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,
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