Radio Modulation Classification Optimization Using Combinatorial Deep Learning Technique

Author:

Elkhatib Ziad1ORCID,Kamalov Firuz1ORCID,Moussa Sherif1ORCID,Mnaouer Adel Ben2ORCID,Yagoub Mustapha C.E.3ORCID,Yanikomeroglu Halim4ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, Canadian University Dubai, Dubai, United Arab Emirates

2. Department of Computer Science Engineering, Prince Sultan University, Riyadh, Saudi Arabia

3. Department of Electrical and Computer Engineering, University of Ottawa, Ottawa, Canada

4. Department of Electrical and Computer Engineering, Carleton University, Ottawa, Canada

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Reference51 articles.

1. Deep learning classification of 3.5 GHz band spectrograms with applications to spectrum sensing;Max Lees;arXiv:1806.07745,2018

2. Attention is all you need;Vaswani;arXiv:1706.03762,2017

3. Modulation classification using neural networks;Sathyanarayanan,2019

4. Automatic Modulation Classification Using Compressive Convolutional Neural Network

5. Modulation Signal Classification Algorithm Based on Denoising Residual Convolutional Neural Network

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Modulation Classifier Based on Deep Learning for Beyond 5G Communications;2024 47th International Conference on Telecommunications and Signal Processing (TSP);2024-07-10

2. LPI radar waveform recognition model based on multiple feature image and quasi-residual attention module;Journal of Physics: Conference Series;2024-07-01

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