OPTICAL COMMUNICATIONS & COMPUTING
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Optical Communications & Computing
Fatih Yaman is a Senior Researcher in the Optical Communications & Computing Department of NEC Laboratories America.
We propose a method to compensate the phase offset between samples from different tributaries in time-interleaved phase OTDR using nested phase reference channels. We demonstrate our method for a four-span bidirectional link with high-loss loopback.
In this talk, we will present recent technological advances in fiber sensing applications with long monitoring distances orextending multiple fiber spans. In forward-transmission-based sensing, adaptive beamforming techniques weredemonstrated to achieve multi-event vibration sensing in environments with
NEC Laboratories America (NECLA) was proud to join the European Conference on Optical Communication (ECOC 2025) in Copenhagen, Denmark, from September 28 to October 2. Our researchers presented cutting-edge work in distributed acoustic sensing, AI-driven fiber optics, and optical networking. From generative
Polarization-based, multi-span sensing over a link without reflection-back circuits is demonstrated experimentally. It is shown that distributed reflection from Rayleigh scattering can serveas an alternative to reflectors after spatial averaging of received state-of-polarization
We jointly estimate the phase noise power spectral densities of multiple lasers using interferometry between different combinations of laser pairs. We demonstrate a beat-frequency trackingmethod that allows under-sampling of interferometric products without phase jumps.
We present a simple and accurate semi-analytical model predicting the gain of a single-stage erbium-doped fiber amplifier (EDFA) embedded with an unknown gain flattening filter (GFF). Characteristic wavelength-dependent gain coefficients and their scaling laws are extracted with a limited set of simple
Subsea cables include a supervisory system that monitors the health of the amplifier pumps and fiber loss on per span basis. In some of the cables, the monitoring is achieved optically and passively using high-loss loop back paths and wavelength selective reflectors. By sending monitoring pulses through
A simple and accurate semi-analytical model for predicting the gain of a single-stage erbium-doped fiber amplifier embedded with an unknown gain flattening filter is proposed for precise system equalization that is crucial for submarine systems.
Experiments show that machine learning model of an EDFA is capable of modelling spectral hole burning effects accurately. As a result, it significantly outperforms black-box models that neglect inhomogeneous effects. Model achieves a record average RMSE of 0.0165 dB between the model predictions and
Our optical networking & sending team has arrived in Frankfurt for the 2024 European Conference on Optical Communication (ECOC) and is excited to present many papers and tutorials this week. Please follow this page and on our social media channels for updates.
The NEC Labs America team Yaowen Li, Andrea D’Amico, Yue-Kai Huang, Philip Ji, Giacomo Borraccini, Ming-Fang Huang, Ezra Ip, Ting Wang & Yue Tian (Not pictured: Fatih Yaman) has arrived in San Diego, CA for OFC24! Our team will be speaking and presenting throughout the event. Read more for an overview
Dependence of EDFA gain shape on input power and input spectrum shape is modelled using a simple neural network-based architecture for amplifiers with different gains and output powers. The model can predict the gain within ±0.1 dB. Even though the model has good success predicting the performance of
Simultaneous phase and polarization sensing with span length resolution using the supervisory path is demonstrated. It is shown that by measuring polarization rotation matrix of the return paths, instead of monitoring only the state of polarization, location of the polarization disturbance can be determined
Polarization-based, multi-span sensing over a link with reflection-back circuits is demonstrated experimentally. By measuring rotation matrices instead of just monitoring polarization, a 35 dB extinction in localization is achieved regardless of the disturbance magnitude.
We report the first distributed acoustic sensing (DAS) experiment with over >1,000 km reach on a hybrid link comprising of a mixture of field and lab fibers with bi-directional inline Raman amplification after each span. We used 20× frequency-diversity chirped-pulses for the probe signal,and recovered
We explore two fiber sensing methods which enables coexistence with data transmission on DWDM fiber networks. Vibration detection and localization can be achieved by extracting optical phase from modified coherent transponders. Frequency-diverse chirped-pulse DAS with all-Raman amplification can improve
We report the first distributed acoustic sensing (DAS) results over>1,000 km on a field-lab hybrid link using chirped-pulses with correlation detection and 20× frequency-diversity, achieving a sensitivity of 100 pa/√Hz at 20-meters spatial resolution.
