Improved particle swarm optimization algorithm for enhanced coupling of coaxial optical communication laser

Highlights

• The non-linearly decreasing inertia weight is more suitable for three DOF stage alignment.

• A new relation between the inertia weight and iteration is established.

• The proposed PSO algorithm presents the good performance via simulation and experiment.

• The increase of search coefficient can change the global and local search ability in improved PSO algorithm.

Abstract

In this paper, we investigate a novel improved Particle Swarm Optimization (IPSO) algorithm to enhance the coupling precision between a laser diode and a single-mode fiber. It mainly relies on the nonlinear adjustment of inertia weight. Several variations of PSO are used as references. The simulated and experimental results show that the proposed strategy has an excellent search success rate with few iterations in multi-degree of freedom alignment. This is largely due to the improvement of exploration via the adjustment of inertia weight. These results confirm that the improved PSO algorithm can be applied reliably to improve both the efficiency and accuracy in laser-fiber coupling.

Introduction

In recent years, coaxial optical communication lasers have been extensively adopted in optical fiber industry, owing to the compact size, large transmission capacity and high precision [1], [2], [3], [4], [5], [6]. However, transmission loss and low efficiency of the optical fiber limit the progress in optical communication technology. A primary objective during the fabricating process is to align the optical fibers and lasers for optimal coupling [7]. In other words, it is highly desirable to find a suitable method to auto-couple coaxial optical communication lasers precisely and efficiently.

The coupling for coaxial optical communication lasers occurs in two steps: preliminary alignment and precise alignment. The common preliminary alignment methods [3], [6] include raster search, spiral search and visual localization. Because of the assembling error and a different mode field center, the optical power at the initial position is always small after the preliminary alignment. Hence, the continual adjustment of their relative positions, based on the optimization algorithm, is subsequently performed to increase the optical power emitted from the fibers. Therefore, a high reliable and brief alignment algorithm for automated coupling of lasers and fibers would represent a major milestone with respect to precise alignment. Until now, several algorithms have been reported for the alignment of optical fiber devices [8], [9], [10], [11], [12], [13], [14]. Among these numerical analysis methods, the Hill-climbing algorithm [8] is widely used for fiber-alignment. This is, because it uses a simple mathematical principle and is easy to program. The drawbacks, however, are that it easily trapped in local maxima and minima, and it hardly overcomes the coupling error between various degrees of freedom (DOFs). The Hamilton algorithm [9] has been implemented into optical fiber automatic alignment. It has a faster search speed than the Hill-climbing algorithm. However, this algorithm, which needs to construct the differential equations of the entire motion system, are carried out difficultly and easily get trapped in the local maximum. The pattern search algorithm (PSA) has been investigated as a potential candidate to develop the automatic alignment of optical fibers [10]. The experimental results indicate that it is reliable and is not likely to exhibit local convergence. However, it can only modulate the coupling error of XY two DOFs, while the simultaneous alignment in other directions of freedom is not done.

Different from numerical analysis methods, intelligent optimization algorithms are more suitable for a complex optimization problem. They do not need an explicit mathematical analytic expression to represent the optimization problem. In addition, they usually avoid getting stuck in local optima [11]. H. Nosato et al. [12] investigated a Genetic Algorithm (GA) for automatic optical-fiber alignment. Their experimental results demonstrate that this algorithm is very accurate and has a good ability to avoid the local maximum. The search speed, however, is relatively slow and the used mathematical principle is complex. Liu et al. [13] used the adaptive simulated annealing (ASA) algorithm for the coupling alignment of waveguide and fiber. The different power of diodes can be coupled into the fiber. But the coupling efficiency and accuracy are not analyzed systematically.

Compared with above algorithms, the Particle Swarm Optimization (PSO) algorithm has exhibited good performance in optimizing search. It can adjust the strategy of the global search and local search by changing inertia weight [4], [14], [15], [16]. In a previous study [4], we have investigated the basic PSO algorithm for coupling alignment between SMFs and LDs. The results of simulations and experiments show that the PSO algorithm can facilitate the cross-coupling of the motion in three DOFs with high reliability. However, the constant value of inertia weight severely limits the search speed and coupling accuracy. In this study, a novel improved PSO (IPSO) with nonlinear decreasing law based on GPSO [17] was used for three DOFs simultaneous coupling alignment between an SMF and LD. The basic PSO [4], the GPSO, an exponential-inertia-weight PSO (EPSO) [18] and an adaptive PSO (APSO) [19] were introduced for comparison. Both simulation and experiments, based on several PSO algorithms, were conducted to test the improvement with respect to search speed and coupling efficiency. Finally, we discussed about the above algorithms to compare their advantages and disadvantages for the purpose of achieving a better coupling efficiency.