mlsanityData to 7 Oct 2026

Improving the Bootstrap of Blind Equalizers with Variational Autoencoders

arXiv 2301.06576 ↗First posted 16 Jan 2023eess.SP cs.IT cs.LGcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 1 of its 9 references that are in the map. First posted on arXiv 16 Jan 2023.

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1 of 9 references.

References · 1

  1. 2022Blind Equalization and Channel Estimation in Coherent Optical Communications Using Variational Autoencoderscited by 7

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Cited by year

Citing papers per year: 2024: 1; 2025: 1.

2 papers.

  1. 2024Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communicationscited by 0
  2. 2025Novel Phase-Noise-Tolerant Variational-Autoencoder-Based Equalization Suitable for Space-Division-Multiplexed Transmissioncited by 0