Abstract
In the noncooperation communication scenario, digital signal modulation recognition will help people to identify the communication targets and have better management over them. To solve problems such as high complexity, low accuracy and cumbersome manual extraction of features by traditional machine learning algorithms, a kind of communication signal modulation recognition model based on convolution neural network (CNN) is proposed. In this paper, a convolution neural network combines bidirectional long short-term memory (BiLSTM) with a symmetrical structure to successively extract the frequency domain features and timing features of signals and then assigns importance weights based on the attention mechanism to complete the recognition task. Seven typical digital modulation schemes including 2ASK, 4ASK, 4FSK, BPSK, QPSK, 8PSK and 64QAM are used in the simulation test, and the results show that, compared with the classical machine learning algorithm, the proposed algorithm has higher recognition accuracy at low SNR, which confirmed that the proposed modulation recognition method is effective in noncooperation communication systems.
Highlights
Academic Editors: Adam Glowacz and José Carlos R
This paper proposed the C-bidirectional long short-term memory (BiLSTM)-A algorithm, which improves the recognition accuracy of digital signal modulation by combining convolution neural network (CNN), BiLSTM and the attention
This paper proposed the C-BiLSTM-A algorithm, which improves the recognition accuracy of digital signal modulation by combining CNN, BiLSTM and the attention mechanism
Summary
Academic Editors: Adam Glowacz and José Carlos R. Modulation recognition is a technology to judge the modulation mode of a received signal when the content of modulation information is unknown. It is widely used in radio signal monitoring, electronic countermeasures, intelligent communication and other fields. Due to the interference of noncooperative communication and background noise, some features of the received signal will be blurred, which will affect the recognition result. How to obtain higher recognition accuracy of the modulation mode under low SNR is an important research topic. Automatic modulation recognition is the main modulation recognition method in wireless communication
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