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Machine Learning For Optical Communication Systems

Optical Communications

NIST will hold a workshop at the Boulder Colorado Laboratories to discuss the role of machine learning (ML) in optical communication systems. Optical communication systems are increasingly used closer to the network edge and are expected to find use in new applications that require more intelligent functionality. Optical networks are needed to address the high speeds and low latency of 5G wireless networks. The analog nature of optical transmission and the complexity of operation and management remain an impediment to greater use of software controls. Furthermore, optical systems are running up against spectral density limits that threaten traditional capacity-based scaling. New efficiency-based scaling methods are needed to further improve the cost/bit/s without relying on capacity improvements alone. Artificial intelligence (AI) and machine learning provide a new direction with the potential to both enable wider use of software controls and to further optimize the efficiency of optical systems across multiple dimensions. Reference data sets for ML would improve functionality and operability across industry further enabling scaling and efficiency.  This workshop seeks to identify and develop applications of AI, and ML in the context of accelerating the use of software-based networking in optical systems for improved performance and scalability. Paths to realizing reference training data sets for ML in optical communications systems including needs for new or different metrology will be examined. Workshop outcomes include a white paper for a plan and path to develop and disseminate reference data sets for ML training and applications to open and programmable optical communication systems, as well as a working group to further develop these ideas.


Just released on March 27th , 2020 for public dissemination a NIST Special Publication Series 2100 White Paper. The publication titled: “Summary: Workshop on Machine Learning for Optical Communication Systems” provides a summary and outcomes from the NIST workshop on Machine Learning For Optical Communication Systems that was hosted on August 2nd, 2019 by the NIST Communications Technology Laboratory (CTL) hosted in partnership with the Laboratory for Information Technologies (ITL). This workshop brought together industry, academia, and government to discuss the roll of artificial intelligence and machine learning in optical communication systems. This NIST special Publication White Paper provides information reflecting the presentations and break-out session discussions which took place during the workshop. The publication also provides a consolidation of important themes related to the topic of machine learning and its application to optical communications systems to address important use cases such as 5G communications, network management, resiliency, scalability and requirements for data sets for machine learning algorithms in the context of optical communications systems. References relevant to information contained in the Special Publication are also provided.

Presentation Slides from August 2, 2019 Workshop on Machine Learning for Optical Communications Systems

Agenda (Printable PDF)

Workshop on Machine Learning For Optical Comm Systems
Friday, August 2nd, 2019
NIST Boulder, Colorado Campus

7:00 – 8:00 Continental Breakfast
8:00 – 8:30 Welcome and Opening Remarks
8:30 – 9:15 Keynote: “Machine Learning for Optical Communication Systems”

  • Speaker: Massimo Tornatore (Politecnico di Milano, Italy)

9:15 – 9:30 Coffee Break
9:30 – 11:30 Morning Talks (35 min each + 5 min questions)

  • Topic 1: “What data matters in optical communications”
    • Speaker: Dr. Uiara Celine (Technical University of Denmark)
  • Topic 2: “Machine learning models”
    • Speaker: Joao Pedro (Infinera)
  • Topic 3: “Data starved systems”
    • Speaker: Michael Majurski (NIST)

11:30-12 pm Morning Speaker Panel- Discussion to address questions from morning talks. (Panel Moderator: Dan Kilper)

12:00 – 13:00 Lunch (available for registered attendees only)
13:00 – 14:00 Afternoon speaker panel facilitated by 3 Flash Talks/ 5 min each.
(Panel Moderator: Abdella Battou)

  • Flash Talk 1: “Possible data sets coming from coherent transponders”
    • Speaker: Jim Westdorp (Ciena)
  • Flash Talk 2: “Data from ROADM / optical layer”
    • Speaker: Dan Kilper (University of Arizona)
  • Flash Talk 3: “Cross-layer/multi-vendor end-to-end networking”
    • Speaker: Jesse Simsarian (Nokia-Bell Labs)

14:00 – 15:00 Breakout groups lead by flash talk speakers
15:00 – 15:15 Coffee Break
15:15 – 16:00 Readout from breakout groups
16:00 – 16:30 Discussion on draft white paper
16:30 – 17:00 Next steps: working groups and follow up workshop

  • Signup sheet for working group.

A block of room have been arranged at the Best Western Plus Boulder Inn

online code:

•        Group code: call 800-233-8469 and reference code " NIST Machine Learning "

•        Arrival Date: Thursday, August 1, 2019

•        Departure Date: Saturday, August 3, 2019

•        Group Rates: $174 for a room with one king bed

Book by July 1, 2019 in order to guarantee the rate.

If you are not registered, you will not be allowed on site.  Registered attendees will receive security and campus instructions prior to the workshop.

NON U.S. CITIZENS PLEASE NOTE:  All foreign national visitors who do not have permanent resident status and who wish to register for the above meeting must supply additional information. Failure to provide this information prior to arrival will results, at a minimum, in significant delays in entering the facility. Authority to gather this information is derived from United States Department of Commerce Department Administrative Order (DAO) number 207-12.

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Created May 3, 2019, Updated October 13, 2021