Stochastic Digital Backpropagation with Residual Memory Compensation
Journal article, 2016

Stochastic digital backpropagation (SDBP) is an extension of digital backpropagation (DBP) and is based on the maximum a posteriori principle. SDBP takes into account noise from the optical amplifiers in addition to handling deterministic linear and nonlinear impairments. The decisions in SDBP are taken on a symbol-by-symbol (SBS) basis, ignoring any residual memory, which may be present due to non-optimal processing in SDBP. In this paper, we extend SDBP to account for memory between symbols. In particular, two different methods are proposed: a Viterbi algorithm (VA) and a decision directed approach. Symbol error rate (SER) for memory-based SDBP is significantly lower than the previously proposed SBS-SDBP. For inline dispersion-managed links, the VA-SDBP has up to 10 and 14 times lower SER than DBP for QPSK and 16-QAM, respectively.

nonlinear compensation

factor graphs

nearMAP detector

Digital backpropagation

optical communications

Author

Naga Vishnukanth Irukulapati

Chalmers, Signals and Systems, Communication, Antennas and Optical Networks

D. Marsella

Sant'Anna School of Advanced Studies (SSSUP)

Nokia

Pontus Johannisson

Chalmers, Microtechnology and Nanoscience (MC2), Photonics

Erik Agrell

Chalmers, Signals and Systems, Communication, Antennas and Optical Networks

M. Secondini

Sant'Anna School of Advanced Studies (SSSUP)

Henk Wymeersch

Chalmers, Signals and Systems, Communication, Antennas and Optical Networks

Journal of Lightwave Technology

0733-8724 (ISSN) 1558-2213 (eISSN)

Vol. 34 2 566-572 7247642

MIMOptics: Multi-mode coherent fiber-optical communications

Swedish Research Council (VR) (2013-5642), 2014-01-01 -- 2017-12-31.

Areas of Advance

Information and Communication Technology

Subject Categories

Telecommunications

Communication Systems

Signal Processing

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

DOI

10.1109/JLT.2015.2477462

More information

Latest update

8/26/2019