Long-haul Optical Transmission Research Articles

Power-aided probabilistic shaping parameter optimization for long-haul optical fiber transmission

A power-aided probabilistic shaping (PS) parameter optimization scheme is proposed to localize the optimal transmitting setup and maximize the transmission capacity in long-haul optical fiber transmission. Using a neural network and genetic algorithm (NNGA), the proposed scheme can select the optimal transmission parameter set, including the launching optical power (LOP) and three PS characteristics. We built a testbed using MATLAB and VPI to validate the proposed scheme. The proposed scheme was demonstrated in a dual-polarization coherent transmission system. The results show that the proposed scheme improves the generalized mutual information (GMI) by 0.3035 bits/symbol/pol and normalized GMI by 0.1022 in a 1000 km G.654E fiber transmission at 420-Gbit/s, compared to a traditional MB-based PS technique. The signal-to-noise ratio (SNR) achieves a gain of 1.003 dB, which validates the outperformance of the proposed scheme.

Hybrid optical-electronic compensation of fiber nonlinearity for long-haul coherent optical transmission

Abstract From the concepts of the dispersion-folded digital backward propagation (DBP) and optical phase conjugation (OPC), a hybrid optical-electronic nonlinearity-compensation scheme is proposed to enhance the system performance of the dispersion-managed transmission. The computational complexity of the proposed scheme, compared with that of the conventional DBP method, is reduced significantly while the performance penalty is negligible. The compensation efficiency of the proposed scheme has been validated in a 5 (and 9)-channel PM-16QAM system at 256 Gbit/s.

Co-LSTM-based fiber link modeling with ASE noise tracking for long-haul coherent optical transmission.

In this Letter, a novel, to the best of our knowledge, channel modeling scheme based on cascading chromatic dispersion-nonlinearity feature decoupling modules is proposed with the center-oriented long short-term memory (Co-LSTM) network structure adopted for modeling nonlinearity of each optical fiber span. By tracking the amplified spontaneous emission (ASE) noise at the output of each fiber span, the Co-LSTM-based channel modeling scheme achieves high waveform accuracy for long-haul coherent optical transmission compared with the conventional split-step Fourier transform method (SSFM) while saving calculation time by almost one order of magnitude.

Low-complexity fiber nonlinear distortion mitigation for long-haul optical transmission based on transformer and triplets

Low-complexity fiber nonlinear distortion mitigation for long-haul optical transmission based on transformer and triplets

Dynamic Secure Key Distribution Based on Dispersion Equalization and Cellular Automata for Optical Transmission

This paper proposes a dynamic secure key distribution scheme based on dispersion equalization and cellular automata (CAs). The scheme effectively eliminates the key inconsistency problem caused by imperfect channel reciprocity, and dynamic key sequences can be conveniently generated with large key space in long-haul optical transmission. In the process of communication, the legitimate parties obtain the secure core parameter from the frequency domain equalizer algorithm, and a final key sequence is generated through CA iterations on the basis of the core parameter. The randomness and reciprocity characteristics of the channel ensure the security and uniqueness of the core parameter and final key sequence. With 10G Baud 16 quadrature amplitude modulation over 400 km standard single-mode fiber transmission, the proposed scheme is verified with a free key error rate and an unlimited key generation rate. The security robustness of this scheme was theoretically analyzed and verified by sweeping the eavesdropper’s tapping position and improving CA operation processing. The proposed key distribution scheme is compatible with the existing transmission system for different signal modulation formats.

Flexible optical fiber channel modeling based on a neural network module.

Optical fiber channel modeling, which is essential in optical transmission system simulations and designs, is usually based on the split-step Fourier method (SSFM), making the simulation quite time-consuming owing to the iteration steps. Here, we train a neural network module termed NNSpan to learn the transfer function of a single fiber (G652 or G655) span with a length of 80 km and successfully emulate long-haul optical transmission systems by cascading multiple NNSpans, which gives remarkable prediction accuracy, even over a transmission distance of 1000 km. Even when trained without erbium-doped fiber amplifier (EDFA) noise, NNSpan performs quite well when emulating the systems affected by EDFA noise. An optical bandpass filter can optionally be added after EDFA, making the simulation more flexible. Comparison with the SSFM shows that NNSpan has a distinct computational advantage, with the computation time reduced by a factor of 12. This method based on NNSpan could be a supplementary option for optical transmission system simulations, thus contributing to system designs as well.

