Dual-Stream CNN-BiLSTM Model with Attention Layer for Automatic Modulation Classification
Author:
Affiliation:
1. Sardar Vallabhbhai National Institute of Technology,Surat,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10041243/10041245/10041403.pdf?arnumber=10041403
Reference18 articles.
1. Convolutional Radio Modulation Recognition Networks
2. Deep architectures for modulation recognition
3. End-to-End Learning From Spectrum Data: A Deep Learning Approach for Wireless Signal Identification in Spectrum Monitoring Applications
4. Modulation Classification Based on Signal Constellation Diagrams and Deep Learning
5. Data-Driven Deep Learning for Automatic Modulation Recognition in Cognitive Radios
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1. BiLSTM and Attention-Based Modulation Classification of Realistic Wireless Signals;2024 International Conference on Signal Processing and Communications (SPCOM);2024-07-01
2. ABConv: Attention Based Convolution for Automatic Modulation Recognition;2024 IEEE International Conference on Communications Workshops (ICC Workshops);2024-06-09
3. Deep multilevel architecture for automatic modulation classification;Physical Communication;2024-06
4. SDR implementation of a light deep learning model based CNN for joint spectrum sensing and AMC;Physica Scripta;2024-04-10
5. DeepSIG: A Hybrid Heterogeneous Deep Learning Framework for Radio Signal Classification;IEEE Transactions on Wireless Communications;2024-01
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