AI RESEARCH
Sequential Neural Probabilistic Amplitude Shaping: Learning the Channel's Language
arXiv CS.LG
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ArXi:2605.28143v1 Announce Type: new We present the first neural probabilistic amplitude shaping that outperforms existing methods while accounting for all implementation losses, using a block-less, easily implementable sequential autoregressive encoder compatible with arithmetic distribution matching, yielding reduced rate loss and higher achievable information rates.