Wideband Multichannel Nyquist-Spaced Long-Haul Optical Transmission Influenced by Enhanced Equalization Phase Noise.

Enhanced equalization phase noise (EEPN), generated from the uncompensated dispersion experienced by laser phase noises, can cause serious damage to the transmission quality of optical fiber systems. In this work, the performance of a wideband Nyquist-spaced long-haul nonlinear optical fiber communication systems suffering from EEPN is investigated and discussed through split-step numerical simulations and analytical models based on the perturbation analysis, in the cases of digital nonlinearity compensation (NLC) and electronic dispersion compensation (EDC). The efficiency and the accuracy of the analytical models were validated via simulations, considering the different symbol rates and modulation formats. The performance of the C-band transmission was comprehensively studied based on the model. Our results reveal that the growth of symbol rates and transmission distances aggravates the distortions in the C-band system.

(INVITED)Reconfigurable topology testbeds: A new approach to optical system experiments

Optical transmission systems provide high capacity, low latency and jitter, and high reliability for city-scale networks. Recirculating loop experiments have facilitated the study of signal propagation in long-haul optical transmission systems. However, they are unsuited for developing control and management software for city-scale optical networks with dozens or hundreds of reconfigurable optical add drop multiplexer (ROADM) units, diverse interconnection topologies, and dynamic traffic patterns. Large-scale testbeds can help, but may be inflexible and time- or cost-prohibitive. Reconfigurable testbeds such as COSMOS enable piece-wise emulation of a city-scale network by applying space and wavelength switching, dual-use software-defined networking (SDN) controllers, and comb sources, while digital twin models enable software emulation. Results from the development of a digital twin for COSMOS are presented for optical amplifiers and stimulated Raman scattering (SRS) including both analytical and machine learning (ML) models.

Impact of the input OSNR on data-driven optical fiber channel modeling

The data-driven approach is promising for computationally efficient modeling of optical fiber channels. Here, for the first time to our knowledge, we investigate the impact of the input optical signal-to-noise ratio (OSNR) on the accuracy of data-driven modeling for optical fiber channels, based on a conditional generative adversarial network (cGAN). Initially, considering a single span of 80 km of standard single mode fiber (SSMF), we vary the launched optical power for the ease of emulating both linear and nonlinear transmission scenarios. When the input OSNR of a root raised cosine (RRC)-shaped 16 quadrature amplitude modulation signal with a roll-off factor of 0.1 varies, we identify that there occurs an OSNR threshold for accurately modeling a single span of 80 km of SSMF in order to reach the normalized mean square error of less than 0.02 in relevance to the traditional split-step Fourier method. The OSNR thresholds are 19 dB and 21 dB, respectively, under scenarios of linear and nonlinear transmissions. Moreover, we verify that the OSNR threshold of accurate modeling is insensitive to both the modulation format and the RRC shaping of the input signal. Furthermore, we find that the cascaded use of cGAN well-trained for the single SSMF span is capable of modeling the multiple-span SSMF transmission in the case that the input OSNR threshold of 22.6 dB is satisfied. We believe that the identification of the OSNR threshold for data-driven optical fiber channel modeling is useful for the accurate and efficient emulation of long-haul fiber optical transmission.

Nonlinear impairment scaling in coupled-core multi-core fibers for space-division multiplexing

We study the nonlinear impairment scaling in coupled-core multi-core fibers (CC-MCFs) with core count by evaluating four typical CC-MCFs with different numbers of cores, which have been demonstrated promising for long-haul optical fiber transmissions, using the Gaussian-noise model. The results show that nonlinear signal degradation in CC-MCFs with more cores becomes significantly weaker, which would be of great interest to ultralong-haul transmission in CC-MCFs. We further analyze how the fiber loss, differential group delay and effective mode field area impact on the trend. Moreover, we compare CC-MCFs and few-mode fibers with the same number of spatial modes in terms of nonlinear impairment and find that CC-MCFs tend to achieve better nonlinear performance. It is also shown that few-mode fibers operated in strong coupling regime are quite promising for long-haul transmission.