Neural networks (NNs) are attractive for nonlinear impairment compensation applications in communication systems, such as optical fiber nonlinearity, nonlinearity of driving amplifiers, and nonlinearity of semiconductor optical amplifiers. Without prior knowledge of the transmission link or the hardware
In optical communication systems, fibre nonlinearity is the major obstacle in increasing the transmission capacity. Typically, digital signal processing techniques and hardware are used to deal with optical communication signals, but increasing speed and computational complexity create challenges for
Guided acoustic Brillouin (GAWBS) noise is measured using a novel, homodyne measurement technique for four commonly used fibers in long-distance optical transmission systems. The measurements are made with single spans and then shown to be consistent with separate multi-span long-distance measurements.
CCCE in a 60-km fiber is estimated from its GAWBS noise spectrum by comparing the TR 1m modes with the R 0m modes. The estimated CCCE value 0.73 μm is consistent with conventional measurements of 0.6–0.8 μm.
Neural networks are attractive for nonlinear impairment compensation applications in communication systems. In this paper, several approaches to reduce computational complexity of the neural network-based algorithms are presented.
We demonstrate the experimental implementation of photonic neural network for fiber nonlinearity compensation over a 10,080 km trans-pacific transmission link. Q-factor improvement of 0.51 dB is achieved with only 0.06 dB lower than numerical simulations.
Fiber nonlinearity is one of the major limitations to the achievable capacity in long distance fiber optic transmission systems. Nonlinear impairments are determined by the signal pattern and the transmission system parameters. Deterministic algorithms based on approximating the nonlinear Schrodinger
Fiber nonlinearity is a major limitation on the achievable maximum capacity per fiber core. Digital signal processing (DSP) can be used directly to compensate nonlinear impairments, however with limited effectiveness. It is well known that fibers with higher chromatic dispersion (CD) reduce nonlinear
Flexible wavelength-multiplexing technique in backbone submarine networks has been deployed to accommodate the trend of variable-rate modulation formats. In this paper, we propose a new design of flexible-rate transponders in the scenario of flexible multiplexing scheme to achieve near-Shannon performance.
Neuron network (NN) is proposed to work together with perturbation-based nonlinearity compensation (NLC) algorithm by feeding with intra-channel cross-phase modulation (IXPM) and intra-channel four-wave mixing (IFWM) triplets. Without prior knowledge of the transmission link and signal pulse shaping/baudrate,
Asymmetric information is shown to be more accurate in characterizing the performance of quadrant folding shaped (QFS) M-QAM. The performance difference of QFS M-QAM schemes strongly depends on the FEC coding rate, and the optimum FEC coding rate is found to be around ?0.8, which is independent of QFS
A simplified, system-agnostic NLC algorithm based on a neuron network is proposed to pre-distort symbols at transmitter side to demonstrate ~0.6dB Q improvement after 2800km SMF transmission using 32Gbaud DP-16QAM.
An ensemble learning algorithm is applied to enhance filtering tolerance of cascaded WSSs in open ROADM environment to demonstrate ~0.8dB Q-factor improvement over MLSE after transmitting over 3200km with 16 ROADMs.
We report on the evolution of the longest segment of FASTER cable at 11,017 km, with 8QAM transponders at 4b/s/Hz spectral efficiency (SE) in service. With offline testing, 6 b/s/Hz is further demonstrated using probabilistically shaped 64QAM, and a novel, low complexity nonlinearity compensation technique
A novel algorithm to design geometric shaped 32QAM to work with probabilistic shaping is proposed to approach the Shannon limit within ~0.2 dB in SNR. The experimental results show ~0.2 dB SNR advantage over 64Gbaud PAS-64QAM, and flex-rate transmission demonstrates > 500 km reach improvement over 32QAM.
A systematic study, including theory, simulation and experiments, is carried out to review the generalized pairwise optimization algorithm for designing optimized constellation. In order to verify its effectiveness, the algorithm is applied in three testing cases: 2-dimensional 8 quadrature amplitude
Generalized mutual information (GMI) has been comprehensively studied in multidimensional constellation and probabilistic-shaped (PS) constellation together with different forward error correction (FEC) coding schemes. The simulation results confirm that GMI is an efficient and accurate tool to compare
