Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Journal of Lightwave Technology
  • Vol. 23,
  • Issue 3,
  • pp. 1219-
  • (2005)

Statistics of Polarization-Dependent Gain in Fiber Raman Amplifiers

Not Accessible

Your library or personal account may give you access

Abstract

We developed an analytical model for the statistics of polarization-dependent gain (PDG) in both copumped and counterpumped fiber Raman amplifiers (FRAs). The validity of this model was confirmed by using experimental data and numerical simulations. The results show that the PDG in a counterpumped FRA cannot be neglected since it is only about 3 times smaller than that in a copumped FRA. Using the proposed model, we also evaluated the effects of various parameters on the PDG including the wavelength difference between the signal and pump,degree-of-polarization (DOP) of pump laser, polarization-mode dispersion,and fiber loss at the pump wavelength. In addition, the proposed model was used to analyze the requirement of the DOP of pump for the suppression of PDG within 1 dB.

© 2005 IEEE

PDF Article
More Like This
Statistics of polarization-dependent gain in fiber-based Raman amplifiers

Q. Lin and Govind P. Agrawal
Opt. Lett. 28(4) 227-229 (2003)

Polarization dependent gain in Raman fiber amplifiers with multiple pumps

Junhe Zhou, Wang Yuheng, and Tengyuan Liu
Opt. Express 32(4) 5692-5704 (2024)

Efficient numerical method for predicting the polarization-dependent Raman gain in fiber Raman amplifiers

Minming Zhang, Deming Liu, Ying Wang, and Dexiu Huang
J. Opt. Soc. Am. A 21(2) 263-266 (2004)

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.