Intelligent FCDAE Denoiser for Reliable Decoding Over Correlated Noise Channel - Li, Yan; Lu, Huaiyin; Zhang, Lin; Chen, Jianyuan; Wu, Zhiqiang (IEEE transactions on vehicular technology, 2024)
In practical systems, colored noise commonly imposes on the data delivered, since the ideal white noise can hardly be achieved. In order to suppress the noise, we propose a denoiser based on a fully convolutional denoising autoencoder (FCDAE) for more reliable information recovery. The smart FCDAE consists of a fully convolution-based encoder and decoder to learn the noise structure distribution in the received signals. Besides, the loss function is selected as a combination of mean square error (MSE) and normality test loss. The proposed denoiser can be further combined with decoders such as the low-density parity-check (LDPC) codes. The simulation results over channels with correlated noise demonstrate that the proposed FCDAE denoiser can effectively improve the signal-to-noise ratio (SNR) and bit error rate (BER) performance, thereby achieving superior reliability performance to benchmark systems.