Deep Learning for Multi-Antenna Modulation Recognition of Radio Signals
Multi-antenna receiving systems have become a prevalent technical solution in communication systems. Meanwhile, deep learning has achieved significant progress in automatic modulation recognition tasks in single-antenna systems. However, the application of deep learning in multi-antenna modulation recognition (MAMR) tasks is still limited. In this paper, we propose an MAMR method namely MAMR-IQ to fully explore the diversity gain of a multi-antenna receiving system, which concatenates the raw received in-phase and quadrature (IQ) signals of multiple antennas and feeds them into a convolutional neural network. Simulation results show that the proposed MAMR-IQ method outperforms two existin...
| Authors | Tao Chen, Shilian Zheng, Jiepeng Chen et al. |
|---|---|
| Primary category | eess.SP |
| Published | 20 April 2026 |
| Last updated at source | 20 April 2026 |
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