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

页码：223 / 226

页数：4

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