ABSTRACT
Free-space optical communication can experience severe fading due to optical scintillation in long-range links. Channel estimation is also corrupted by background and electrical noise. Accurate estimation of channel parameters and scintillation index (SI) depends on perfect removal of background irradiance. In this paper, we propose three different methods, the minimum-value (MV), mean-power (MP), and maximum-likelihood (ML) based methods, to remove the background irradiance from channel samples. The MV and MP methods do not require knowledge of the scintillation distribution. While the ML-based method assumes gamma-gamma scintillation, it can be easily modified to accommodate other distributions. Each estimator's performance is compared using simulation data as well as experimental measurements. The estimators' performance are evaluated from low- to high-SI areas using simulation data as well as experimental trials. The MV and MP methods have much lower complexity than the ML-based method. However, the ML-based method shows better SI and background-irradiance estimation performance.
ABSTRACT
A large number of model probability density functions (PDFs) are used to analyze atmospheric scintillation statistics. We have analyzed scintillation data from two different experimental setups covering a range of scintillation strengths to determine which candidate model PDFs best describe the experimental data. The PDFs were fitted to the experimental data using the method of least squares. The root-mean-squared fitting error was used to monitor the goodness of fit. The results of the fitting were found to depend strongly on the scintillation strength. We find that the log normally modulated Rician and the log normal PDFs are the best fit to the experimental data over the range of scintillation strengths encountered.
