4.7 Article

Implementing Neural Network-Based Equalizers in a Coherent Optical Transmission System Using Field-Programmable Gate Arrays

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Engineering, Electrical & Electronic

Reducing Computational Complexity of Neural Networks in Optical Channel Equalization: From Concepts to Implementation

Pedro J. Freire et al.

Summary: This paper introduces a new method for developing low-complexity neural network (NN) based equalizers for high-speed coherent optical transmission systems. Deep model compression techniques applied to feed-forward and recurrent NN designs are explored and compared, with a focus on their impact on equalizer performance. A Bayesian optimization-assisted compression approach is proposed and evaluated, optimizing hyperparameters to simultaneously enhance performance and reduce complexity. Additionally, metrics are introduced to quantify computing complexity in various compression algorithms, serving as benchmarks for evaluating the effectiveness of NN equalizers with compression. The trade-off between compression complexity and performance is evaluated using simulated and experimental data.

JOURNAL OF LIGHTWAVE TECHNOLOGY (2023)

Article Engineering, Electrical & Electronic

Fixed-Point Analysis and FPGA Implementation of Deep Neural Network Based Equalizers for High-Speed PON

Noriaki Kaneda et al.

Summary: This article proposes a deep neural network based equalizer to tackle the intersymbol interference in high speed passive optical network (PON) links. The performance of the DNN based equalizer is found to be superior to the conventional equalizer in both back-back and through fiber experiments. To reduce hardware complexity, the article investigates embedded parallelization and classification output stage, and analyzes the impact of fixed-point resolution on hardware resource utilization.

JOURNAL OF LIGHTWAVE TECHNOLOGY (2022)

Article Optics

Real-time FPGA prototyping of a 15GBaud SP-16QAM coherent optical receiver with optimal interpolating for clock recovery and equalization

Jingwei Song et al.

Summary: We demonstrate a real-time coherent optical receiver based on a single FPGA chip. Comparing with traditional schemes, the optimal interpolator significantly reduces the utilization of hardware resources and can work properly under different optical powers.

OPTICS EXPRESS (2022)

Proceedings Paper Computer Science, Artificial Intelligence

Learnable Lookup Table for Neural Network Quantization

Longguang Wang et al.

Summary: This paper proposes a learning lookup table method for neural network quantization, which has smaller computational overhead compared to existing methods and can adapt to different distributions in different layers. Experimental results show that quantized networks using this method achieve state-of-the-art performance in multiple tasks.

2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR) (2022)

Article Engineering, Electrical & Electronic

Performance Versus Complexity Study of Neural Network Equalizers in Coherent Optical Systems

Pedro J. Freire et al.

Summary: The study compared the performance and complexity of different artificial neural networks for nonlinear channel equalization in coherent optical communication systems. The CNN+biLSTM architecture showed the largest Q-factor improvement and was the best option when computational complexity was not constrained. However, when complexity was restricted to lower levels, the three-layer perceptron performed best.

JOURNAL OF LIGHTWAVE TECHNOLOGY (2021)

Article Engineering, Electrical & Electronic

Transfer Learning for Neural Networks-Based Equalizers in Coherent Optical Systems

Pedro J. Freire et al.

Summary: In this work, the adaptability of artificial neural networks (NNs) used for impairments mitigation in optical transmission systems is addressed through transfer learning techniques. The study demonstrates the effectiveness of retraining NN-based equalizers to adapt to changes in the transmission system with just a fraction of the initial training data or epochs. Transfer learning proves to be efficient in adapting NN architectures to different transmission regimes and scenarios, showing promise for engineering flexible and universal solutions for nonlinearity mitigation in coherent optical communication systems.

JOURNAL OF LIGHTWAVE TECHNOLOGY (2021)

Article Engineering, Electrical & Electronic

Complex-Valued Neural Network Design for Mitigation of Signal Distortions in Optical Links

Pedro J. Freire et al.

Summary: Nonlinearity compensation is crucial for increasing channel transmission rates in optical communication systems. Data-driven approaches using neural networks have shown to improve the performance of complex fiber-optic systems without prior knowledge of specific parameters. The proposed neural network design, optimized using a Bayesian optimizer, has successfully demonstrated improved performance in both linear and nonlinear regimes of fiber-optic communication.

JOURNAL OF LIGHTWAVE TECHNOLOGY (2021)

Article Computer Science, Information Systems

An FPGA-Based LSTM Acceleration Engine for Deep Learning Frameworks

Dazhong He et al.

Summary: This paper introduces an implementation scheme for an LSTM network acceleration engine based on FPGA, which is optimized through fixed-point arithmetic, systolic array, and lookup table. The proposed acceleration engine is integrated into Caffe for easy deployment and application, achieving significant performance and energy efficiency improvements compared to CPU and GPU within the Caffe framework.

ELECTRONICS (2021)

Article Computer Science, Information Systems

Towards Test-Driven Development for FPGA-Based Modules Across Abstraction Levels

Julian Caba et al.

