Sequential Neural Probabilistic Amplitude Shaping: Learning the Channel's Language

For communication systems engineers, this provides a practical neural shaping method that improves over conventional probabilistic amplitude shaping.

This work introduces the first neural probabilistic amplitude shaping method that outperforms existing approaches while accounting for all implementation losses, using a block-less sequential autoregressive encoder that reduces rate loss and achieves higher achievable information rates.