Transponder Implementation Penalty-Accounted Gaussian-Noise-Based Performance Modeling of Fiber-Optic Transmission Systems

Kaliteevskiy, Nikolay; Ivanov, Viacheslav; Sterlingov, Petr; Downie, John D.; Makovejs, Sergejs; Hurley, Jason

doi:10.1109/jlt.2020.2966372

Cited by 5 publications

(6 citation statements)

References 24 publications

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“…The environment faced mainly refers to the user's request. The agent system makes decisions on the allocation of tasks and resources by perceiving the environment, improving service efficiency, and optimizing the environment feedback of the agent system as incentives and rewards [18].…”

Section: Formal Modeling Of Networked Intelligent Servicementioning

confidence: 99%

Optimization Strategy Analysis of Intelligent Product Service System Based on Computer Simulation Technology

et al. 2022

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In order to solve the needs of a large number of users and the efficiency of user service requirements, an optimization strategy analysis method of intelligent product service system based on computer simulation technology is proposed. Aiming at the two challenges of massive requests and efficient service in the network intelligent service system, the characteristics of the network intelligent service system are analyzed, and the network intelligent service system is formally modeled as an agent system. The performance modeling, performance evaluation, and performance optimization methods of the network intelligent service system are proposed. In order to solve this massive demand, the performance modeling of the network intelligent service system is carried out based on queuing theory. This paper proposes a task assignment algorithm for the network intelligent service system. Through the application of these results, the processing efficiency of the entire medical insurance application system has been greatly improved, and the average completion time of all businesses has been shortened by 59%, providing new ideas for optimizing service methods and improving service quality.

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Section: Formal Modeling Of Networked Intelligent Servicementioning

confidence: 99%

Optimization Strategy Analysis of Intelligent Product Service System Based on Computer Simulation Technology

et al. 2022

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“…where ν = 12.5 GHz (0.1 nm) is the resolution bandwidth of the OSA. The OSNR in the backto-back configuration is obtained by measuring signal power (P ch ) and noise power level within the resolution bandwidth (P ASE ) on the OSA and then applying the following expression OSNR = P ch − P ASE P ASE (10) There are different approaches to include the effect of the measured implementation penalty on final predicted SNR [11]- [13], [20]. The approach we use here is to fit a polynomial function to the measured penalty calculated by Eq.…”

Section: Table I Parameters Of Fiber Spansmentioning

confidence: 99%

“…T OT = GSNR dB − SNR dB m,fit GSNR dB (11) Before applying the implementation penalty, we also account for the measured initial, or start, OSNR and add a corresponding constant noise term, which is due to additional EDFAs needed between the transmitter and the loop or system under test for channel multiplexing, as given in Eq. 12:…”

Section: Snr Dbmentioning

confidence: 99%

“…For such long-haul and high-baud-rate systems operating at low channel powers, there are several impactful effects such as the generalized signal droop (GD) [1]- [2], [5]- [10] effect, transponder implementation penalty [11]- [13], and to smaller extents, nonlinear interference (NLI) [14]- [16] noise and Guided Acoustic Waveguide Brillouin Scattering (GAWBS) [9], [17]- [19] noise.…”

Section: Introductionmentioning

confidence: 99%

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Experimental Evaluation of the Generalized Signal Droop Model With SNR Measurements Including Transponder Implementation Penalty

Ivanov¹,

Downie

Liang

et al. 2021

IEEE Photonics J.

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We experimentally assess the accuracy of a constant output power generalized droop (COP-GD) model combined with transponder implementation penalty to predict transmission performance for single-core long-haul optical transmission systems operating at low channel launch powers and high baud rates. The droop model includes Guided Acoustic Waveguide Brillouin Scattering (GAWBS) and nonlinear interference (NLI) effects along with amplifier noise for signal-to-noise ratio (SNR) calculation in the context of long-haul systems with constant output power amplifiers. We show how the model accuracy is decreased if one of the modeling components is removed, namely, either the droop effect, GAWBS or the transponder implementation penalty. We show that inclusion of implementation penalty and GD is important for accurate performance evaluation, moreover, the transponder implementation penalty has impact both at low and high SNR ends. We compare the model including both effects to experimental transmission data over a wide link SNR range for the first time and demonstrate excellent agreement between modeling predictions and experimental results.

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“…In optical fiber communication network, there are usually two kinds of interference signals, noise and interference, which will affect the utilization of effective signals and reduce the quality of signal transmission. By combining IP model and nonlinear Gaussian noise model, the influence of nonlinear interference noise can be effectively reduced, and the damage of additional link components can be reduced [5].…”

Section: Introductionmentioning

confidence: 99%

Digital interference signal filtering on laser interface for optical fiber communication

Zhang¹,

Gadekallu

2022

EAI Endorsed Scal Inf Syst

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INTRODUCTION: Fiber laser communication is a communication method that uses laser and fiber medium to realize data transmission and information output OBJECTIVES: In order to reduce the signal interference of optical fiber communication laser interface and ensure the communication quality of optical fiber network. A filtering method of optical fiber communication laser interface interference signal based on digital filtering technology is designed. METHODS: In this paper, the interface model of optical fiber communication network is firstly constructed, and the interface noise signal is input into the digital filter bank. The digital quadrature filtering method and the least square algorithm are used to separate the denoised signals to reduce the crosstalk between the signals in the channel. In this way, the crosstalk component in the signal can be filtered out, and a better filtering processing effect of the laser interface interference signal can be achieved. RESULTS: The results of peak signal-to-noise ratio are above 25, which effectively filters the interference signal in the signal, and retains the effective signal completely. The intelligibility of optical fiber communication network in signal communication is above 0.94, and the highest value is 0.986. The distortion degree are all below 0.025, and the minimum value is 0.004. The communication bit error rate are all below 0.001, which ensures the communication quality of the network. CONCLUSION: The experimental results show that the signal noise reduction effect of the proposed method is good, which provides a reliable basis for filtering and separating interference signals of optical fiber communication laser interface.

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Transponder Implementation Penalty-Accounted Gaussian-Noise-Based Performance Modeling of Fiber-Optic Transmission Systems

Cited by 5 publications

References 24 publications

Optimization Strategy Analysis of Intelligent Product Service System Based on Computer Simulation Technology

Optimization Strategy Analysis of Intelligent Product Service System Based on Computer Simulation Technology

Experimental Evaluation of the Generalized Signal Droop Model With SNR Measurements Including Transponder Implementation Penalty

Digital interference signal filtering on laser interface for optical fiber communication

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