## 1 Introduction  
The technology of free-space optical (FSO) communications, after decades of research efforts, seems to be ready to bring a revolution to the area of telecommunications. Yet, a few final burdens need to be overcome. This new technology promises to meet the requirements for increased data rates transmission for many current applications and also support the fiber-optic backbone networks by solving the last-mile problem [1]. The major obstacle in deploying an FSO link is the various effects of the laser beam traveling along the atmosphere. Atmospheric extinction, due to aerosols and molecules that cause the light beam to be absorbed or scattered, often leads to intensity degradation even to such a degree that can permanently interrupt the link. Atmospheric turbulence is another phenomenon that seriously degrades the quality of an FSO link by causing intensity fluctuations to the receiver, beam wandering, angle-of-arrival fluctuations and beam spreading [1]. Therefore, the state of the weather conditions severely affects the reliability and availability of the link. In order to better estimate those performance metrics, an accurate model should be selected, according to the weather conditions and especially the atmospheric turbulence. Traditionally, a large number of probability density functions (PDFs) have been utilized to model the received optical power of an FSO link. The most widely used and accepted PDF models include the Log-Normal (LN), Gamma-Gamma (GG), Gamma, Weibull, K, I-K, Malaga, the Fisher-Snedecor F and the negative exponential [1, 2, 3]. In order to evaluate the performance of an optical communication system, various link parameters can be employed, such as the probability of detection, the outage probability, the average capacity and the outage capacity [1,4]. In any case, knowledge of the PDF of the received optical power is required; however, it is rather difficult to determine which PDF better fits the statistics of the received power data [1]. In the open technical literature, several PDF models are available for weak, moderate and strong turbulence. For example, the Log-Normal and the Gamma-Gamma distributions accurately describe the weak and moderate regime whereas the Gamma-Gamma, the negative exponential and the K-distribution yield a better fit for the strong regime [4]. Apart from selecting a distribution corresponding to the correct turbulence strength regime, it is risky to assume that only a certain one accurately fits the experimental data. Instead, it is critical to investigate the best fit among different distributions. In the past, extensive research work to estimate the performance of FSO links under various atmospheric conditions and communication schemes has been conducted. For example, [PERSON] et al. analyzed the performance of an FSO link affected by atmospheric turbulence and line-of-sight (LOS) blockages. They modeled the intensity fading due to turbulence using the Malaga distribution and derived a closed-form expression for the outage probability (OP). Their results showed a strong dependency of the LOS impact to the OP on the turbulence strength [5]. In [6], the scintillation effect has been modeled by the Gamma-Gamma and the I-K distribution to study the time dispersion and atmospheric turbulence in the performance of an FSO link and closed-form mathematical expressions for the evaluation of the link's fade probability derived. [PERSON] et al. elaborated on the end-to-end capacity of dual hop FSO systems employing amplify-and-forward (AF) relaying. The link's performance is affected by atmospheric turbulence, modeled by the Gamma-Gamma distribution, pointing errors and atmospheric absorption and derived analytical approximations for the channel's ergodic capacity [7].