Advanced DSP for Coherent Optical Fiber Communication

Jian Zhao,Yaping Liu,Tianhua Xu

doi:10.3390/app9194192

Jian Zhao, Yaping Liu + Show 1 more

Open Access

https://doi.org/10.3390/app9194192

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Journal: Applied sciences	Publication Date: Oct 8, 2019
Citations: 41	License type: CC BY 4.0

Affiliation: Tianjin University, University of Warwick

Abstract

In this paper, we provide an overview of recent progress on advanced digital signal processing (DSP) techniques for high-capacity long-haul coherent optical fiber transmission systems. Not only the linear impairments existing in optical transmission links need to be compensated, but also, the nonlinear impairments require proper algorithms for mitigation because they become major limiting factors for long-haul large-capacity optical transmission systems. Besides the time domain equalization (TDE), the frequency domain equalization (FDE) DSP also provides a similar performance, with a much-reduced computational complexity. Advanced DSP also plays an important role for the realization of space division multiplexing (SDM). SDM techniques have been developed recently to enhance the system capacity by at least one order of magnitude. Some impressive results have been reported and have outperformed the nonlinear Shannon limit of the single-mode fiber (SMF). SDM introduces the space dimension to the optical fiber communication. The few-mode fiber (FMF) and multi-core fiber (MCF) have been manufactured for novel multiplexing techniques such as mode-division multiplexing (MDM) and multi-core multiplexing (MCM). Each mode or core can be considered as an independent degree of freedom, but unfortunately, signals will suffer serious coupling during the propagation. Multi-input–multi-output (MIMO) DSP can equalize the signal coupling and makes SDM transmission feasible. The machine learning (ML) technique has attracted worldwide attention and has been explored for advanced DSP. In this paper, we firstly introduce the principle and scheme of coherent detection to explain why the DSP techniques can compensate for transmission impairments. Then corresponding technologies related to the DSP, such as nonlinearity compensation, FDE, SDM and ML will be discussed. Relevant techniques will be analyzed, and representational results and experimental verifications will be demonstrated. In the end, a brief conclusion and perspective will be provided.

Highlights

With the development of Erbium doped fiber amplifier (EDFA), wavelength division multiplexing (WDM), dispersion management and optical fiber nonlinearity compensation technologies, optical fiber communication capacity has been rapidly improved over the past few decades
Winzer et al reported a 56 Gbaud, 224 Gbit/s polarization-division multiplexed (PDM)-QPSK 2500 km transmission experiment assisted by coherent detection with all linear impairments compensation
The use of a correlated backpropagation (CBP) for nonlinearity compensation has been reported in a 112 Gbit/s PDM-QPSK system [37], and the step size of digital backward propagation (DBP) can be increased by 70%

Summary

Introduction

With the development of Erbium doped fiber amplifier (EDFA), wavelength division multiplexing (WDM), dispersion management and optical fiber nonlinearity compensation technologies, optical fiber communication capacity has been rapidly improved over the past few decades. The research on high-order modulation formats has increased the transmission capacity and spectral efficiency (SE) of optical fibers. The complex field of the received signal can be completely acquired, and the linear transmission impairments, such as CD and PMD, can be fully compensated by using static and adaptive DSP. Compensation of nonlinear impairments brings about an increase in the fundamental capacity limit for fiber transmission, which is an important research area for coherent optical communications. Machine learning (ML) techniques have become one of the most promising disciplines and is beneficial to optical fiber communication applications such as nonlinearity mitigation, optical performance monitoring (OPM), carrier recovery, in-band optical signal-to-noise ratio (OSNR) estimation and modulation format classification, and especially, advanced DSP. A brief conclusion with our perspectives is provided in the last section

Principle of Coherent Detection and Linear Impairments Equalization

Nonlinearity

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Findings

Conclusions