Investigation of long-haul optical transmission systems: diverse chirped FBGs with DCF for 300km length of SMF

Investigation of long-haul optical transmission systems: diverse chirped FBGs with DCF for 300km length of SMF

High-speed multi-channel long-haul coherent optical transmission system

In this work, high-speed transmission over the long-haul optical channel using orthogonal frequency division multiplexing (OFDM) was investigated. Furthermore, we recommend mixing polarization division multiplexing (PDM) with coherent OFDM (CO-OFDM) and quadrature amplitude modulation (16-QAM) to improve spectral efficiency (SE) while transmitting over a wavelength division multiplexing (WDM) system. An 800 Gb/s WDM PDM-CO-OFDM-16QAM transmission system with various channel spacing of 100 GHz, 50 GHz, and 25 GHz is examined utilizing the OptiSystem (2021) version 18.0 software package over ten spans of 60 km standard single-mode fiber (SSMF). Different channel spacing WDM systems have been compared in terms of performance and SE. The results reveal that the WDM system with 100 GHz channel spacing has a longer transmission range and needs minimal optical signal to noise ratio (OSNR) at the reception. The 25 GHz channel spacing WDM system exceeds the others in terms of SE. Further, the effect of ultra-low loss and large effective area fiber in lowering span loss and nonlinear effects for 25 GHz channel spacing WDM system is investigated. The findings show that the system performance with the new fiber outperforms the SSMF. The acceptable bit error rate (BER) for this study is 0.033 (20% concatenated forward error correction (FEC) threshold).

Low-Complexity Triplet-Correlative Perturbative Fiber Nonlinearity Compensation for Long-Haul Optical Transmission

In this paper, we propose a triplet-correlative perturbative nonlinearity compensation (TC-PNC) scheme to compensate for intra-channel fiber nonlinear impairments. The complexity of TC-PNC is much lower than both of the conventional perturbative nonlinearity compensation (PNC) and degenerate PNC (DPNC), while the compensation performance of TC-PNC is much better than DPNC and is slightly worse than PNC. Compared to PNC and DPNC, the implementation complexity of TC-PNC is reduced by 94.73% and 22.53%, respectively. The compensation performance is evaluated by both simulations and experiments. In simulations with a transmission distance of 2000 km for 70 Gbaud dual-polarization 16-ary quadrature amplitude modulation (16QAM) signals, the signal-to-noise ratio (SNR) gains of TC-PNC are 0.3 dB and 0.77 dB compared to DPNC and the uncompensated case, respectively. In experiments for 30 Gbaud dual-polarization probabilistically shaped 16QAM (PS-16QAM) signals with a transmission distance of 432 km, the effectiveness of TC-PNC is validated by comparing the performance relative to PNC and DPNC.

Fast and Accurate Waveform Modeling of Long-Haul Multi-Channel Optical Fiber Transmission Using a Hybrid Model-Data Driven Scheme

The modeling of optical wave propagation in optical fiber is a task of fast and accurate solving the nonlinear Schr\"odinger equation (NLSE), and can enable the optical system design, digital signal processing verification and fast waveform calculation. Traditional waveform modeling of full-time and full-frequency information is the split-step Fourier method (SSFM), which has long been regarded as challenging in long-haul wavelength division multiplexing (WDM) optical fiber communication systems because it is extremely time-consuming. Here we propose a linear-nonlinear feature decoupling distributed (FDD) waveform modeling scheme to model long-haul WDM fiber channel, where the channel linear effects are modelled by the NLSE-derived model-driven methods and the nonlinear effects are modelled by the data-driven deep learning methods. Meanwhile, the proposed scheme only focuses on one-span fiber distance fitting, and then recursively transmits the model to achieve the required transmission distance. The proposed modeling scheme is demonstrated to have high accuracy, high computing speeds, and robust generalization abilities for different optical launch powers, modulation formats, channel numbers and transmission distances. The total running time of FDD waveform modeling scheme for 41-channel 1040-km fiber transmission is only 3 minutes versus more than 2 hours using SSFM for each input condition, which achieves a 98% reduction in computing time. Considering the multi-round optimization by adjusting system parameters, the complexity reduction is significant. The results represent a remarkable improvement in nonlinear fiber modeling and open up novel perspectives for solution of NLSE-like partial differential equations and optical fiber physics problems.

