Various Types of Functional Link Artificial Neural Network Based Nonlinear Equalizers used in CO-OFDM System for Nonlinearities Mitigation
|International Journal of Electronics and Communication Engineering|
|© 2018 by SSRG - IJECE Journal|
|Volume 5 Issue 2|
|Year of Publication : 2018|
|Authors : Gurpreet Kaur and Gurmeet Kaur|
How to Cite?
Gurpreet Kaur and Gurmeet Kaur, "Various Types of Functional Link Artificial Neural Network Based Nonlinear Equalizers used in CO-OFDM System for Nonlinearities Mitigation," SSRG International Journal of Electronics and Communication Engineering, vol. 5, no. 2, pp. 1-6, 2018. Crossref, https://doi.org/10.14445/23488549/IJECE-V5I2P101
Artificial neural network based nonlinear equalizers (ANN-NLEs) have received much attention in the last three years due to its ability of complex mapping between the complex input and output spaces.In the history of ANN-NLE, the focus has always been improving the performance of coherent optical orthogonal frequency division multiplexing (CO-OFDM) system. Recent developments in ANN-NLE have led to a decision that a single neuron based ANN i.e., functional link artificial neural network (FLANN) has been considered as an efficient technique of performance improvement with less computational complexity.There are many types of FLANN available in literature depending on the expansion technique used in network such as PPN (Polynomial Perceptron Network), T-FLANN (Trigonometric Functional link Artificial Neural Network), Le-FLANN (Legendre Functional link Artificial Neural Network) and Ch-FLANN (Chebyshev Functional link Artificial Neural Network).Until now this methodology has only been applied to Ch-FLANN based NLE. It has not yet been established whether other types of FLANN can do the task of nonlinearity mitigation in CO-OFDM system. In this context authors tried to use other types of FLANN-NLE for the mitigation of nonlinearities in CO-OFDM system.
Chebyshev Functional Link ANN (Ch-FLANN); Coherent Optical Orthogonal Frequency Division Multiplexing (CO-OFDM); Legendre Functional Link ANN (Le-FLANN); Multilayer Perceptron (MLP); Polynomial Perceptron Network (PPN); Trigonometric Functional Link ANN (T-FLANN).
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