Top Page | English | 简体中文 | 繁體中文 | 한국어 | 日本語
Monday, 12 March 2018, 10:24 HKT/SGT

Source: Fujitsu Ltd
Fujitsu Applies Deep Learning to Develop Estimation Technology for Optical Transmission Signal Parameters
Essential to building, operating and managing optical networks

TOKYO, Mar 12, 2018 - (JCN Newswire) - Fujitsu Laboratories Ltd., Fujitsu Laboratories of America, Inc., and Fujitsu R&D Center Co., Ltd. today announced the development of technology for a framework to estimate optical signal transmission parameters from optical receivers. The companies have embarked on this development to simplify the building, operating, and managing of optical networks.

The companies have now developed technology that uses deep learning that can be trained on parameters to avoid the impact of systemic errors in optical signal transmission in the course of learning to estimate optical transmission signal parameters, which is an issue unique to optical communication systems, including for symbol rate and optical signal to noise ratio (OSNR). The companies developed an experimental transmission system within Fujitsu Laboratories that emulates an optical network, and with about 10 thousand pieces of data verified that this technology could estimate OSNR with a measurement error of 1%, and could estimate modulation format and symbol rate with a measurement error of 5%.

When problems arise in building or operating an optical network, this technology now makes it possible to accomplish tasks in a matter of minutes that would take an expert several days using specialized measurement equipment. This will contribute to considerably easing the building, operation and management of networks.

Details of this technology will be announced at the Optical Networking and Communication Conference & Exhibition 2018 (OFC 2018), the world's largest international conference on fiber-optic communications, which is being held March 11-15 in San Diego.

Development Background

Communications traffic on the optical networks that sustain an ICT-powered society is expected to increase tremendously alongside the number of devices connected to the internet in the years ahead. In order to accommodate this volume of data, a number of new optical transmission technologies are being adopted one after another in optical networks, and it is believed that networks will become even more diverse and complex. Consequently, demand exists for technologies that will make it easier to build, operate and manage optical networks.


Previously, when building an optical network, or when problems arose in operating a network, it was necessary to send an expert in this field with expensive and specialized measurement equipment to a worksite, and conduct measurements and tests to determine the cause. In optical networks that aim to boost capacity and distance, the increasing complexity of types of optical transmission signals and device parameter settings means that building the network or fixing issues may require several days, leading to significant issues in quickly building and managing fiber-optic networks. As a result, demand has emerged for the development of technologies that can remotely monitor the status of optical networks in order to resolve these issues. There have been challenges, however, in measuring the information that network operators and managers need without relying on dedicated measurement devices due to the unique optical signal characteristics of newly-deployed optical transmission technologies.
Figure 1: Summary of the newly developed technology

About the Newly Developed Technology

Fujitsu Laboratories, Fujitsu Laboratories of America, and Fujitsu R&D Center have now developed technology to measure the optical signal transmission parameters (signal to noise ratio, modulation format, and symbol rate(1)) needed to build and operate a network from optically transmitted signals in remote optical receivers.

This newly developed technology trains a deep neural network by inputting the signals received by optical receivers into the network. By using the results of measurement equipment to provide supervisory labels, this technology trains the deep neural network to recreate the measurement results produced by the equipment, enabling it to estimate the optical signal transmission parameters. Since systemic errors can arise in signal characteristics such as laser frequency when an optically transmitted signal has been received, if the received data is used for training as-is, the neural network will be trained to specialize on erroneous states. This could increase measurement errors in estimates. As a way to counter this, the new technology virtually generates signals based on optically transmitted signals in varying states, for example, virtually generating multiple data with different laser frequencies, and then combining these to form the training dataset. In so doing, it becomes possible to reflect a variety of situations in the training results, enabling this technology to minimize measurement errors in estimates.
Figure 2: Summary of the newly developed technology


Fujitsu Laboratories, Fujitsu Laboratories of America, and Fujitsu R&D Center conducted a trial by building a simulated transmission system that models an actual optical network. The trial verified that with 10 thousand pieces of data this technology was capable of estimating OSNR with a measurement error of 1%, and the modulation format and symbol rate with a measurement error of 5%. Using this technology, it is expected that tasks that took an expert using specialized measurement devices several days to complete can now be estimated remotely in a matter of minutes.

