In recent years, extensive research has been done to obtain better demodulation performance by combining signal demodulation with deep learning algorithms, such as convolutional neural networks (CNN). However, the demodulation performance of CNN is not much improved compared with traditional coherent demodulation algorithms. This paper proposes a signal demodulation algorithm based on generative adversarial networks (GAN). The proposed GAN-based demodulation network uses the confrontation characteristics between the generator and the discriminator in GAN to greatly improve the demodulation ability of the signal. Numerical results show that the demodulation performance is better than the coherent demodulation algorithm and the CNN-based demodulation algorithm.
A Signal Demodulation Algorithm Based on Generative Adversarial Networks
2021-10-20
1522647 byte
Conference paper
Electronic Resource
English
EvolGAN: Evolutionary Generative Adversarial Networks
British Library Conference Proceedings | 2021
|