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Open AccessJournal ArticleDOI

How to Increase the Achievable Information Rate by Per-Channel Dispersion Compensation

TLDR
In this paper, the authors show that per-channel dispersion compensation increases the frequency correlation of the distortions induced by XPM over the channel bandwidth, making them more similar to a conventional phase noise.
Abstract
Deploying periodic inline chromatic dispersion compensation enables reducing the complexity of the digital back propagation (DBP) algorithm. However, compared with nondispersion-managed (NDM) links, dispersion-managed (DM) ones suffer a stronger cross-phase modulation (XPM). Utilizing per-channel dispersion-managed (CDM) links (e.g., using fiber Bragg grating) allows for a complexity reduction of DBP, while abating XPM compared to DM links. In this paper, we show for the first time that CDM links enable also a more effective XPM compensation compared to NDM ones, allowing a higher achievable information rate (AIR). This is explained by resorting to the frequency-resolved logarithmic perturbation model and showing that per-channel dispersion compensation increases the frequency correlation of the distortions induced by XPM over the channel bandwidth, making them more similar to a conventional phase noise. We compare the performance (in terms of the AIR) of a DM, an NDM, and a CDM link, considering two types of mismatched receivers: one neglects the XPM phase distortion and the other compensates for it. With the former, the CDM link is inferior to the NDM one due to an increased in-band signal–noise interaction. However, with the latter, a higher AIR is obtained with the CDM link than with the NDM one owing to a higher XPM frequency correlation. The DM link has the lowest AIR for both receivers because of a stronger XPM.

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Journal ArticleDOI

Improved Lower Bounds on Mutual Information Accounting for Nonlinear Signal-Noise Interaction

TL;DR: In this paper, lower bounds on mutual information were computed using an auxiliary backward channel, which has not been previously considered in the context of fiber-optic communications, which can be explained by the ability of SDBP to account for nonlinear signal-noise interactions.
Proceedings ArticleDOI

Four-dimensional polarization-ring-switching for dispersion-managed optical fibre systems

TL;DR: The recently introduced 4D 64-ary polarisation-ring-switching format is investigated in dispersion-managed systems and numerical simulations show a reach increase of $25\%$ with respect to PM-8QAM.
References
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Book

Nonlinear Fiber Optics

TL;DR: The field of nonlinear fiber optics has advanced enough that a whole book was devoted to it as discussed by the authors, which has been translated into Chinese, Japanese, and Russian languages, attesting to the worldwide activity in the field.
Book

Probability, random variables and stochastic processes

TL;DR: This chapter discusses the concept of a Random Variable, the meaning of Probability, and the axioms of probability in terms of Markov Chains and Queueing Theory.
Journal ArticleDOI

Capacity Limits of Optical Fiber Networks

TL;DR: In this article, the capacity limit of fiber-optic communication systems (or fiber channels?) is estimated based on information theory and the relationship between the commonly used signal to noise ratio and the optical signal-to-noise ratio is discussed.
Journal ArticleDOI

Compensation of Dispersion and Nonlinear Impairments Using Digital Backpropagation

TL;DR: In this article, the use of digital backpropagation (BP) in conjunction with coherent detection to jointly mitigate dispersion and fiber nonlinearity is studied. But the authors focus on the noniterative asymmetric split-step Fourier method (SSFM) for solving the inverse nonlinear Schrodinger equation (NLSE).
Journal ArticleDOI

Nonlinear limits to the information capacity of optical fibre communications.

TL;DR: This work uses a key simplification to investigate the theoretical limits to the information capacity of an optical fibre arising from these nonlinearities and relates the nonlinear channel to a linear channel with multiplicative noise, for which it is able to obtain analytical results.
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