基于局部优化SFLA的VCSEL模型参数识别

垂直腔面发射激光器(VCSEL)是光纤通信系统的重要光源,精确的参数是光纤通信仿真分析取得正确结果的必要因素. 通过实验测得激光器L-I-V关系和小信号响应,引入混合蛙跳算法(SFLA)来实现参数搜索. 针对经典SFLA收敛速度慢、子群易陷入局部最优的缺点,引入NM单一形状搜索法改进局部搜索方案. 实验结果表明,局部优化SFLA在本工作中收敛速度更快、适应度更优,可准确实现对VCSEL实际参数的识别.

Parameter Identification of VCSEL Model Based on Local Optimized SFLA

Vertical cavity surface emitting laser(VCSEL)is an important source of optical fiber communication system. The accurate parameters are the key factors to achieve the correct results of optical fiber communication simulation analysis. Based on the experimental results of the relationship between Light-Current-Voltage(L-I-V)characteristics and the small signal response of the laser,we introduce a shuffled frog leaping algorithm(SFLA)to realize the parameter search. In view of the shortcomings of the slow convergence rate of classical SFLA and easiness to fall into local optimal subgroups,the NM single shape search method is introduced to improve the local search scheme. The experimental results show that the local optimization SFLA has faster convergence speed and better adaptability,and that it can accurately identify the actual parameters of VCSEL.