For the efficient dynamic dispersion compensation, it is essential to monitor the dispersion accurately. The existing main dispersion monitoring techniques in high bit-rate optical communication systems are presented ...For the efficient dynamic dispersion compensation, it is essential to monitor the dispersion accurately. The existing main dispersion monitoring techniques in high bit-rate optical communication systems are presented as well as their operating principles and research progress. The advantages and disadvantages of these methods are analyzed and discussed.展开更多
Low-cost,flexible and intelligent optical performance monitoring and management is a key enabling technology for network quality guarantee,especially in the era of explosive growth of communication capacity and networ...Low-cost,flexible and intelligent optical performance monitoring and management is a key enabling technology for network quality guarantee,especially in the era of explosive growth of communication capacity and network scale.However,to the best of our knowledge,it is extremely challenging to implement real-time performance monitoring and operations,administration and maintenance(OAM) in a highly complex dynamic network.In this paper,we propose an innovative optical identification(OID) scheme that can realize both performance monitoring and some advanced OAM sub-functions.The basic concepts,applications,challenges and evolution directions of this OID tool are also discussed.展开更多
A designed visual geometry group(VGG)-based convolutional neural network(CNN)model with small computational cost and high accuracy is utilized to monitor pulse amplitude modulation-based intensity modulation and direc...A designed visual geometry group(VGG)-based convolutional neural network(CNN)model with small computational cost and high accuracy is utilized to monitor pulse amplitude modulation-based intensity modulation and direct detection channel performance using eye diagram measurements.Experimental results show that the proposed technique can achieve a high accuracy in jointly monitoring modulation format,probabilistic shaping,roll-off factor,baud rate,optical signal-to-noise ratio,and chromatic dispersion.The designed VGG-based CNN model outperforms the other four traditional machine-learning methods in different scenarios.Furthermore,the multitask learning model combined with MobileNet CNN is designed to improve the flexibility of the network.Compared with the designed VGG-based CNN,the MobileNet-based MTL does not need to train all the classes,and it can simultaneously monitor single parameter or multiple parameters without sacrificing accuracy,indicating great potential in various monitoring scenarios.展开更多
文摘For the efficient dynamic dispersion compensation, it is essential to monitor the dispersion accurately. The existing main dispersion monitoring techniques in high bit-rate optical communication systems are presented as well as their operating principles and research progress. The advantages and disadvantages of these methods are analyzed and discussed.
基金supported in part by the National Key R&D Program of China under Grant No.2019YFB2205302。
文摘Low-cost,flexible and intelligent optical performance monitoring and management is a key enabling technology for network quality guarantee,especially in the era of explosive growth of communication capacity and network scale.However,to the best of our knowledge,it is extremely challenging to implement real-time performance monitoring and operations,administration and maintenance(OAM) in a highly complex dynamic network.In this paper,we propose an innovative optical identification(OID) scheme that can realize both performance monitoring and some advanced OAM sub-functions.The basic concepts,applications,challenges and evolution directions of this OID tool are also discussed.
基金supported by the National Key Research and Development Program of China (Grant No.2019YFB1803700)the Key Technologies Research and Development Program of Tianjin (Grant No.20YFZCGX00440).
文摘A designed visual geometry group(VGG)-based convolutional neural network(CNN)model with small computational cost and high accuracy is utilized to monitor pulse amplitude modulation-based intensity modulation and direct detection channel performance using eye diagram measurements.Experimental results show that the proposed technique can achieve a high accuracy in jointly monitoring modulation format,probabilistic shaping,roll-off factor,baud rate,optical signal-to-noise ratio,and chromatic dispersion.The designed VGG-based CNN model outperforms the other four traditional machine-learning methods in different scenarios.Furthermore,the multitask learning model combined with MobileNet CNN is designed to improve the flexibility of the network.Compared with the designed VGG-based CNN,the MobileNet-based MTL does not need to train all the classes,and it can simultaneously monitor single parameter or multiple parameters without sacrificing accuracy,indicating great potential in various monitoring scenarios.
