End-to-End Learning of Geometrical Shaping Maximizing Generalized Mutual Information
Paper in proceedings, 2020

GMI-based end-to-end learning is shown to be highly nonconvex. We apply gradient descent initialized with Gray-labeled APSK constellations directly to the constellation coordinates. State-of-the-art constellations in 2D and 4D are found providing reach increases up to 26% w.r.t. to QAM.

Author

Kadir Gümüş

Eindhoven University of Technology

Alex Alvarado

Eindhoven University of Technology

Bin Chen

Eindhoven University of Technology

Christian Häger

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

Erik Agrell

Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems

Optical Fiber Communication Conference (OFC) 2020, OSA Technical Digest

W3D.4

Optical Fiber Communication Conference (OFC) 2020
San Diego, CA, USA,

Coding for terabit-per-second fiber-optical communications (TERA)

European Commission (EC), 2017-01-01 -- 2019-12-31.

Areas of Advance

Information and Communication Technology

Subject Categories

Telecommunications

Communication Systems

Signal Processing

DOI

10.1364/OFC-2020-W3D.4

ISBN

9781943580712

More information

Latest update

9/15/2020