Blockchain and machine learning for communications and networking systems
Recently, with the rapid development of information and communication technologies, the
infrastructures, resources, end devices, and applications in communications and networking …
infrastructures, resources, end devices, and applications in communications and networking …
Machine learning techniques for optical performance monitoring and modulation format identification: A survey
The trade-off between more user bandwidth and quality of service requirements introduces
unprecedented challenges to the next generation smart optical networks. In this regard, the …
unprecedented challenges to the next generation smart optical networks. In this regard, the …
Machine learning meets communication networks: Current trends and future challenges
The growing network density and unprecedented increase in network traffic, caused by the
massively expanding number of connected devices and online services, require intelligent …
massively expanding number of connected devices and online services, require intelligent …
Enabling AI in future wireless networks: A data life cycle perspective
Recent years have seen rapid deployment of mobile computing and Internet of Things (IoT)
networks, which can be mostly attributed to the increasing communication and sensing …
networks, which can be mostly attributed to the increasing communication and sensing …
Toward 6G internet of things and the convergence with RoF system
N Chen, M Okada - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
The Internet of Things (IoT) has been a promising communication paradigm that involves
sensors, microcontrollers, and transceivers for an efficient communication and computation …
sensors, microcontrollers, and transceivers for an efficient communication and computation …
Data-driven optical fiber channel modeling: A deep learning approach
A data-driven fiber channel modeling method based on deep learning (DL) is introduced in
an optical communication system. In this study, bidirectional long short-term memory …
an optical communication system. In this study, bidirectional long short-term memory …
End-to-end optimization of coherent optical communications over the split-step Fourier method guided by the nonlinear Fourier transform theory
Optimizing modulation and detection strategies for a given channel is critical to maximizing
the throughput of a communication system. Such an optimization can be easily carried out …
the throughput of a communication system. Such an optimization can be easily carried out …
[HTML][HTML] Overview on routing and resource allocation based machine learning in optical networks
For optical networks, routing and resource allocation which considerably determines the
resource efficiency and network capacity is one of the most important works. It has been …
resource efficiency and network capacity is one of the most important works. It has been …
Combining nonlinear Fourier transform and neural network-based processing in optical communications
We propose a method to improve the performance of the nonlinear Fourier transform (NFT)-
based optical transmission system by applying the neural network post-processing of the …
based optical transmission system by applying the neural network post-processing of the …
AI-based modeling and monitoring techniques for future intelligent elastic optical networks
With the development of 5G technology, high definition video and internet of things, the
capacity demand for optical networks has been increasing dramatically. To fulfill the capacity …
capacity demand for optical networks has been increasing dramatically. To fulfill the capacity …