Design of a flattening filter using Fiber Bragg Gratings for EDFA gain equalization: an artificial neural network application

Abstract


 
 
 This paper presents a proposal for the non-uniform gain compensation of an Erbium-doped fiber optic amplifier (EDFA) in a Wavelength Division Multiplexed (WDM) system using Fiber Bragg Gratings (FBG). In this proposal, the multilayer perceptron feed-forward artificial neural network with backpropagation was trained under the secant method (one-step secant) and was selected according to mean square error measurement. The proposal optimizes FBG parameters such as center frequency, rejection level and length in order to determine a filtering response based on a reduced number of FBGS that will be used to flatten the non-linear response of the amplifier gain and avoid the per-carrier treatment of a standard flattening filter. While an artificial neural network with a 7-10-6 structure demonstrated the feasibility of equalizing the gain of an EDFA using as few as three FBGS, a 25-18-12 structure improved the results when the configuration consisted of an FBG array of six resonances that provided similar results to that featured by the standard gain-flattening filter. The proposal was evaluated in an amplified WDM system of eight optical carriers located between 195-196.4 THz.
 
 

A Comprehensive Study on EDFA Gain Flattening for WDM Transmission using Cascaded Fiber Bragg Gratings

“…However, the center frequency of an FBG resonance is not always the central frequency of an optical carrier. When compared to the system without equalization, the system based on three FBGs had an improvement factor of 18.51, while the system based on six FBGs had an improvement factor of 149 [11].…”

“…P 5;2 coveys the traveling wave equation, and therefore, it can be expressed as [16] e1 #$% Oc = (𝛤. 𝑔_𝑁, 𝑣 _ a − 𝛼 : ) P 5;2 + 𝑅 :G (11) where 𝑅 :G represents the local spontaneously generated noise.…”

Edición especial en Ingeniería Eléctrica, Telecomunicaciones y Ciencias de la Computación

“…◾ Desing of a flattening filter using fiber bragg gratings for edfa gain equalization: an artificial neural network application [2].…”

“…En [1] se caracterizan los efectos de interferencia entre canales en sistemas Nquist-WDM, utilizando como parámetro de evaluación el Bit Error Rate (ber). En [2] se propone una optimización de los parámetros de Fiber Bragg Gratings (fbg) correspondientes a la frecuencia central, el nivel de rechazo y longitud del filtro, para compensar la ganancia no uniforme de los amplificadores ópticos Erbium-Doped Fiber optic Amplifier (edfa).…”