A Novel Design Approach for Erbium-Doped Fiber Amplifiers by Particle Swam Optimization
Alireza Mowla
and
Nosrat Granpayeh
A novel design approach for erbium-doped fiber amplifiers is proposed based on particle swarm optimization algorithm. The main six parameters of the EDFAs including: pumping wavelength, input signal power, fiber numerical aperture, erbium-doped area radius, erbium concentration, and the fiber length are optimized utilizing a fast and efficient method called particle swarm optimization algorithm. In this paper, a combination of fiber amplifier bandwidth, gain, and flatness are taken into account as objective function and the results are presented for different pump powers. Our investigation shows that particle swarm optimization algorithm outperforms genetic algorithm in convergence speed, straightforwardness, and coping with highdimensional spaces, when the parameters of EDFA are to be optimized. It has been shown that the required time for the optimization of the fiber amplifier parameters is reduced four times by using particle swarm optimization algorithm, compared to genetic algorithm method.
