Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
  • Journal of Lightwave Technology
  • Vol. 18,
  • Issue 7,
  • pp. 922-
  • (2000)

Comparison of Conventional and Gain-Clamped Semiconductor Optical Amplifiers for Wavelength-Division-Multiplexed Transmission Systems

Not Accessible

Your library or personal account may give you access

Abstract

We compare the output spectra and data streams of a conventional 1550-nm semiconductor optical amplifier (SOA) with its gain-clamped (GCSOA) counterpart, in order to assess the impact of gain clamping on cross-gain modulation (XGM) and difference frequency generation (DFG). Whereas the conventional SOA exhibits a large amount of crosstalk due to XGM, there is virtually no XGM present in the GCSOA. However, the XGM effect in the SOA shows evidence of diminished efficiency at moderate input levels. We observe much higher DFG levels from the GCSOA (roughly 10 dB greater than the SOA). These DFG levels are such that cascaded wavelength cross-connect devices, in-line amplifiers,and even optical gates could experience inhibited performance.

[IEEE ]

PDF Article
More Like This
Strong tunable slow and fast lights using a gain-clamped semiconductor optical amplifier

S. H. Moon, J. Park, J. M. Oh, N. J. Kim, D. Lee, S. W. Chang, D. Nielsen, and S. L. Chuang
Opt. Express 17(23) 21222-21227 (2009)

Phase-sensitively amplified wavelength-division multiplexed optical transmission systems

Kovendhan Vijayan, Zonglong He, Benjamin Foo, Jochen Schröder, Magnus Karlsson, and Peter A. Andrekson
Opt. Express 29(21) 33086-33096 (2021)

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.