Artificial Neural Network-Based Prediction of the Atmospheric Attenuation and Scattering Coefficient at 1550 nm for Optical Wireless System in Foggy Atmosphere
摘要
This paper proposes an ANN model for predicting the atmospheric attenuation and the scattering coefficient in the optical wireless communication system at 1550 nm. This paper extends from my prior work, which established that better transmission is attainable at 1550 nm relative to other wavelengths under the foggy atmosphere. The two critical parameters, scattering coefficient and atmospheric attenuation in relation to visibility are investigated. Further analysis reveals that as the visibility increases, both the scattering coefficient and attenuation exhibit a non-linear decreasing trend as visibility increases from 0 to 5 kms. This model has trained with visibility data, and the performance measures demonstrated good accuracy where the Mean Square Error (MSE) of the ANN model is of the order of 1.2915e-06, which implies very accurate prediction and the value of regression coefficient (R) stands for 1 indicating the high predictive accuracy of the chosen ANN. Thus, the application of the ANN model for estimating atmospheric attenuation and scattering coefficient improves FSO system utilization by varying the power levels, modulation techniques or beam steering, therefore improving signal transmission in spite of changes in conditions within the atmosphere.