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.

nearMAP detector

factor graphs

nonlinear compensation

optical communications

Digital backpropagation

Författare

Naga Vishnukanth Irukulapati

Signaler och system, Kommunikationssystem, informationsteori och antenner, Kommunikationssystem

D. Marsella

Scuola Superiore Sant'Anna di Studi Universitari e di Perfezionamento

Nokia Corporation

Pontus Johannisson

Chalmers, Mikroteknologi och nanovetenskap (MC2), Fotonik

Erik Agrell

Signaler och system, Kommunikationssystem, informationsteori och antenner, Kommunikationssystem

M. Secondini

Scuola Superiore Sant'Anna di Studi Universitari e di Perfezionamento

Henk Wymeersch

Signaler och system, Kommunikationssystem, informationsteori och antenner, Kommunikationssystem

Journal of Lightwave Technology

0733-8724 (ISSN)

Vol. 34 566-572 7247642

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier

Telekommunikation

Kommunikationssystem

Signalbehandling

Infrastruktur

C3SE (Chalmers Centre for Computational Science and Engineering)

DOI

10.1109/JLT.2015.2477462