Low-complexity EVM estimation based on artificial neural networks for coherent optical systems

被引:2
作者
Jha, Dhirendra Kumar [1 ]
Mishra, Jitendra K. [1 ]
机构
[1] Indian Inst Informat Technol Ranchi, Dept Elect & Commun Engn, Ranchi 834010, Jharkhand, India
关键词
optical communications; machine learning (ML); deep learning (DL); artificial neural network (ANN); ERROR VECTOR MAGNITUDE; CHANNELS; MODEL;
D O I
10.1088/2040-8986/ad529f
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
With continuous growth in modulation formats, the requirement for autonomous devices is becoming more important than ever. Predicting error vector magnitude (EVM) of m-ary quadrature amplitude modulation (mQAM) are intricate issue for the effective design of transmission systems. Existing estimation techniques have survived through repetitive processes that are frequently computationally expensive, and time-consuming. Recently deep learning approaches demonstrated good performance as useful computational tools, offering a different way for accelerating such mQAM simulations. This paper introduces an artificial neural network (ANN) architecture that aims to forecast the EVM of the popular modulation forms including 18 Gbaud 8QAM, 14 Gbaud 16QAM, and 10 Gbaud 64QAM under different transmission conditions. Amplitude histograms (AHs) are produced from constellation diagrams obtained with varying launch power, laser linewidth, OSNR, and transmission distance by an offline preprocessing flow. The fully trained framework exhibits superior performance in terms of computing cost compared to the simulation experiments. The overall execution time of the ANN-based modeling method is approximately 234 s as opposed to more than 23000 s when employing the simulation technique, resulting in a 99% reduction in computation time. As a result, this technology opens the door to quick, all-encompassing techniques for characterizing and analyzing optical fiber problems.
引用
收藏
页数:11
相关论文
共 30 条
[1]   Integrated Free-Space Optics and Fiber Optic Network Performance Enhancement for Sustaining 5G High Capacity Communications [J].
Alsharari, Meshari ;
Aliqab, Khaled ;
Ali, Farman ;
Armghan, Ammar .
INTERNATIONAL JOURNAL OF OPTICS, 2023, 2023
[2]   An inspired chaos-based estimation-theory optimization for low-density parity-check (LDPC) code decoding [J].
Dahan, Fadl ;
Roberts, Michaelraj Kingston ;
Nagabushanam, Munivenkatappa ;
Alfakih, Taha M. .
RESULTS IN ENGINEERING, 2024, 22
[3]   Efficient Classification of Optical Modulation Formats Based on Singular Value Decomposition and Radon Transformation [J].
Eltaieb, Rania A. ;
Farghal, Ahmed E. A. ;
Ahmed, HossamEl-din H. ;
Saif, Waddah S. ;
Ragheb, Amr ;
Alshebeili, Saleh A. ;
Shalaby, Hossam M. H. ;
Abd El-Samie, Fathi E. .
JOURNAL OF LIGHTWAVE TECHNOLOGY, 2020, 38 (03) :619-631
[4]  
Fan Y., 2021, CLEO SCI INNOVATIONS
[5]  
Fan Y., 2021, EUR C OPT COMM ECOC, P1
[6]   Linear Regression vs. Deep Learning for Signal Quality Monitoring in Coherent Optical Systems [J].
Fan, Yuchuan ;
Pang, Xiaodan ;
Udalcovs, Aleksejs ;
Natalino, Carlos ;
Zhang, Lu ;
Spolitis, Sandis ;
Bobrovs, Vjaceslavs ;
Schatz, Richard ;
Yu, Xianbin ;
Furdek, Marija ;
Popov, Sergei ;
Ozolins, Oskars .
IEEE PHOTONICS JOURNAL, 2022, 14 (04)
[7]   Experimental validation of CNNs versus FFNNs for time- and energy-efficient EVM estimation in coherent optical systems [J].
Fan, Yuchuan ;
Udalcovs, Aleksejs ;
Natalino, Carlos ;
Pang, Xiaodan ;
Schatz, Richard ;
Furdek, Marija ;
Popov, Sergei ;
Ozolins, Oskars .
JOURNAL OF OPTICAL COMMUNICATIONS AND NETWORKING, 2021, 13 (10) :E63-E71
[8]   Fast signal quality monitoring for coherent communications enabled by CNN-based EVM estimation [J].
Fan, Yuchuan ;
Udalcovs, Aleksejs ;
Pang, Xiaodan ;
Natalino, Carlos ;
Furdek, Marija ;
Popov, Sergei ;
Ozolins, Oskars .
JOURNAL OF OPTICAL COMMUNICATIONS AND NETWORKING, 2021, 13 (04) :B12-B20
[9]   A Noise Power Ratio Measurement Method for Accurate Estimation of the Error Vector Magnitude [J].
Freiberger, Karl ;
Enzinger, Harald ;
Vogel, Christian .
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, 2017, 65 (05) :1632-1645
[10]   An Error Vector Magnitude Performance Modeling and Analysis Methodology for 5G mm-Wave Transmitters [J].
Ghoniem, Ahmed A. ;
Mehana, Ahmed Hesham ;
Mobarak, Mohamed ;
Abdalla, Mohamed A. Y. .
IEEE MICROWAVE AND WIRELESS TECHNOLOGY LETTERS, 2023, 33 (06) :771-774