Over-the-fiber Digital Predistortion Using Reinforcement Learning
Paper in proceeding, 2021

We demonstrate, for the first time, experimental over-the-fiber training of transmitter neural networks (NNs) using reinforcement learning. Optical back-to-back training of a novel NN-based digital predistorter outperforms arcsine-based predistortion with up to 60% bit-error-rate reduction.

Author

Jinxiang Song

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Zonglong He

Chalmers, Microtechnology and Nanoscience (MC2), Photonics

Christian Häger

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Magnus Karlsson

Chalmers, Microtechnology and Nanoscience (MC2), Photonics

Alexandre Graell I Amat

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Henk Wymeersch

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Jochen Schröder

Chalmers, Microtechnology and Nanoscience (MC2), Photonics

2021 European Conference on Optical Communication, ECOC 2021

9605972
978-1-6654-3868-1 (ISBN)

47th European Conference on Optical Communications, ECOC 2021
Bordeaux, France,

Unlocking the Full-dimensional Fiber Capacity

Knut and Alice Wallenberg Foundation (KAW 2018.0090), 2019-07-01 -- 2024-06-30.

Multi-dimensional Signal Processing with Frequency Comb Transceivers

Swedish Research Council (VR) (2018-03701), 2018-12-01 -- 2021-12-31.

Subject Categories

Telecommunications

Other Physics Topics

Bioinformatics (Computational Biology)

DOI

10.1109/ECOC52684.2021.9605972

ISBN

9781665438681

More information

Latest update

1/3/2024 9