Spectral efficiency and performance improvement of coherent optical transmission system

This paper presents an orthogonal frequency division multiplexing (OFDM) for a long-haul optical transmission system with high-rate transferability to alleviate dispersion effects. In addition, we suggest combining polarization division multiplexing (PDM) with coherent OFDM (CO-OFDM) to increase spectral efficiency (SE). Based on OptiSystem (2021) version 18.0" software package, a 100 Gbps single-channel PDM-CO-OFDM transmission system is investigated using different modulation formats; bipolar phase keying (BPSK), quadrature phase shift keying (QPSK), Eight-Phase-Shift Keying modulators (8-PSK), and quadrature amplitude modulation (16-QAM). A 60 km span of standard single-mode fiber (SSMF) cable is employed in this investigation. The system's performance and spectral efficiency have been evaluated by comparing against the different modulation schemes. The outcomes that were got show that the BPSK modulation scheme has the longest transmission distance and requires a lesser level of optical signal to noise ratio (OSNR) at the receiver side. Concerning spectral efficiency, 16-QAM outperforms the others. Farther, the impact of employing ultra-low loss and large effective area fiber in reducing loss and nonlinear effects in the optical channel for 16-QAM modulation formats is examined. The result found that the system with advanced fiber has superior performance than the SSMF. The bit error rate (BER) of 0.033 (20% concatenated forward error correction (FEC) threshold) is used as a baseline.

Convolutional Neural Network-Aided DP-64 QAM Coherent Optical Communication Systems

Optical nonlinearity impairments have been a major obstacle for high-speed, long-haul and large-capacity optical transmission. In this paper, we propose a novel convolutional neural network (CNN)-based perturbative nonlinearity compensation approach in which we reconstruct a feature map with two channels that rely on first-order perturbation theory and build a classifier and a regressor as a nonlinear equalizer. We experimentally demonstrate the CNN equalizer in 375 km 120-Gbit/s dual-polarization 64-quadrature-amplitude modulation (64-QAM) coherent optical communication systems. We studied the influence of the dropout value and nonlinear activation function on the convergence of the CNN equalizer. We measured the bit-error-ratio (BER) performance with different launched optical powers. When the channel size is 11, the optimum BER for the CNN classifier is 0.0012 with 1 dBm, and for the CNN regressor, it is 0.0020 with 0 dBm; the BER can be lower than the 7 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> hard decision-forward threshold of 0.0038 from −3 dBm to 3 dBm. When the channel size is 15, the BERs at −4 dBm, 4 dBm and 5 dBm can be lower than 0.0020. The network complexity is also analyzed in this paper. Compared with perturbative nonlinearity compensation using a fully connected neural network (2392-64-64), we can verify that the time complexity is reduced by about 25 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> , while the space complexity is reduced by about 50 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> .

