Characterization, Modelling and Measurement of Device Imperfections in Advanced Coherent Transceivers

Tao, Zhenning; Fan, Yangyang; Ye, Tong; Su, Xiaofei; Nakashima, Hideharu; Hoshida, Takeshi

doi:10.1109/ecoc52684.2021.9605882

Cited by 3 publications

(2 citation statements)

References 24 publications

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“…It consists of multiple layers that perform weighted summation and nonlinear mapping. The output of the first layer (1) h , the kth layer () k h , and the last layer y of a NN and the MSE as a loss function for the BP can be expressed as [29]:…”

Section: A the Principle Of Vnle And Time Delayed Nn Structurementioning

confidence: 99%

“…Given the compromised linearity properties across broad frequency bands, leading to restricted optical transmission performance, high-speed coherent optical transmission systems implementing high symbol rate and high order quadrature amplitude modulation (QAM) formats signals require highly efficient nonlinear equalizers (NLEs) to compensate for nonlinear impairments. In short-range fiber links, exemplified by data center interconnects (DCI) and data center networks (DCN), the influence of nonlinearity introduced by optical/electrical (O/E) components including the digital-to-analog converter (DAC), the electrical power amplifier (PA), and the optical modulator in coherent transceivers (CO-TRx)-takes a prominent role, significantly compromising transmission capacity [1]. Conversely, in long-range transmission scenarios such as metropolitan area networks, core networks, and transoceanic transmission, fiber nonlinearity emerges as the major bottleneck.…”

Section: Introductionmentioning

confidence: 99%

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Noisy samples-robust Neural Network-based Equalizer for Coherent Optical Transmission Nonlinearity Compensation

Deng,

Cao,

Dai

et al. 2024

Preprint

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Nonlinear impairments introduced by optical/electrical components in coherent transceivers (CO-TRx) and optical fiber are the primary bottleneck for enhancing optical transmission capacity. As most nonlinearity equalizers (NLEs) are training data-driven, they can provide significant gain under high-quality training signals but only a weak gain under poor ones. This limitation becomes noteworthy for high-speed transmission systems characterized by high-baud rate and high-order modulation formats resulting in signals with relatively low signal-to-noise ratio, which are susceptible to penalties from various impairments. In response to this issue, we propose a novel approach known as noisy samples-robust neural network-based nonlinearity equalizer (NS-NNLE). With the combination of a pre-trained model, a filter network for noise feature filtration, and a main network for nonlinear mapping, the proposed NS-NNLE can be trained efficiently using noisy training sequences and achieve more stable generalizability than common NLEs. We experimentally demonstrate its performance in a dual-polarization (DP) 64 GBaud 16QAM signals back-to-back (B2B) coherent optical transmission and a DP-40GBaud 16QAM signals 110 km fiber transmission. Experimental results illustrate that the proposed NS-NNLE can provide a stable gain at an acceptable complexity cost under various test conditions where conventional NLEs struggle to achieve adequate training, both for CO-TRx and fiber-induced nonlinearity

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Section: A the Principle Of Vnle And Time Delayed Nn Structurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Noisy samples-robust Neural Network-based Equalizer for Coherent Optical Transmission Nonlinearity Compensation

Deng,

Cao,

Dai

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Nonlinear noise spectrum measurement using a probability-maintained noise power ratio method

Zhang

et al. 2022

Commun Eng

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Nonlinear distortion (noise) limits many communication systems, demanding a means of estimating system performance via device nonlinear characteristics. The noise power ratio (NPR) method which was proposed in 1971 solves this problem for systems with Gaussian stimuli or with special nonlinearity, but practical and accurate methods for many communication systems with non-Gaussian stimuli are rare. Here we propose a probability-maintained (PM) NPR method to accurately measure the spectrum of nonlinear noise via a spectrum analyzer in non-specific systems, including systems with non-Gaussian stimuli. Using an equivalent additive noise model in which the spectrum of equivalent nonlinear noise is the measurement result of PM NPRs, nonlinear system performance could be estimated with an error of 0.5 dB. Further, we find that zero-mean Chi-square noise, instead of Gaussian noise, should be selected for large memory and low-order nonlinear systems. Our method is verified in seven different scenarios with various nonlinear mechanisms and communication applications.

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Characterization, Measurement and Specification of Device Imperfections in Optical Coherent Transceivers

Tao

Fan

et al. 2022

J. Lightwave Technol.

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Transceiver imperfections become the primary source of impairment as baud rate and modulation order grow in advanced optical coherent communications. Thus, transceiver imperfections, both linear and nonlinear, need to be appropriately characterized, measured, and specified. Treatments for linear imperfections are relatively mature. This study reviews the transceiver's linear imperfection modeling, characterization, and measurement technologies. In practical applications, in-field measurement using the transceiver and a few low speed additional devices is preferred. In the case of nonlinear imperfections, the situation is complex. One important task is to estimate the nonlinear system performance from the nonlinear characteristics of the devices. In this study, we attempt to establish a connection between them by examining different technologies. Although the orthogonal component has a good correlation with nonlinear system performance, its measurement is prohibitively complex. In the nonlinear noise to power ratio measurement, a certain frequency component of the input signal is notched, and the re-growth component at the notch frequency is measured at the nonlinear device output. The ratio between the re-growth component power and the output signal power is the noise to power ratio. While this method is easy to carry out, it does not correctly estimate nonlinear impairment in general. The reason for this is that the signal incurs different nonlinear responses in two conditions, i.e., with or without a notch. This method accurately estimates the nonlinear impairment in some special but useful cases, such as Gaussian input signals and nonlinear systems whose dominant nonlinear term is the even order term.

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Characterization, Modelling and Measurement of Device Imperfections in Advanced Coherent Transceivers

Cited by 3 publications

References 24 publications

Noisy samples-robust Neural Network-based Equalizer for Coherent Optical Transmission Nonlinearity Compensation

Noisy samples-robust Neural Network-based Equalizer for Coherent Optical Transmission Nonlinearity Compensation

Nonlinear noise spectrum measurement using a probability-maintained noise power ratio method

Characterization, Measurement and Specification of Device Imperfections in Optical Coherent Transceivers

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