Comparative Analysis of Optical Multicarrier Modulations: An Insight into Machine Learning-based Multicarrier Modulation

Year 2021, , 1016 - 1033, 01.12.2021

Augustus Ibhaze , Frederick Edeko , Patience Orukpe

https://doi.org/10.35378/gujs.774296

Cited By: 2

Abstract

The performances of various optical multicarrier modulation schemes have been investigated in this work by comparatively analyzing the bit error rate response relative to the signal to noise ratio metric. The machine learning-based multicarrier modulation (MLMM) approach was proposed and adopted as a method to improve the bit error rate response of the conventional schemes. The results showed performance enhancement as the proposed machine learning approach outperformed the conventional schemes. This proposition is therefore recommended for adoption in the implementation of optical multicarrier modulation-based solutions depending on the spectral and energy efficiency requirements of the intended application.

Keywords

Bit error rate, Machine learning, Multicarrier modulation, Signal to noise ratio

Supporting Institution

Petroleum Technology Development Fund (PTDF)

Project Number

P4567720076521527

Thanks

The authors gratefully acknowledge the sponsorship of this research by the Petroleum Technology Development Fund (PTDF) under the grant award number P4567720076521527.

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