End-to-end learning for VCSEL-based optical interconnects: State-of-the-art, challenges, and opportunities
Optical interconnects (OIs) based on vertical-cavity surface-emitting lasers (VCSELs) are the
main workhorse within data centers, supercomputers, and even vehicles, providing low-cost …
main workhorse within data centers, supercomputers, and even vehicles, providing low-cost …
Extraction of sift features for identifying disaster hit areas using machine learning techniques
Beyond the death toll, disasters have major and often devastating social and economic
ramifications, including financial damage and loss. As a result of recent advances in artificial …
ramifications, including financial damage and loss. As a result of recent advances in artificial …
High-speed underwater optical wireless communication with advanced signal processing methods survey
Underwater wireless communication (UWC) technology has attracted widespread attention
in the past few years. Compared with conventional acoustic underwater wireless …
in the past few years. Compared with conventional acoustic underwater wireless …
[HTML][HTML] Advanced Neural Network-Based Equalization in Intensity-Modulated Direct-Detection Optical Systems: Current Status and Future Trends
Intensity-modulated direct-detection (IM/DD) optical systems are most widely employed in
short-reach optical interconnects due to their simple structure and cost-effectiveness …
short-reach optical interconnects due to their simple structure and cost-effectiveness …
Machine learning enhanced next-generation optical access networks—challenges and emerging solutions [Invited Tutorial]
Optical access networks are envisioned to become increasingly complex as they support
more and more diverse and immersive services, each with a different capacity, latency, and …
more and more diverse and immersive services, each with a different capacity, latency, and …
High-performance end-to-end deep learning IM/DD link using optics-informed neural networks
In this paper, we introduce optics-informed Neural Networks and demonstrate
experimentally how they can improve performance of End-to-End deep learning models for …
experimentally how they can improve performance of End-to-End deep learning models for …
Serial and parallel convolutional neural network schemes for NFDM signals
Two conceptual convolutional neural network (CNN) schemes are proposed, developed and
analysed for directly decoding nonlinear frequency division multiplexing (NFDM) signals …
analysed for directly decoding nonlinear frequency division multiplexing (NFDM) signals …
Digital Predistortion Based Experimental Evaluation of Optimized Recurrent Neural Network for 5G Analog Radio Over Fiber Links
In the context of Enhanced Remote Area Communications (ERAC), Radio over Fiber (RoF)
technology plays a crucial role in extending reliable connectivity to underserved and remote …
technology plays a crucial role in extending reliable connectivity to underserved and remote …
Addressing concept drift of dynamic traffic environments through rapid and self-adaptive bandwidth allocation
Passive optical networks are envisioned to become increasingly complex as they support
more and more diverse and immersive services that have different capacity, latency, and …
more and more diverse and immersive services that have different capacity, latency, and …
Intelligent equally weighted multi-task learning for joint OSNR monitoring and modulation format identification
Y Zhang, P Zhou, C Dong, Y Lu, L Chuanqi - Optical Fiber Technology, 2022 - Elsevier
A novel scheme for combining modulation format identification (MFI) and optical
performance monitoring (OPM) in elastic optical networks using convolutional-neural …
performance monitoring (OPM) in elastic optical networks using convolutional-neural …