English

Improving the Bootstrap of Blind Equalizers with Variational Autoencoders

Signal Processing 2023-01-18 v1 Information Theory Machine Learning math.IT

Abstract

We evaluate the start-up of blind equalizers at critical working points, analyze the advantages and obstacles of commonly-used algorithms, and demonstrate how the recently-proposed variational autoencoder (VAE) based equalizers can improve bootstrapping.

Keywords

Cite

@article{arxiv.2301.06576,
  title  = {Improving the Bootstrap of Blind Equalizers with Variational Autoencoders},
  author = {Vincent Lauinger and Fred Buchali and Laurent Schmalen},
  journal= {arXiv preprint arXiv:2301.06576},
  year   = {2023}
}

Comments

Accepted and to be presented at the Optical Fiber Communication Conference (OFC) 2023

R2 v1 2026-06-28T08:12:50.388Z