In this paper, we propose a longitudinal cascaded few-mode erbium-doped fiber amplifier (FM-EDFA) by particle swarm optimization (PSO). Triple-cascaded few-mode erbium-doped fibers (FM-EDFs) are applied longitudinally, which have the same refractive index distributions and different erbium-ion doping profiles. Each fiber is uniformly doped in different regions. The input power of the pump and signal are settled. The length and order of three pieces of FM-EDFs are optimized by PSO, which helps to minimize the differential modal gain (DMG) and maximize the modal gain at the output port. An ultra-low DMG of 0.007 dB and minimum modal gain (MMG) of about 24.890 dB are obtained at the wavelength of 1550 nm.
A coupled multi-core fiber (CMCF) with selective erbium ions doping is proposed. Due to the small gap between the cores, four signal supermodes are supported. Based on the overlap integral between the signal and pump modes, the concentration proportion of the central core to outer cores is modified. At a concentration ratio of 0.93, the signal gains are higher than 20 dB and at the same time, a small differential modal gain (DMG) of 0.17 dB is obtained.
Few-mode erbium-doped fiber amplifier (FM-EDFA) is a key element to realize signal gain compensation in a longdistance mode division multiplexing (MDM) system. The differential modal gain (DMG) between modes directly affects the communication quality of the MDM system. In this paper, the particle swarm optimization (PSO) method is applied to design the erbium ion doping profile for high gain and low DMG simultaneously. By adjusting the doping radius and concentration concurrently, both high signal gains and low DMG can be obtained. In the conditions of the core pump and cladding pump respectively, the erbium ion with a multi-layered doping profile is automatically optimized by the PSO for a few-mode erbium-doped fiber (FM-EDF). Results show that as a three-layered ion adjustment, the gain is higher than 20 dB and DMG is lower than 0.15 dB in a four-mode step-index fiber. PSO is easy to implement and simple to operate. Compared with the other intelligent methods, such as the genetic algorithm or gradient descent optimization algorithm, PSO has no "crossover" and "mutation". The optimization time is greatly reduced. The PSO-based fiber design provides new guidance for the improvement of fiber gain equalization.
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