2011
DOI: 10.1109/jphot.2011.2140366
|View full text |Cite
|
Sign up to set email alerts
|

Optimization of Distributed Raman Amplifiers Using a Hybrid Genetic Algorithm With Geometric Compensation Technique

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
18
0
2

Year Published

2013
2013
2024
2024

Publication Types

Select...
8

Relationship

0
8

Authors

Journals

citations
Cited by 36 publications
(23 citation statements)
references
References 13 publications
0
18
0
2
Order By: Relevance
“…In this simulation we assumed that the lossy fiber has a length of about 10 Km. Runge-Kutta and a shooting method is used to solve the pump and signal interaction equations [21]. Our goal is to minimize the gain ripple in the C-L band by utilizing of the FAMPSO method to introduce optimizing sixteen parameters; the wavelengths and power levels for the 8 pumps range are from 1420 nm -1520 nm and 0 mW -120 mW respectively.…”
Section: Numerical Resultsmentioning
confidence: 99%
“…In this simulation we assumed that the lossy fiber has a length of about 10 Km. Runge-Kutta and a shooting method is used to solve the pump and signal interaction equations [21]. Our goal is to minimize the gain ripple in the C-L band by utilizing of the FAMPSO method to introduce optimizing sixteen parameters; the wavelengths and power levels for the 8 pumps range are from 1420 nm -1520 nm and 0 mW -120 mW respectively.…”
Section: Numerical Resultsmentioning
confidence: 99%
“…Therefore, a proper combination of different pump lasers operating in a particular set of wavelengths with specific optical powers has to be used in order to maximize gain while maintaining acceptable levels of gain ripple. [9][10][11][12][13][14] due to the implementation simplicity inherent to GAs. 1 The design of such multipump Raman amplifiers can be treated as a multiple-objective optimization problem 3 since it requires the optimization of multiple and often conflicting parameters, such as gain, ripple, and number of pump lasers.…”
Section: Introductionmentioning
confidence: 99%
“…To overcome this issue and effectively reduce time consumption, the use of a simplified analytical 5,12 or semianalytical 9 solution has been proposed for the calculation of the Raman gain profile. Moreover, previous reports of optimizations of multipump Raman amplifiers based on analytical calculation of the Raman gain profile 5,9,12 still present issues concerning the time consumption due to the use of slow optimization heuristics needing a huge number of iterations to achieve the desired result. Moreover, previous reports of optimizations of multipump Raman amplifiers based on analytical calculation of the Raman gain profile 5,9,12 still present issues concerning the time consumption due to the use of slow optimization heuristics needing a huge number of iterations to achieve the desired result.…”
Section: Introductionmentioning
confidence: 99%
“…Gustavo et. al [12] proposed an accurate method for a Raman Amplifier model for extended C and C+L band by combining a hybrid genetic algorithm with a geometric compensation technique and determined pump wavelengths and powers using minimum number of pumps intended to meet the specifications. In [13], Carmelo et.…”
Section: Introductionmentioning
confidence: 99%
“…al presented another multi-objective particle swarm optimizer to define the number of pump lasers and their wavelengths and powers. While multiparameter optimization was adopted for RFA in [12,13], but the Raman length was not optimized in parallel. In spite of the numerous works on the optimization of RFA, researchers had not shown much optimization work for On the Optimization of Raman Fiber Amplifier using Genetic Algorithm in … -Simranjit Singh et al…”
Section: Introductionmentioning
confidence: 99%