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http://dx.doi.org/10.6109/jicce.2018.16.1.1

Nonlinear Compensation Using Artificial Neural Network in Radio-over-Fiber System  

Najarro, Andres Caceres (Gwangju Institute of Science and Technology)
Kim, Sung-Man (Department of Electronic Engineering, Kyungsung University)
Publication Information
Journal of information and communication convergence engineering / v.16, no.1, 2018 , pp. 1-5 More about this Journal
Abstract
In radio-over-fiber (RoF) systems, nonlinear compensation is very important to meet the error vector magnitude (EVM) requirement of the mobile network standards. In this study, a nonlinear compensation technique based on an artificial neural network (ANN) is proposed for RoF systems. This technique is based on a backpropagation neural network (BPNN) with one hidden layer and three neuron units in this study. The BPNN obtains the inverse response of the system to compensate for nonlinearities. The EVM of the signal is measured by changing the number of neurons and the hidden layers in a RoF system modeled by a measured data. Based on our simulation results, it is concluded that one hidden layer and three neuron units are adequate for the RoF system. Our results showed that the EVMs were improved from 4.027% to 2.605% by using the proposed ANN compensator.
Keywords
Artificial neural network; Nonlinear compensation; Radio over fiber;
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Times Cited By KSCI : 2  (Citation Analysis)
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