End-to-End Learning of Joint Geometric and Probabilistic Constellation Shaping

作者：Vahid Aref, Mathieu Chagnon · 年份：2022 · DOI：10.1364/ofc.2022.w4i.3 · 被引用次数：19 · 研究领域：Optical Network Technologies、Wireless Signal Modulation Classification、graph theory and CDMA systems

We present a novel autoencoder-based learning of joint geometric and probabilistic constellation shaping for coded-modulation systems. It can maximize either the mutual information (for symbol-metric decoding) or the generalized mutual information (for bit-metric decoding).