Modulation Classification with Deep Learning
Train a neural network to listen to a radio signal and tell you which modulation scheme it uses.
- Role
- Course Project
- Period
- Sep. 2025 – Jan. 2026
- Institution
- SUSTech Supervised by Dr. Guang Wu
Why this matters
A receiver has to know the modulation scheme before it can demodulate. Hand-designed discriminative features work until the channel conditions change, then they break. Letting a network learn directly from the raw waveform is the more general approach.
What I did
- Generated QPSK, 8-PSK, and 64-QAM baseband signals in MATLAB, including symbol mapping, upsampling, and square-root raised cosine (RRC) pulse shaping.
- Analyzed time-domain and frequency-domain characteristics of modulated signals using FFT to study bandwidth and spectral properties.
- Applied a convolutional neural network (CNN) to classify digital modulation schemes and interpreted classification probabilities.
Technologies
- MATLAB
- Digital Communications
- FFT Spectral Analysis
- Convolutional Neural Networks