Artificial Intelligence (AI) Methods in Optical Networks: A Comprehensive Survey
arXiv:1801.01704 · doi:10.1016/j.osn.2017.12.006
Abstract
Artificial intelligence (AI) is an extensive scientific discipline which enables computer systems to solve problems by emulating complex biological processes such as learning, reasoning and self-correction. This paper presents a comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks. The use of AI-based techniques is first studied in applications related to optical transmission, ranging from the characterization and operation of network components to performance monitoring, mitigation of nonlinearities, and quality of transmission estimation. Then, applications related to optical network control and management are also reviewed, including topics like optical network planning and operation in both transport and access networks. Finally, the paper also presents a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.
References in corpus (1)
Cited by in corpus (8)
- Machine Learning for Intelligent Optical Networks: A Comprehensive Survey
- Application of Machine Learning in Fiber Nonlinearity Modeling and Monitoring for Elastic Optical Networks
- Time-Series Pattern Recognition in Smart Manufacturing Systems: A Literature Review and Ontology
- Survey on Machine Learning for Traffic-Driven Service Provisioning in Optical Networks
- Equalization of a 10 Gbps IMDD signal by a small silicon photonics time delayed neural network
- The Next Decade of Telecommunications Artificial Intelligence
- Centralized and Distributed Machine Learning-Based QoT Estimation for Sliceable Optical Networks
- Optimal Control of SOAs with Artificial Intelligence for Sub-Nanosecond Optical Switching