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

Abstract

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.

Experimental Machine Learning Approach for Optical Turbulence and FSO Outage Performance Modeling

“…modeled the received signal strength indicator (RSSI) parameter of a FSO link over a maritime environment based on meteorological parameters. The comparison with different theoretical models presented good agreement [3][4][5]. Jellen et.…”

“…The Hellenic Naval Academy (HNA), Piraeus, Greece, has demonstrated a substantial research effort on the field of atmospheric characterization and modeling with a focus on laser communication systems applications [3][4][5]21,26,31,32]. An established horizontal laser communication link between the roof of the HNA and the lighthouse of Psitalia island, 2958 m apart and 35 m above sea level, is utilized to measure the received signal strength on the receiver.…”

PDF Comparison based on Various FSO Channel Models under Different Atmospheric Turbulence

“…[27]. The LN model is the most popular AT model because of its comparatively straightforward shape [9].…”

“…The congruence between the mathematical analysis and the actual experimental data observed among [9] of these PDFs is a necessary factor in choosing the most appropriate distribution for channel modeling, as well as the computational complexity factor, which is the main point of this paper. The best PDF is determined to be the one with the least amount of spacing to Kullback-Leibler divergence (KLD) metrics [9], which enables a performance metric to be computed for each candidate PDF. KLD is most helpful for application in a real-world dataset from a practical standpoint because it directly provides specific outputs that make it possible to scan any PDF file.…”

“…The term for this is PE [8]. A PDF distribution is also impacted by the aperture averaging effect, which tends to lessen the harmful impacts of scintillation and turbulence [9].…”