How to Increase the Achievable Information Rate by Per-Channel Dispersion Compensation
TL;DR: It is shown 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) by resorting to the frequency-resolved logarithmic perturbation model.
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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01 Jan 2020
TL;DR: The chapter starts with a brief introduction of some basic concepts of information theory, introducing the notion of channel capacity and focusing on some issues that are particularly relevant for the optical fiber channel: how to deal with waveform channels, with memory, and with the unavailability of an exact channel model.
Abstract: The chapter starts with a brief introduction of some basic concepts of information theory, introducing the notion of channel capacity and focusing on some issues that are particularly relevant for the optical fiber channel but often only briefly touched in classical textbooks on information theory: how to deal with waveform channels, with memory, and with the unavailability of an exact channel model. The optical fiber channel is then described by presenting the main equations governing the propagation of light in optical fibers and by discussing a few different approximated channel models that can be deployed for an information theoretical analysis, providing different trade-offs between accuracy and complexity. The last part of the chapter is devoted to the study of the capacity of the optical fiber channel, providing both easy-to-compute capacity bounds and more accurate but complex bounding techniques, and considering different scenarios and link configurations. Future perspectives and open problems are finally discussed.
10 citations
Posted Content•
TL;DR: In this article, the authors investigated the 4D 64-ary polarisation-ringswitching format in dispersion-managed systems and showed a reach increase of $25\%$ with respect to PM-8QAM.
Abstract: The recently introduced 4D 64-ary polarisation-ring-switching format is investigated in dispersion-managed systems. Numerical simulations show a reach increase of $25\%$ with respect to PM-8QAM. This gain is achieved from the nonlinear tolerance of the format and a 4D demapper using correlated noise assumptions.
References
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Book•
01 Jan 1989TL;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.
Abstract: Nonlinear fiber optics concerns with the nonlinear optical phenomena occurring inside optical fibers. Although the field ofnonlinear optics traces its beginning to 1961, when a ruby laser was first used to generate the second-harmonic radiation inside a crystal [1], the use ofoptical fibers as a nonlinear medium became feasible only after 1970 when fiber losses were reduced to below 20 dB/km [2]. Stimulated Raman and Brillouin scatterings in single-mode fibers were studied as early as 1972 [3] and were soon followed by the study of other nonlinear effects such as self- and crossphase modulation and four-wave mixing [4]. By 1989, the field ofnonlinear fiber optics has advanced enough that a whole book was devoted to it [5]. This book or its second edition has been translated into Chinese, Japanese, and Russian languages, attesting to the worldwide activity in the field of nonlinear fiber optics.
15,770 citations
4,028 citations
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.
Abstract: We describe a method to estimate the capacity limit of fiber-optic communication systems (or ?fiber channels?) based on information theory. This paper is divided into two parts. Part 1 reviews fundamental concepts of digital communications and information theory. We treat digitization and modulation followed by information theory for channels both without and with memory. We provide explicit relationships between the commonly used signal-to-noise ratio and the optical signal-to-noise ratio. We further evaluate the performance of modulation constellations such as quadrature-amplitude modulation, combinations of amplitude-shift keying and phase-shift keying, exotic constellations, and concentric rings for an additive white Gaussian noise channel using coherent detection. Part 2 is devoted specifically to the "fiber channel.'' We review the physical phenomena present in transmission over optical fiber networks, including sources of noise, the need for optical filtering in optically-routed networks, and, most critically, the presence of fiber Kerr nonlinearity. We describe various transmission scenarios and impairment mitigation techniques, and define a fiber channel deemed to be the most relevant for communication over optically-routed networks. We proceed to evaluate a capacity limit estimate for this fiber channel using ring constellations. Several scenarios are considered, including uniform and optimized ring constellations, different fiber dispersion maps, and varying transmission distances. We further present evidences that point to the physical origin of the fiber capacity limitations and provide a comparison of recent record experiments with our capacity limit estimation.
2,135 citations
"How to Increase the Achievable Info..." refers background in this paper
...7] becomes the predominant nonlinear impairment [1], [16]–[18]....
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...TRANSMISSION over long-haul fiber-optic systems is predominantly impaired by chromatic dispersion (CD), Kerr nonlinearity, and amplified spontaneous emission (ASE) noise [1]....
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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).
Abstract: Optical fiber transmission is impacted by linear and nonlinear impairments. We study the use of digital backpropagation (BP) in conjunction with coherent detection to jointly mitigate dispersion and fiber nonlinearity. We propose a noniterative asymmetric split-step Fourier method (SSFM) for solving the inverse nonlinear Schrodinger equation (NLSE). Using simulation results for RZ-QPSK transmitted over terrestrial systems with inline amplification and dispersion compensation, we obtain heuristics for the step size and sampling rate requirements, as well as the optimal dispersion map.
1,061 citations
"How to Increase the Achievable Info..." refers background in this paper
...,[30], [31]) or the transmission line [4], [32]....
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Posted Content•
TL;DR: In this article, the authors show that the capacity of the nonlinear information channel of an optical fiber does not grow indefinitely with increasing signal power, but has a maximal value, which is the same as that of a linear channel with multiplicative noise.
Abstract: The exponential growth in the rate at which information can be communicated through an optical fiber is a key element in the so called information revolution. However, like all exponential growth laws, there are physical limits to be considered. The nonlinear nature of the propagation of light in optical fiber has made these limits difficult to elucidate. Here we obtain basic insights into the limits to the information capacity of an optical fiber arising from these nonlinearities. The key simplification lies in relating the nonlinear channel to a linear channel with multiplicative noise, for which we are able to obtain analytical results. In fundamental distinction to the linear additive noise case, the capacity does not grow indefinitely with increasing signal power, but has a maximal value. The ideas presented here have broader implications for other nonlinear information channels, such as those involved in sensory transduction in neurobiology. These have been often examined using additive noise linear channel models, and as we show here, nonlinearities can change the picture qualitatively.
604 citations