Automatic Recognition of Communication Signal Modulation based on Neural Network

被引：0
|
作者：
Zhu, Xiaolei [1 ]
Lin, Yun [1 ]
Dou, Zheng [1 ]
机构：
[1] Harbin Engn Univ, Coll Informat & Commun Engn, Harbin, Peoples R China
来源：
2016 IEEE INTERNATIONAL CONFERENCE ON ELECTRONIC INFORMATION AND COMMUNICATION TECHNOLOGY ICEICT 2016 PROCEEDINGS | 2016年
关键词：
modulation recognition; cyclic feature; neural network;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In order to solve the problem of low modulation recognition rate of digital communication signals and the difficulty of selecting the appropriate decision threshold, the paper features a recognition method for communication signal modulation. The paper constructs characteristic parameters for recognizing signals in the cyclic frequency domain, and uses a 3-layer neural network as a classifier to identify the modulation mode. The experiment indicates that it can recognize 2FSK, 4FSK, 8FSK, BPSK, QPSK, MSK and 2ASK. When signal to noise ratio (SNR) is higher than 0 dB, the recognition rate achieves 95%. The results suggest that recognition of communication signal modulation based on neural network is accurate and feasible.
引用
收藏
页码：223 / 226
页数：4
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