A UnetNND-BP Architecture for Channel Decoding Under Correlated Noise

In this letter, we introduce a Unet-based neural network denoiser-belief propagation (UnetNND-BP) architecture with two training modes to improve the decoding performance of low-density parity-check (LDPC) codes. In the supervised learning mode, UnetNND-BP achieves better performance than benchmark schemes, while in the self-supervised learning mode, it achieves comparable performance.