Using Machine Learning Algorithms for Accurate Received Optical Power Prediction of an FSO Link over a Maritime Environment

Using Machine Learning Algorithms for Accurate Received Optical Power Prediction of an FSO Link over a Maritime Environment

The performance prediction of an optical communications link over maritime environments has been extensively researched over the last two decades. The various atmospheric phenomena and turbulence effects have been thoroughly explored, and long-term measurements have allowed for the construction of s...

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Bibliographic Details
Main Authors: Antonios Lionis, Konstantinos Peppas, Hector E. Nistazakis, Andreas Tsigopoulos, Keith Cohn, Athanassios Zagouras
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Photonics
Subjects:
free space optical communication
received signal strength indicator
atmospheric turbulence
refractive index structure parameter
machine learning
Online Access:https://www.mdpi.com/2304-6732/8/6/212

Internet

https://www.mdpi.com/2304-6732/8/6/212

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