Future Plans

Going forward, Fujitsu Laboratories, Fujitsu Laboratories of America, and Fujitsu R&D Center will proceed with trials in an actual network environment, with the goal of commercializing this technology in fiscal 2019 or beyond. The companies will additionally continue investigation aimed at automatic operation of optical networks.

(1) Symbol rate
The speed at which amplitude and phase information can be switched when modulating electrically transmitted data through light.
(2) Digital coherent receiver
A receiver that can handle optical signal phase information with stability, which was an issue with previous coherent receivers, by applying digital signal processing to the optical communication.

About Fujitsu Laboratories

Founded in 1968 as a wholly owned subsidiary of Fujitsu Limited, Fujitsu Laboratories Ltd. is one of the premier research centers in the world. With a global network of laboratories in Japan, China, the United States and Europe, the organization conducts a wide range of basic and applied research in the areas of Next-generation Services, Computer Servers, Networks, Electronic Devices and Advanced Materials. For more information, please see:

About Fujitsu Ltd

Fujitsu is the leading Japanese information and communication technology (ICT) company, offering a full range of technology products, solutions, and services. Approximately 140,000 Fujitsu people support customers in more than 100 countries. We use our experience and the power of ICT to shape the future of society with our customers. Fujitsu Limited (TSE: 6702) reported consolidated revenues of 4.1 trillion yen (US $39 billion) for the fiscal year ended March 31, 2018.

For more information, please see
This release at

Fujitsu Laboratories Ltd.

Fujitsu Limited
Public and Investor Relations
Tel: +81-3-6252-2176

Mar 12, 2018 10:24 HKT/SGT
Source: Fujitsu Ltd

Fujitsu Ltd (TSE: 6702)

Topic: Press release summary
Sectors: Telecoms, Electronics, Enterprise IT
From the Asia Corporate News Network

Copyright © 2019 ACN Newswire. All rights reserved. A division of Asia Corporate News Network.

Figure 1: Summary of the newly developed technology
View Image
Figure 2: Summary of the newly developed technology
View Image
Fujitsu Ltd Links

Fujitsu Ltd
Mar 13, 2019 18:38 HKT/SGT
Fujitsu Formulates "Fujitsu Group AI Commitment," Demonstrating Dedication to Safe and Secure Use of AI
Mar 11, 2019 10:31 HKT/SGT
Fujitsu Completes Image Processing Field Trial to Support Restoration of Earthquake-Damaged Kumamoto Castle
Mar 11, 2019 10:07 HKT/SGT
Yamaha Motor and Fujitsu Begin IoT-based Field Trial to Improve Sailing Performance for 470 Class Events
Mar 4, 2019 10:05 HKT/SGT
Fujitsu Offers Online Biometric Authentication Service for TEPCO Systems
Mar 1, 2019 12:58 HKT/SGT
Fujitsu Limited Announces Recruitment Plans
Mar 1, 2019 11:55 HKT/SGT
Fujitsu Successfully Develops Technology to Miniaturize High-Sensitivity Infrared Cameras for Autonomous Ship Navigation
Feb 27, 2019 09:13 HKT/SGT
Fujitsu and Sony Global Education Initiate Blockchain Field Trials for Course Records and Transcript Management
Feb 18, 2019 10:24 HKT/SGT
Fujitsu Receives Order for Massively Parallel Supercomputer System from The University of Tokyo
Feb 13, 2019 17:01 HKT/SGT
Fujitsu Launches "Healthcare Personal service Platform" to Manage Health and Medical Information
Feb 12, 2019 10:50 HKT/SGT
Sapporo Medical University and Fujitsu in Joint R&D for Diabetes Treatment that Uses AI-based Machine Learning
More news >>
 News Alerts
Copyright © 2019 ACN Newswire - Asia Corporate News Network
Home | About us | Services | Partners | Events | Login | Contact us | Privacy Policy | Terms of Use | RSS
US: +1 800 291 0906 | Beijing: +86 400 879 3881 | Hong Kong: +852 2217 2912 | Singapore: +65 6304 8926 | Tokyo: +81 3 6721 7212

Connect With us: