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山东大学学报 (工学版) ›› 2019, Vol. 49 ›› Issue (1): 17-22.doi: 10.6040/j.issn.1672-3961.0.2018.196

• 机器学习与数据挖掘 • 上一篇    下一篇

高速光通信激光器带宽模型改进与并行计算优化

杨思1(),李思童2,张进东3,白羽4,*()   

  1. 1. 北京建筑大学机电与车辆工程学院, 北京 100044
    2. 北京建筑大学土木与交通工程学院, 北京 100044
    3. 中国科学院大学中国科学院计算机研究所, 北京 100083
    4. 北京建筑大学理学院建筑结构与环境修复功能材料北京市重点实验室, 北京 100044
  • 收稿日期:2018-05-25 出版日期:2019-02-20 发布日期:2019-03-01
  • 通讯作者: 白羽 E-mail:1262421800@qq.com;baiyu@bucea.edu.cn
  • 作者简介:杨思(1994—)，男，北京人，硕士研究生，主要研究方向为人工智能和信号处理. E-mail：1262421800@qq.com
  • 基金资助:
    国家自然基金项目(21576023);国家自然基金项目(51406008);“十三五”重点研发计划项目(2016YFC0700601);北京建筑大学市属高校科研业务基本经费项目(X18122);北京建筑大学市属高校科研业务基本经费项目(X18087)

Improvement of bandwidth model for high speed optical communicationlaser and its optimization by parallel computing

Si YANG1(),Sitong LI2,Jindong ZHANG3,Yu BAI4,*()   

  1. 1. School of Mechanical-Electronic and Vehicle Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
    2. School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
    3. Institute of Computing Technology, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing 100083, China
    4. Beijing Key Laboratory of Functional Materials for Building Structure and Environment Remediation, School of Science, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
  • Received:2018-05-25 Online:2019-02-20 Published:2019-03-01
  • Contact: Yu BAI E-mail:1262421800@qq.com;baiyu@bucea.edu.cn
  • Supported by:
    国家自然基金项目(21576023);国家自然基金项目(51406008);“十三五”重点研发计划项目(2016YFC0700601);北京建筑大学市属高校科研业务基本经费项目(X18122);北京建筑大学市属高校科研业务基本经费项目(X18087)

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摘要：

为适应高速传输的网络需求,需要优化光线通信激光器特性。利用垂直腔面发射激光器(vertical cavity surface emitting laser, VCSEL)实测输出的数据,对激光器热传感模型进行改进。模型改进过程中,使用量子速率方程描述VCSEL的特性,考虑到增益常数与温度之间的关系,用高阶拟合方法优化激光器带宽系统,与实测数据更加接近。结合下一代高速网络需求,采用并行数据挖掘思想,利用缓冲器加快求解速度。结果表明:输出光功率在高温和大量注入电流下会出现热饱和下降;优化后的模型更贴近实测数据,遗传算法对于系统规模变化的适应性很强,给出的规划线路具备可靠性;基于状态机的并行数据处理方法使得模型计算速度提高了9.15%。在考虑热限制的同时,实现了新一代光纤通信高速传输需求。

关键词: 垂直腔面发射激光器, 热分析, 带宽模型, 并行计算, 数据挖掘

Abstract:

In order to adapt to high-speed network, features of optical fiber communication laser need to be optimized. Laser thermal sensing model was improved by measuring the data exported by vertical cavity surface emitting laser (VCSEL). In the modified model, the quantum rate equation was developed to describe features of laser VCSEL. Considering the relationship between the gain constant, the transparent current carriers and the temperature, the high order fitting method was introduced to optimize the laser bandwidth system, which maked it closer to the measured data. Meanwhile, based on the parallel data mining method, the buffer helped to speed up the solving process to satisfy the demand of the next-generation high-speed network. The results showed that the output light power appeared to decrease in thermal saturation under the high temperature and large injection current. The model after optimization was closer to the actual measured data, genetic algorithm had a strong adaptability towards scale change of system, and the route planned by algorithm was reliable. The calculation speed was increased by 9.15% based on parallel data processing method. This modified model met the demand of the new-generation high-speed fiber optic communication, and considered the thermal limitation.

Key words: VCSEL, thermal analysis, bandwidth model, parallel computation, data mining

中图分类号: 

  • TP391.9

图1

VCSEL激光器结构示意图"

图2

最大光功率随温度变化图"

图3

激光器幅频响应曲线"

表1

参数迭代后结果"

类型 ηi β/10-6 τn/ns k/μW G0/Ms-1 N0/106 τp/ps ε/10-8
初值 0.700 0 10.00 9.6 0.015 1.8 0.497 3.80 4.7
迭代计算后 0.564 2 8.38 17.9 7.526 1 751.0 3.193 5.91 9.3

图4

小信号驱动模型的光功率幅值优化过程"

图5

实测曲线与仿真曲线对比图"

图6

7.5 mA的偏置电流不同环境温度下的带宽响应曲线"

图7

20 ℃下不同偏置电流的带宽响应曲线"

表2

参数优化结果"

参数 a0 a1 a2 b0 b1 b2
优化结果 46.402 7 88.627 8 17.591 0 85.025 7 99.982 5 65.045 8

图8

新模型与实测数据的仿真曲线对比"

图9

基于MapReduce的遗传算法过程"

图10

参数复用状态机"

表3

集群环境下实时计算性能对比"

系统运行次序 并行计算时延/s 串联计算时延/s
1 0.525 0.575
2 0.535 0.557
3 0.554 0.657
4 0.527 0.574
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