Summary: High-Level Synthesis (HLS) tools assist engineers in dealing with the complexity of building heterogeneous embedded systems and introducing software industry techniques like Test-Driven Development (TDD) to hardware design. However, HLS tools have limited support for verification activities.

IEEE ACCESS (2021)

Article Engineering, Electrical & Electronic

Nonlinearity mitigation with a perturbation based neural network receiver

Marina M. Melek et al.

OPTICAL AND QUANTUM ELECTRONICS (2020)

Proceedings Paper Computer Science, Information Systems

Recurrent Neural Network Soft-Demapping for Nonlinear ISI in 800Gbit/s DWDM Coherent Optical Transmissions

Maximilian Schaedler et al.

2020 EUROPEAN CONFERENCE ON OPTICAL COMMUNICATIONS (ECOC) (2020)

Proceedings Paper Engineering, Electrical & Electronic

Neural Networks and FPGA Hardware Accelerators for Millimeter-Wave Radio-over-Fiber Systems

Jeonghun Lee et al.

2020 22ND INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS (ICTON 2020) (2020)

Proceedings Paper Computer Science, Hardware & Architecture

High-Throughput Convolutional Neural Network on an FPGA by Customized JPEG Compression

Hiroki Nakahara et al.

28TH IEEE INTERNATIONAL SYMPOSIUM ON FIELD-PROGRAMMABLE CUSTOM COMPUTING MACHINES (FCCM) (2020)

Article Engineering, Electrical & Electronic

Compensation of Fiber Nonlinearities in Digital Coherent Systems Leveraging Long Short-Term Memory Neural Networks

Stavros Deligiannidis et al.

JOURNAL OF LIGHTWAVE TECHNOLOGY (2020)

Article Computer Science, Hardware & Architecture

Design Space Exploration of Neural Network Activation Function Circuits

Tao Yang et al.

IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS (2019)

Article Multidisciplinary Sciences

Field and lab experimental demonstration of nonlinear impairment compensation using neural networks

Shaoliang Zhang et al.

NATURE COMMUNICATIONS (2019)

Article Engineering, Electrical & Electronic

ASIC Implementation of Time-Domain Digital Back Propagation for Coherent Receivers

Christoffer Fougstedt et al.

IEEE PHOTONICS TECHNOLOGY LETTERS (2018)

Article Computer Science, Artificial Intelligence

Reconfigurable FPGA implementation of neural networks

Zbigniew Hajduk

NEUROCOMPUTING (2018)

Article Engineering, Electrical & Electronic

On the Impact of Fixed Point Hardware for Optical Fiber Nonlinearity Compensation Algorithms

Tom Sherborne et al.

JOURNAL OF LIGHTWAVE TECHNOLOGY (2018)

Article Engineering, Electrical & Electronic

Digital Signal Processing for Coherent Transceivers Employing Multilevel Formats

Md. Saifuddin Faruk et al.

JOURNAL OF LIGHTWAVE TECHNOLOGY (2017)

Article Optics

Ripple distribution for nonlinear fiber-optic channels

Mariia Sorokina et al.

OPTICS EXPRESS (2017)

Article Engineering, Electrical & Electronic

Artificial Neural Network Nonlinear Equalizer for Coherent Optical OFDM

Mutsam A. Jarajreh et al.

IEEE PHOTONICS TECHNOLOGY LETTERS (2015)

Article Engineering, Electrical & Electronic

Reduced Complexity Digital Back-Propagation Methods for Optical Communication Systems

Antonio Napoli et al.

JOURNAL OF LIGHTWAVE TECHNOLOGY (2014)

Article Engineering, Electrical & Electronic

Intrachannel Nonlinearity Compensation by Inverse Volterra Series Transfer Function

Ling Liu et al.

JOURNAL OF LIGHTWAVE TECHNOLOGY (2012)

Article Automation & Control Systems

FPGAs in Industrial Control Applications

Eric Monmasson et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2011)

Article Automation & Control Systems

FPGA Implementation of the Multilayer Neural Network for the Speed Estimation of the Two-Mass Drive System

Teresa Orlowska-Kowalska et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2011)

Article Engineering, Electrical & Electronic

Data-Aided Versus Blind Single-Carrier Coherent Receivers

Maxim Kuschnerov et al.

IEEE PHOTONICS JOURNAL (2010)

Article Engineering, Electrical & Electronic

Compensation of Dispersion and Nonlinear Impairments Using Digital Backpropagation

Ezra Ip et al.

JOURNAL OF LIGHTWAVE TECHNOLOGY (2008)

Article Automation & Control Systems

FPGA realization of a neural-network-based nonlinear channel equalizer

CT Yen et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2004)

Article Engineering, Electrical & Electronic

Approximation of sigmoid function and the derivative for hardware implementation of artificial neurons

K Basterretxea et al.

IEE PROCEEDINGS-CIRCUITS DEVICES AND SYSTEMS (2004)

Article Computer Science, Hardware & Architecture

Efficient digital implementation of the sigmoid function for reprogrammable logic

MT Tommiska

IEE PROCEEDINGS-COMPUTERS AND DIGITAL TECHNIQUES (2003)