RSSI Probability Density Functions Comparison Using Jensen-Shannon Divergence and Pearson Distribution

The performance of a free-space optical (FSO) communications link suffers from the deleterious effects of weather conditions and atmospheric turbulence. In order to better estimate the reliability and availability of an FSO link, a suitable distribution needs to be employed. The accuracy of this mod...

Full description

Saved in:
Bibliographic Details
Published in:Technologies (Basel) 2021-06, Vol.9 (2), p.26
Main Authors: Lionis, Antonios, Peppas, Konstantinos P., Nistazakis, Hector E., Tsigopoulos, Andreas
Format: Article
Language:English
Subjects:
Approximation
Atmospheric models
Atmospheric turbulence
Dimensional analysis
Free-space optical communication
Information theory
Jensen-Shannon divergence
Kullback–Leibler divergence
Kurtosis
Model accuracy
optical wireless communications
Pearson distribution
Pearson distributions
Performance evaluation
Probability density functions
Refractivity
Reliability aspects
RSSI
Signal strength
Turbulence models
Weather
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The performance of a free-space optical (FSO) communications link suffers from the deleterious effects of weather conditions and atmospheric turbulence. In order to better estimate the reliability and availability of an FSO link, a suitable distribution needs to be employed. The accuracy of this model depends strongly on the atmospheric turbulence strength which causes the scintillation effect. To this end, a variety of probability density functions were utilized to model the optical channel according to the strength of the refractive index structure parameter. Although many theoretical models have shown satisfactory performance, in reality they can significantly differ. This work employs an information theoretic method, namely the so-called Jensen–Shannon divergence, a symmetrization of the Kullback–Leibler divergence, to measure the similarity between different probability distributions. In doing so, a large experimental dataset of received signal strength measurements from a real FSO link is utilized. Additionally, the Pearson family of continuous probability distributions is also employed to determine the best fit according to the mean, standard deviation, skewness and kurtosis of the modeled data.
ISSN:2227-7080
2227-7080
DOI:10.3390/technologies9020026