[ECOC 2020] End-to-End Deep Learning Optimization for Phase-Noise Robust Optical Communications

Veeru Talreja, a former intern at MERL, presenting his paper entitled “End-to-End Deep Learning Optimization for Phase-Noise Robust Optical Communications“ for the European Conference on Optical Communications (ECOC), held in December 2020. The paper is a collaborative work with Toshiaki Koike-Akino, Ye Wang, David Millar, Keisuke Kojima, and Kieran Parsons at MERL Abstract: We propose an end-to-end deep learning model for phase noise-robust optical communications. A tail-biting convolutional embedding la