Modulation Type Identification TRIZ Cases
- Transpositional Modulation Signal Separation for Bandwidth Efficiency
Combining transpositional modulation with legacy schemes on one carrier resolves bandwidth efficiency limits while maintaining system compatibility.
- Deep Learning Fusion for Automatic Modulation Classification
LSTM and FPN networks extract temporal features to distinguish WBFM from DSB-AM signals, improving classification accuracy.
- Joint Precoding and Probabilistic Constellation Shaping for Channel Efficiency
Joint precoding and probabilistic constellation shaping optimize symbol probabilities to lower transmission energy without sacrificing data throughput.