Sep 9, 2021 · In this paper, we propose to use densely connected convolutional networks combined with bidirectional recurrent neural networks to identify the radios of 11 ...

This paper proposes to use densely connected convolutional networks combined with bidirectional recurrent neural networks to identify the radios of 11 ...

In this paper, we propose to use densely connected convolutional networks combined with bidirectional recurrent neural networks to identify the radios of 11 ...

DenseNet and BLSTM, and use it for radio modulation recognition, which solves the problem of lower classification accuracy. III. NEURAL NETWORK MODEL. A. CNN ...

In this paper, we propose to use densely connected convolutional networks combined with bidirectional recurrent neural networks to identify the radios of 11 ...

DenseNet + BLSTM + DNN structure. A Kind of Wireless Modulation Recognition Method Based on DenseNet and BLSTM. Article. Full-text available. Sep 2021.

Xiaosong Xie, Guangsong Yang , Mengxi Jiang, Qiubo Ye , Chen-Fu Yang: A Kind of Wireless Modulation Recognition Method Based on DenseNet and BLSTM.

This paper proposes to use densely connected convolutional networks combined with bidirectional recurrent neural networks to identify the radios of 11 ...

In the proposed model, DenseNet and ResNet extract different spatial features of samples, and then LSTM extracts the sequence of samples. Also, the attention ...

Sep 17, 2022 · This paper proposes a novel MR algorithm that is capable of recognizing a broad variety of modulation types, including M-ary QAM and M-ary PSK, without ...