Efficient Error-Rate Estimation for Optical Transmission Systems Using Artificial Neural Networks

ABSTRACT

With the advancement in modulation formats, optical transmission systems are becoming more adaptable and dynamic. Predicting bit errors of higher-order modulation formats is a challenging problem for the optimum design of communication systems. The existing simulation methods have persisted by employing iterative procedures that frequently incur high computing expenses and time consumption. On the other hand, deep learning (DL) algorithms have demonstrated remarkable efficacy as practical computing tools, presenting a viable approach to accelerate modulation simulations. In this paper, an artificial neural network (ANN) based bit error rate (BER) estimation scheme is proposed for the popular modulation forms including 56 Gbps 16-quadrature amplitude modulation (16QAM), 100 Gbps 32QAM, and 120 Gbps 64QAM optical system. Based on constellation diagrams (CDs) acquired with different launch power, laser linewidth, transmission distance, and OSNR, amplitude histograms (AHs) are generated via a manual preprocessing method. The properly trained ANN architecture exhibits a computational speed that surpasses traditional simulation methods by a factor exceeding 347. Moreover, the design considerations including the number of layers, nodes, activation functions, learning rate, optimizers, and evolution epochs are also investigated in detail. This research paves the way for optical transmission systems to use fast DL-based optimization strategies.

KEYWORDS:

• Optical communications
• artificial intelligence (AI)
• machine learning (ML)
• deep learning (DL)
• artificial neural network (ANN)

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Additional information

Notes on contributors

Dhirendra Kumar Jha

Dhirendra Kumar Jha received the M.Tech degree in electronics and communication engineering from National Institute of Technology Agartala, India in 2016. Currently, he is working toward the Ph.D degree in electronics and communication engineering from Indian Institute of Information Technology Ranchi, India. His research interests include machine learning, optical fiber transmission design using machine learning.

Jitendra K. Mishra

Jitendra K. Mishra received the Ph.D degree in electronics and communication engineering from Indian Institute of Technology (ISM) Dhanbad, India in 2016. He was with City, University of London, UK as an exchange research fellow under Erasmus Mundus scholarship of European Commission. Currently, he is with the department of electronics and communication engineering, Indian Institute of Information Technology Ranchi, Jharkhand, India. He has authored more than 25 peer reviewed publications, including two book chapters. His research interests include optical communication, optical quantum communication and application of machine learning in information and communication technology.