Paper Abstract and Keywords |
Presentation |
2021-01-14 15:45
Automatic design of constellations and discriminant boundary by auto-encoder type machine learning Yudai Goto, Masanori Hanawa (Univ. of Yamanashi) OCS2020-32 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Autoencoder (AE), a type of machine learning, was applied to the automatic design of signal constellations and discriminant boundary for coherent optical fiber transmission systems. A realistic single-wavelength, point-to-point single-mode fiber coherent optical transmission system with considering both wavelength dispersion and self-phase modulation is inserted in the middle of the AE. It is shown that the transmitter of the AE automatically constructs an encoder with a constellation map corresponding to noise, wavelength dispersion and self-phase modulation given during AE learning, and the receiver automatically constructs a decoder with a linear discriminant boundary. It is also shown that setting an appropriate signal-to-noise power ratio (SNR) during learning stabilizes the learning results and improves the BER characteristics, and that the BER characteristics obtained by AE are close to those of 16QAM with wavelength dispersion and self-phase modulation compensated by the back propagation method. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Coherent transmission / Machine learning / Autoencoder / Design of constellations / Discriminant boundary / / / |
Reference Info. |
IEICE Tech. Rep., vol. 120, no. 309, OCS2020-32, pp. 27-32, Jan. 2021. |
Paper # |
OCS2020-32 |
Date of Issue |
2021-01-07 (OCS) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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OCS2020-32 |
Conference Information |
Committee |
OCS CS |
Conference Date |
2021-01-14 - 2021-01-15 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Core and metro system, Submarine telecommunications system, Optical access system and next generation PON, Ethernet, Optical Transport Network (OTN), Transmission monitoring and control, Design and tool for optical transmission system, Co-operation between optical and mobile, etc. |
Paper Information |
Registration To |
OCS |
Conference Code |
2021-01-OCS-CS |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Automatic design of constellations and discriminant boundary by auto-encoder type machine learning |
Sub Title (in English) |
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Keyword(1) |
Coherent transmission |
Keyword(2) |
Machine learning |
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Autoencoder |
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Design of constellations |
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Discriminant boundary |
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1st Author's Name |
Yudai Goto |
1st Author's Affiliation |
University of Yamanashi (Univ. of Yamanashi) |
2nd Author's Name |
Masanori Hanawa |
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University of Yamanashi (Univ. of Yamanashi) |
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Speaker |
Author-1 |
Date Time |
2021-01-14 15:45:00 |
Presentation Time |
25 minutes |
Registration for |
OCS |
Paper # |
OCS2020-32 |
Volume (vol) |
vol.120 |
Number (no) |
no.309 |
Page |
pp.27-32 |
#Pages |
6 |
Date of Issue |
2021-01-07 (OCS) |
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