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Impairment analysis of WDM Ro-FSO system under different weather conditions employing machine learning

SANMUKH KAUR1,* , AANCHAL SHARMA1

Affiliation

  1. Amity School of Engineering & Technology, Amity University Uttar Pradesh, Noida, 201313, India

Abstract

In this work, a WDM Ro-FSO communication system has been designed for transmitting data at 80 Gbps with 8 different channels carrying phase shift keying (PSK) modulated signals over a wavelength range of 1546.91 nm to 1552.52 nm at a data rate of 10 Gbps. Quality of signal received at the output of each channel has been analysed for clear air, low haze, heavy haze, and light fog conditions. Artificial neural network (ANN) and support vector machine (SVM) techniques have been implemented to investigate and predict the signal impairments at the receiving end. Root mean square error (RMSE) and R2 values of 0.148 and 0.98 respectively have been observed in case of ANN model. With RMSE and R2 values of 0.937 and 0.76, Linear SVM exhibits the best performance in estimation of Q factor of the received signal..

Keywords

Ro-FSO, Free space optical communication, Phase shift keying, Fog weather conditions, Machine learning, ANN, SVM.

Submitted at: Feb. 19, 2023
Accepted at: Oct. 6, 2023

Citation

SANMUKH KAUR, AANCHAL SHARMA, Impairment analysis of WDM Ro-FSO system under different weather conditions employing machine learning, Journal of Optoelectronics and Advanced Materials Vol. 25, Iss. 9-10, pp. 444-452 (2023)