An unsupervised learning approach based on expectation maximization is proposed to obtain the parameters of a soft decision forward error correction decoding metric for probabilistic shaping. The algorithm depends only on the channel observations and does not require transmitted data.
@article{arxiv.1806.10062,
title = {Blind Decoding-Metric Estimation for Probabilistic Shaping via Expectation Maximization},
author = {Fabian Steiner and Patrick Schulte and Georg Böcherer},
journal= {arXiv preprint arXiv:1806.10062},
year = {2018}
}