantages of high frequency band utilization and flexible modulation. Therefore, the recognition of MQAM modulation mode is of great significance. Traditional clustering algorithm has some limitations when it is used to identify MQAM signal modulation, such as too many iterations and long recognition time. For high-order modulated signals, a modulation recognition method based on Constellation Clustering is proposed. The constellation is used as the feature of modulation recognition, and the constellation of received signal is reconstructed in groups. The simulation results show that the collected characteristic parameters have strong interference ability to multi-channel, and the recognition rate reaches 97.6%. It has important engineering application value for signal modulation recognition in low SNR environment.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1827/1/012153