automatic-modulation-classification

[IEEE-WCL] A Spatiotemporal Multi-Channel Learning Framework for Automatic Modulation Recognition

[TCCN 2023] Official code for "Towards the Automatic Modulation Classification with Adaptive Wavelet Network".

[ICASSP 2023] Official repo for "AMC-Net: An Effective Network for Automatic Modulation Classification".

Meta-Transformer: A meta-learning framework for scalable automatic modulation classification

Code for "Complex-Valued Depthwise Separable Convolutional Neural Network for Automatic Modulation Classification"

This is the official implementation for the paper: "A Contrastive Learner for Automatic Modulation Classification" (IEEE Trans. Wireless Commun., vol. 24, no. 4, 2025).

Code containing various models for automatic modulation classification (AMC).

Official code for "EMC²-Net: Joint Equalization and Modulation Classification based on Constellation Network", ICASSP 2023.

Deep learning based automatic modulation classification for sub-carriers of OFDM signals.

Energy-Modulated Gain (EMG) that the sufficient-statistic-driven conditional normalization layer for automatic modulation recognition, with EMGNet and five baselines on RML2016.10a, RML2018.01a, and HisarMod2019.

Train a CNN for classifying digital modulation

Automatic modulation classification with a CNN-LSTM (JIEE 2025): PyTorch notebooks for dataset construction, training and evaluation on RadioML 2018.01A and GNU Radio signals.

Automatic modulation classification for six simulated I/Q signal classes using DSP features, Random Forest, a compact 1D CNN, and a Streamlit workbench.

Deployment-guided automatic modulation classification for bare-metal MCU-class IoT edge devices using DSC-AMCNet.

Project page for “CNN-LSTM Hybrid Architecture for Over-the-Air Automatic Modulation Classification using SDR” (JIEE 2025)

Why do automatic modulation classifiers lose accuracy on a new domain? Measuring, explaining and closing the gap on RadioML 2016.10a and 2018.01A. PyTorch, ICRNNA reproduction, literature baselines.

Wireless modulation classification with MATLAB, NumPy, PyTorch, channel simulation, and SNR robustness analysis.