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MGF Methods for Fixed and Gain Saturated Optically Preamplified FSO Links Impaired by Misalignments and Atmospheric Turbulence

Abstract

The Gaussian approximation is commonly used to evaluate the performance of free space optical communication systems. However, other performance evaluation methods such as the saddle point approximation, Chernoff bound and the modified Chernoff bound have also been used. This paper investigates the performance of fixed and gain saturated optically preamplified communication systems limited by factors such as strong atmospheric turbulence and pointing errors using various evaluation methods. Average bit error rate results are obtained over a range of average transmitted powers for free space optical communication systems without pointing error and those with pointing error using different saturation regimes, normalised beam widths and pointing error standard deviations. Results obtained in this paper show over a propagation distance of 1500 m, a receiver diameter of 0.15 m performed better than a receiver diameter of 0.03 m when the pointing error standard deviation is 0.1. Also, a receiver diameter of 0.03 m performed better than a receiver diameter of 0.15 m when the pointing error standard deviation is 4. These results show that while larger receiving lenses performed better when pointing error effects are minimal or absent, smaller receiving lenses are better when pointing error effects are dominant. Additionally, it is shown in this paper that while fixed and gain saturated optical preamplifiers produced similar performances when the decision threshold at the receiver is adaptive, the saddle point approximation is not useful for gain saturated optically preamplified receivers. Also, results in this paper showed optimal and near-optimal adaptive decision thresholds for the modified Chernoff bound and Gaussian approximation, respectively.

Index Terms
Atmospheric turbulence; free-space optical communication; modified Chernoff bound; optical amplifier; pointing error; saddle point approximation

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