Next Article in Journal
Multi-Turn Chatbot Based on Query-Context Attentions and Dual Wasserstein Generative Adversarial Networks
Next Article in Special Issue
Reduced-Complexity Artificial Neural Network Equalization for Ultra-High-Spectral-Efficient Optical Fast-OFDM Signals
Previous Article in Journal
Learning to Measure Stereoscopic S3D Image Perceptual Quality on the Basis of Binocular Rivalry Response
Previous Article in Special Issue
A Simple Joint Modulation Format Identification and OSNR Monitoring Scheme for IMDD OOFDM Transceivers Using K-Nearest Neighbor Algorithm
Open AccessArticle

Optimization Algorithms of Neural Networks for Traditional Time-Domain Equalizer in Optical Communications

1
Department of Electronic Engineering, College of Information Science and Technology, Jinan University, Guangzhou 510632, China
2
Huawei Technologies Duesseldorf GmbH, European Research Center, 80992 Munich, Germany
3
Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hong Kong, China
4
State Key Laboratory of Optoelectronic Materials and Technologies, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510275, China
5
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2019, 9(18), 3907; https://doi.org/10.3390/app9183907
Received: 20 August 2019 / Revised: 13 September 2019 / Accepted: 15 September 2019 / Published: 18 September 2019
(This article belongs to the Special Issue Optics for AI and AI for Optics)
Neural networks (NNs) have been successfully applied to channel equalization for optical communications. In optical fiber communications, the linear equalizer and the nonlinear equalizer with traditional structures might be more appropriate than NNs for performing real-time digital signal processing, owing to its much lower computational complexity. However, the optimization algorithms of NNs are useful in many optimization problems. In this paper, we propose and evaluate the tap estimation schemes for the equalizer with traditional structures in optical fiber communications using the optimization algorithms commonly used in the NNs. The experimental results show that adaptive moment estimation algorithm and batch gradient descent method perform well in the tap estimation of equalizer. In conclusion, the optimization algorithms of NNs are useful in the tap estimation of equalizer with traditional structures in optical communications. View Full-Text
Keywords: neural networks; optical communications; optimization; equalizer; tap estimation neural networks; optical communications; optimization; equalizer; tap estimation
Show Figures

Graphical abstract

MDPI and ACS Style

Wang, H.; Zhou, J.; Wang, Y.; Wei, J.; Liu, W.; Yu, C.; Li, Z. Optimization Algorithms of Neural Networks for Traditional Time-Domain Equalizer in Optical Communications. Appl. Sci. 2019, 9, 3907.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop