Artificial Intelligence in Optical Communications: From Machine Learning to Deep Learning

نویسندگان

چکیده

Techniques from artificial intelligence have been widely applied in optical communication and networks, evolving early machine learning (ML) to the recent deep (DL). This paper focuses on state-of-the-art DL algorithms aims highlight contributions of communications. Considering characteristics different data types, we review multiple DL-enabled solutions communication. First, a convolutional neural network (CNN) is used for image recognition recurrent (RNN) sequential analysis. A variety functions can be achieved by corresponding through processing collected data-driven channel modeling method also proposed replace conventional block-based improve end-to-end performance. Additionally, generative adversarial (GAN) introduced augmentation expand training dataset rare experimental data. Finally, reinforcement (DRL) perform self-configuration adaptive allocation networks.

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ژورنال

عنوان ژورنال: Frontiers in communications and networks

سال: 2021

ISSN: ['2673-530X']

DOI: https://doi.org/10.3389/frcmn.2021.656786