Experimental Demonstration of Geometrically-Shaped Constellations Tailored to the Nonlinear Fibre Channel

A geometrically-shaped 256-QAM constellation, tailored to the nonlinear optical fibre channel, is experimentally demonstrated. The proposed constellation outperforms both uniform and AWGN-tailored 256-QAM, as it is designed to optimise the trade-off between shaping gain, nonlinearity and transceiver impairments

Candidate technologies for high-capacity optical communication systems

The practicalities in designing high-capacity optical communication systems are described. With a given perspective on the present and future technologies, we cover the transceiver design and optical amplifier technologies to maximize optical fiber capacity. OCIS codes:

Achievable rate degradation of ultra-wideband coherent fiber communication systems due to stimulated Raman scattering

As the bandwidths of optical communication systems are increased to maximize channel capacity, the impact of stimulated Raman scattering (SRS) on the achievable information rates (AIR) in ultra-wideband coherent WDM systems becomes significant, and is investigated in this work, for the first time. By modifying the GN-model to account for SRS, it is possible to derive a closed-form expression that predicts the optical signal-to-noise ratio of all channels at the receiver for bandwidths of up to 15 THz, which is in excellent agreement with numerical calculations. It is shown that, with fixed modulation and coding rate, SRS leads to a drop of approximately 40% in achievable information rates for bandwidths higher than 15 THz. However, if adaptive modulation and coding rates are applied across the entire spectrum, this AIR reduction can be limited to only 10%

The Benefits of Using the S-Band in Optical Fiber Communications and How to Get There

The throughput gains of extending the optical transmission bandwidth to the S+C+L-band are quantified using a Gaussian Noise model that accounts for inter-channel stimulated Raman scattering (ISRS). The impact of potential ISRS mitigation strategies, such as dynamic gain equalization and power optimization, are investigated

Modeling and mitigation of fiber nonlinearity in wideband optical signal transmission [Invited]

The adoption of open optical networks (OONs) requires the development of open and effective network planning tools, enabling the use of multi-vendor or white-box transport solutions. Such tools for studying and planning optical networks must be able to take into account the physical layer impairments, including fiber nonlinearity. The use of wideband wavelength division multiplexing in OONs, with channel frequencies extending across the short, conventional, and long bands and beyond, offers a pathway to increasing data rates through the installed fiber infrastructure. However, achievable information rates are limited by the resulting signal distortion due to fiber nonlinearity as signal bandwidths are increased, in particular, inter-channel stimulated Raman scattering (ISRS). In this paper, we describe the nonlinear effects observed in wideband transmission systems, and review recently developed analytical tools, based on the Gaussian noise (GN) model of nonlinear interference with the inclusion of ISRS. Using the ISRS GN model, we assess the impact of fiber nonlinearity on the achievable information rates in transmission systems with bandwidths of up to 12 THz. We demonstrate the use of the model in the optimization of launch power spectral profiles for a variety of dynamic gain equalizer arrangements in a 1000 km standard single-mode fiber link, using particle swarm optimization and the steepest descent algorithm. Such nonlinear models and optimization methods could be applied in OON planning tools, for example, in optical link emulators to estimate quality-of-transmission and data throughput, and in impairment-aware software-defined network control and management

A Closed-Form Expression to Evaluate Nonlinear Interference in Raman-Amplified Links

An accurate, closed-form expression to evaluate the nonlinear interference (NLI) noise power in Nyquist-spaced, coherent optical communication systems using backward-pumped Raman amplification is presented. This enables rapid estimation of the signal-to-noise ratio (SNR) and avoids the need of integral evaluations and split-step simulations. The accuracy of the proposed formula is compared to numerical integration of the Gaussian noise (GN) model and split-step simulations over a wide range of parameters, including three different fiber types. Additionally, the impact of pump depletion on the NLI noise power is studied and the formula is applied to a second-order Raman-amplified system. In the case of first-order amplification and negligible pump depletion, a maximum deviation of 0.34 dB in NLI coefficient between the GN model and the closed-form formula is found which corresponds to a maximum deviation of 0.1 dB in optimal SNR or similar figures of merit (e.g., maximum reach). When pump depletion is considered, it is shown that the NLI coefficient becomes a function of launch power and as a result the cubic power dependence of the NLI noise power is no longer valid in such regimes. Finally, for the second-order Raman-amplified system, a maximum deviation of 0.39 dB in NLI coefficient is reported

Digital back-propagation for nonlinearity mitigation in distributed Raman amplified links

The performance of digital back-propagation (DBP) for distributed Raman amplified optical communication systems is evaluated through analytical models and numerical simulations, and is compared with conventional lumped amplifier solutions, such as EDFA. The complexity of the DBP algorithm including the characteristic signal power profile of distributed Raman amplifiers is assessed. The use of full-field DBP in distributed Raman amplified systems leads to 1.3 dB additional gain with respect to systems employing lumped amplification, at the cost of only a 25% increase in complexity

Intelligent design of optical networks: which topology features help maximise throughput in the nonlinear regime?

The overarching goal in intelligent network design is to deliver capacity when and where it is needed. The key to this is to understand which network topology characteristics impact the achievable network throughput. This is explored through the use of a new generative network model, taking into account physical layer network characteristics

Making intelligent topology design choices: understanding structural and physical property performance implications in optical networks [Invited]

The key goal in optical network design is to introduce intelligence in the network and deliver capacity when and where it is needed. It is critical to understand the dependencies between network topology properties and the achievable network throughput. Real topology data of optical networks are scarce, and often large sets of synthetic graphs are used to evaluate their performance including proposed routing algorithms. These synthetic graphs are typically generated via the Erdos–Renyi (ER) and Barabasi–Albert (BA) models. Both models lead to distinct structural properties of the synthetic graphs, including degree and diameter distributions. In this paper, we show that these two commonly used approaches are not adequate for the modeling of real optical networks. The structural properties of optical core networks are strongly influenced by internodal distances. These, in turn, impact the signal-to-noise ratio, which is distance dependent. The analysis of optical network performance must, therefore, include spatial awareness to better reflect the graph properties of optical core network topologies. In this work, a new variant of the BA model, taking into account the internodal signal-to-noise ratio, is proposed. It is shown that this approach captures both the effects of graph structure and physical properties to generate better networks than traditional methods. The proposed model is compared to spatially agnostic approaches, in terms of the wavelength requirements and total information throughput, and highlights how intelligent choices can significantly increase network throughputs while saving fiber