Blind Radius Directed Equalizer with Likelihood-based Selection for Probabilistically Shaped and High Order QAM

摘要

We propose a novel equalization algorithm for high order and shaped M-QAM. Our blind RDE utilizes conditional filter updates based on the assignment likelihood of amplitude levels. Compared to traditional RDE we demonstrate a convergence rate of > 99% for up to 93% higher DGD.