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

Chalmers, 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

Chalmers, Signaler och system, Kommunikationssystem, informationsteori och antenner, Kommunikationssystem

M. Secondini

Scuola Superiore Sant'Anna di Studi Universitari e di Perfezionamento

Henk Wymeersch

Chalmers, Signaler och system, Kommunikationssystem, informationsteori och antenner, Kommunikationssystem

Journal of Lightwave Technology

0733-8724 (ISSN)

Vol. 34 2 566-572 7247642

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier

Telekommunikation

Kommunikationssystem

Signalbehandling

Infrastruktur

C3SE (Chalmers Centre for Computational Science and Engineering)

DOI

10.1109/JLT.2015.2477462