Convolutional Radio Modulation Recognition Networks









6 thoughts on “Convolutional Radio Modulation Recognition Networks

  1. Dear author,
    My name is Yanlun Wu and I am a graduate student in Electrical Engineering at the University of China, Chengdu. I found your paper on “Convolutional Radio Modulation Recognition Networks” very insightful and would like to replicate the results you have reported. I have found the dataset and your GitHub code but it is not the same with your paper, your paper used 96000 examples for training and 64000 for test, the classifier performance vs SNR is higher than the public code in GitHub. If possible, could you please share the source code with me?

  2. The approach and results are impressive. However, have you compare it with feature based method such as those using cyclic cumulants or the likelihood based method? Meanwhile, if it is possible to share your matlab simulation codes?

  3. Did the Keras code you used for training on this work get posted to github recently? I recall seeing something about it at GRCon. What’s the URL?

  4. 1.Could you give a accurate result with numbers, but not the figure 7 in your paper?Because I want to compare your result with mine .
    2.Could you explain the sentence”After training, we achieve roughly a 87.4% classification accuracy across all signal to noise ratios on the test dataset” in your paper? is 87.4% average accuracy at all SNR?

  5. Hi Prof. O’Shea,
    Our group is doing similar research on AMC using neural network. We managed to reproduce similar accuracy result using CLDNN (We discussed about this in Asilomar Conference). But our classification result for QAM signals are not good, while I see in the confusion matrix that you managed to achieve perfect classification between QAM16 and QAM64. Could you please let us know the network architecture you used for the result you presented in the paper?

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