Investigation of FSO Communication System Using Various Neural Networks

Volume: 11 | Issue: 02 | Year 2025 | Subscription
International Journal of Broadband Cellular Communication
Received Date: 05/27/2025
Acceptance Date: 06/19/2025
Published On: 2025-12-30
First Page: 12
Last Page: 20

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By: Ritu Gupta and Sandeep Kaur.

1,2 Associate Professor, Department of ECE, Chandigarh University, Gharuan, Punjab, India

Abstract

A prospective method for high-speed data transfer via light propagation in free space, such as between buildings, satellites, or metropolitan areas, is Free Space Optics (FSO) communication. FSO systems have great promises, but their performance can be severely hampered by atmospheric disturbances. Problems like fog, rain, and turbulence cause the optical signal to be absorbed and scattered, increasing BER. To address these challenges, various Neural Network (NN) techniques such as Recurrent Neural Networks (RNN) and Convolutional Neural Networks (CNN), have been investigated. According to the study, CNNs perform better than ANNs and RNNs among the NN approaches investigated in controlling for the spatial changes brought on by atmospheric circumstances. CNN’s ability to analyze spatial data is probably the reason for this advantage, which makes it perfect for addressing localized FSO communication problems. CNNs hence result in a more dependable link by improving BER and SNR, particularly in adverse weather conditions.

Keywords : Free Space Optics (FSO), Artificial Neural Networks (ANN), Recurrent Neural Networks
(RNN), Convolutional Neural Networks (CNN), Signal-to-Noise Ratio (SNR), Bit Error Rate (BER)

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Citation:

How to cite this article: Ritu Gupta and Sandeep Kaur Investigation of FSO Communication System Using Various Neural Networks. International Journal of Broadband Cellular Communication. 2025; 11(02): 12-20p.

How to cite this URL: Ritu Gupta and Sandeep Kaur, Investigation of FSO Communication System Using Various Neural Networks. International Journal of Broadband Cellular Communication. 2025; 11(02): 12-20p. Available from:https://journalspub.com/publication/ijbcc/article=22538

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