Stochastic Digital Backpropagation with Residual Memory Compensation
Artikel i vetenskaplig tidskrift, 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

Författare

Naga Vishnukanth Irukulapati

Chalmers, Signaler och system, Kommunikation, Antenner och Optiska Nätverk

D. Marsella

Scuola Superiore Sant'Anna (SSSUP)

Nokia

Pontus Johannisson

Chalmers, Mikroteknologi och nanovetenskap, Fotonik

Erik Agrell

Chalmers, Signaler och system, Kommunikation, Antenner och Optiska Nätverk

M. Secondini

Scuola Superiore Sant'Anna (SSSUP)

Henk Wymeersch

Chalmers, Signaler och system, Kommunikation, Antenner och Optiska Nätverk

Journal of Lightwave Technology

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

Vol. 34 2 566-572 7247642

MIMOptics: Multimod koherent fiberoptisk kommunikation

Vetenskapsrådet (VR) (2013-5642), 2014-01-01 -- 2017-12-31.

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier

Telekommunikation

Kommunikationssystem

Signalbehandling

Infrastruktur

C3SE (Chalmers Centre for Computational Science and Engineering)

DOI

10.1109/JLT.2015.2477462

Mer information

Senast uppdaterat

2019-08-26