# Study of the Ionospheric Scintillation Radio Propagation Characteristics with Cosmic Observations
## 5 Conclusions  
In this work, the global ionospheric scintillation feature for radio propagation is investigated with the COSMIC occultation data from 2010 to 2019. The statistical characteristics of the amplitude scintillation index S4 and SNR are analyzed, and the radio propagation channel feature is extracted. It was found that the probability for weak scintillation accounts for the largest proportion, with approximately 69%, while the moderate and strong scintillation accounts for approximately 20%, and 11% respectively. The SNR distribution curves under different normalized S4 are analyzed in each year. When the normalized S4 is small, there is a bimodal phenomenon in the measured distribution curve, which is probably caused by different factors affecting ionospheric scintillation, such as atmospheric multipath refraction. The Nakagami-\(m\), \(\alpha\)-\(\mu\) and \(\kappa\)-\(\mu\) distributions are used to fit the amplitude scintillation feature. From the results, it is considered that the overall fitting performance of the \(\alpha\)-\(\mu\) distribution curve is the best. When the normalized \(S4\geq 0.8\), the Nakagami-\(m\) distribution function achieves better performance. The \(\kappa\)-\(\mu\) distribution is suitable for weak scintillation cases. The \(\alpha\) and \(\mu\) values under different normalized S4 are calculated and analyzed by confidence intervals. To evaluate the fitting performance of the three distribution curves, the standard deviation, kurtosis, information entropy and confidence interval are used. Through the analysis of standard deviation, the following are found: (a) With the increase of the normalized S4, the standard deviation of difference between the Nakagami-\(m\) distribution and the measured curve decreases, indicating that the fitting performance of the Nakagami-\(m\) distribution becomes better with increasing normalized S4. (b) The distribution curve fitted by the \(\alpha\)-\(\mu\) distribution has a generally smaller standard deviation difference than the other two distributions. (c) The standard deviation of the difference for the \(\kappa\)-\(\mu\) distribution shares the similar variation trend as that of the Nakagami-\(m\) distribution, while the fitting performance is not as good as that of the Nakagami-\(m\) distribution. In the Nakagami-distribution, the kurtosis difference decreases with increasing normalized S4, indicating that the fitting performance of the Nakagami-\(m\) distribution in this range improves. In the \(\alpha\)-\(\mu\) distribution, the kurtosis difference is generally small regardless of the change in normalized S4. The \(\kappa\)-\(\mu\) distribution is outstanding among the three distributions to fit the low scintillation intensity case. A similar trend was noticed for the information entropy evaluation. The fitting performance of the three distribution models is analyzed in different solar activity years. The fitting interval analysis was discussed to evaluate the fitting performance. The fitting interval length of the Nakagami-\(m\) distribution increases with increasing normalized S4; \(\alpha\)-\(\mu\) distribution meets the 100% confidence level in the whole range; \(\kappa\)-\(\mu\) distribution has a similar trend as that of the Nakagami-\(m\) distribution, while it does not reach 100% in the whole range. The skewness-kurtosis profile extracted in this work shows similar features as revealed by a previous study, indicating that the amplitude scintillation propagation channel is probably related to the nonlinearity of ionospheric irregularity and potential influential factors of the ionosphere. [PERSON] and [PERSON] initiated the study and proposed the method. [PERSON] analyzed the data and drew the results. [PERSON] and [PERSON] wrote the manuscript. [PERSON] and [PERSON] checked and modified the manuscript. All authors provided critical feedback and approved the manuscript. All authors have read and agreed to the published version of the manuscript.