High-Throughput and Long-Distance Transmission With &gt;120 nm S-, C- and L-Band Signal in a 125μm 4-Core Fiber

We investigate recirculating transmission of a wideband S-, C- and L-band signal in a 4-core fiber. We transmit 552 x 25 GHz spaced, 24.5 GBd channels, covering more than 120 nm bandwidth from 1487.8 nm to 1608.33 nm through each core of the multi-core fiber (MCF), which has the same 125&#x03BC;m cladding dimeter as standard single-mode fiber. We first use PDM-16QAM modulation and measure performance at distances up to 3001 km, corresponding to 43 spans of the 69.8 km MCF. At this distance we measure a decoded throughput of 319 Tb&#x002F;s or 342 Tb&#x002F;s when estimating from the generalised mutual information (GMI). Extending the transmission distance to 8027 km, a selection of PDM-QPSK modulated channels across the spectrum were received with an average GMI estimated data-rate of 83.7 Gb&#x002F;s. These results show that wideband transmission including the S-band has the potential to increase data-rates in long-haul optical fiber transmission. Further, our experiment confirms that 125 &#x03BC;m diameter MCFs can multiply transmission capacity whilst offering benefits of resource sharing and integration, expected in SDM systems.

Transfer Learning for Neural Networks-Based Equalizers in Coherent Optical Systems

In this work, we address the question of the adaptability of artificial neural networks (NNs) used for impairments mitigation in optical transmission systems. We demonstrate that by using well-developed techniques based on the concept of transfer learning, we can efficaciously retrain NN-based equalizers to adapt to the changes in the transmission system, using just a fraction (down to 1%) of the initial training data or epochs. We evaluate the capability of transfer learning to adapt the NN to changes in the launch power, modulation format, symbol rate, or even fiber plants (different fiber types and lengths). The numerical examples utilize the recently introduced NN equalizer consisting of a convolutional layer coupled with bi-directional long-short term memory (biLSTM) recurrent NN element. Our analysis focuses on long-haul coherent optical transmission systems for two types of fibers: the standard single-mode fiber (SSMF) and the TrueWave Classic (TWC) fiber. We underline the specific peculiarities that occur when transferring the learning in coherent optical communication systems and draw the limits for the transfer learning efficiency. Our results demonstrate the effectiveness of transfer learning for the fast adaptation of NN architectures to different transmission regimes and scenarios, paving the way for engineering flexible and universal solutions for nonlinearity mitigation.

Chaos Synchronization Based on Hybrid Entropy Sources and Applications to Secure Communication

We experimentally demonstrate a chaotic synchronization scheme based on the electro-optic hybrid entropy sources. The chaos synchronization method is experimentally validated that 200 km high-level chaos synchronization can be attained and the distance can be further extended. The digital signal induced chaos synchronization signal has good robustness against the potential distortions in long-haul optical transmission. On the basis of the digital signal induced chaos synchronization strategy, a correlated random bit generation (CRBG) scheme with bit rate of 1.25 Gb/s and distance of 200 km is proposed. The generated correlated random bit sequences (CRBSs) pass all the NIST tests. Meanwhile, a data encryption scheme based on the robust chaos synchronization method is proposed with low computation complexity. The synchronization signal, in which the encrypted data is embedded, maintains the strength in long-haul transmission. The strong robustness of the scheme under parameter mismatch is numerically analyzed. These propositions show great potential in the field of secure communication, especially the long-haul scenario.

Second-Order Perturbation Theory-Based Digital Predistortion for Fiber Nonlinearity Compensation

The first-order (FO) perturbation theory-based nonlinearity compensation (PB-NLC) technique has been widely investigated to combat the detrimental effects of the intra-channel Kerr nonlinearity in polarization-multiplexed (Pol-Mux) optical fiber communication systems. However, the NLC performance of the FO-PB-NLC technique is significantly limited in highly nonlinear regimes of the Pol-Mux long-haul optical transmission systems. In this paper, we extend the FO theory to second-order (SO) to improve the NLC performance. This technique is referred to as the SO-PB-NLC. A detailed theoretical analysis is performed to derive the SO perturbative field for a Pol-Mux optical transmission system. Following that, we investigate a few simplifying assumptions to reduce the implementation complexity of the SO-PB-NLC technique. The numerical simulations for a single-channel system show that the SO-PB-NLC technique provides an improved bit-error-rate performance and increases the transmission reach, in comparison with the FO-PB-NLC technique. The complexity analysis demonstrates that the proposed SO-PB-NLC technique has a reduced computational complexity when compared to the digital back-propagation with one step per span.