Impact of System Parameters of Optical Fiber Link on Four Wave Mixing

Title:Impact of System Parameters of Optical Fiber Link on Four Wave Mixing

Volume: 14 Issue: 1

Author(s): Anil Kumar and Karamjit Kaur*

Affiliation:

• Department of Electronics & Communication Engineering, Amity School of Engineering & Technology, Amity University Haryana, Manesar, Gurugram,India

Keywords: FWM, channel spacing, dispersion, BER, Q-value, wavelength division multiplexing, non-liner impairments.

Abstract:

Background: The invention of WDM technology in optical communication system has completely revolutionized the telecomm industry through its high data carrying capacity and efficiency of transmission. Advanced optical modulation formats with high spectral efficiency, advanced components like Reconfigurable Optical Add Drop Multiplexers (ROADMS), OXC, and large bandwidth requirements contributed significantly in existence of dynamic, flexible translucent and transparent networks. In these networks, it is common practice to increase the power levels as much as possible to overcome the power penalty effects and better transmission, but this introduces several non-linear impairments in the link and hence degrades the quality of signal flowing. These impairments arise when several high strength optical fields of different wavelengths interact with molecular vibrations and acoustic waves. The different non-linear impacts include Self Phase Modulation (SPM), Cross Phase Modulation (XPM), Four Wave Mixing (FWM) and scattering effects like Stimulated Raman Scattering (SRS), Stimulated Brillouin Scattering (SBS). The main cause of these impairments is variation in refractive index of fiber (also called Kerr effect) due to intensity of signal flowing through fiber. Due to the degradation impact posed by these impairments, it is crucial to analyze their cause, their influence on system performance and mitigation techniques so as to improve the overall quality of transmission. The monitoring of impairments is quite a challenging task due to their dependency on time, present state of network, signals flowing in adjoining channels and fibers.

Objective: The present work aims to identify and describe the role of FWM in optical networks. The mathematical model of FWM is studied to know the parameters influencing the overall impact on system performance. The power of optical source, channel spacing, distance of transmission and presence of dispersion are considered as key factors influencing FWM power being developed. Their impact on FWM power and hence, FWM efficiency is calculated. In addition, the influence of FWM on Quality of transmission is quantified in terms of BER and Q-factor.

Methods: The analysis is done through a two-channel transmitter system with varied power, channel spacing, distance of transmission and presence of other degradation factors (dispersion) is taken into account. The corresponding optical spectrums are analysed.

Result: In this paper, the non-linear impairment FWM posing degradation effect on the signal quality has been discussed. The basics involved are presented along with the mathematical model. It has been found that FWM results in power transfer from one channel to generation of new waves which may lead to power depletion and interference. The new waves generated depend on the number of wavelengths travelling in the fiber and channel spacing. The influence of FWM on system performance is presented in terms of BER and Q-value.

Conclusion: It has been concluded that the increased power of transmission and decreased channel spacing are the crucial factors increasing the magnitude of FWM and need to be closely monitored. On the other hand, increased distance of propagation and presence of certain level of dispersion leads to decrease in FWM power. Therefore, if selected carefully, they may act as source of FWM mitigation without requiring any external compensating device.

Cite this article as:

Kumar Anil and Kaur Karamjit *, Impact of System Parameters of Optical Fiber Link on Four Wave Mixing, Recent Advances in Computer Science and Communications 2021; 14 (1) . https://dx.doi.org/10.2174/2666255813666191227143529