Estimation of the conditional distribution of an optical nonlinear channel with memory using deep neural networks

  • Estaran Tolosa J.
  • Renaudier J.
  • Rios Muller R.

We demonstrate that deep neural networks can be used to approximate the conditional distribution of a non-linear channel with memory. This distribution is then used in the BCJR algorithm to infer the unknown transmitted data. This procedure is validated experimentally in a IM/DD 3.2 km long transmission of 64 GBd PAM4 signal.

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