Tractable Optical Channel Modeling Between UAVs

doi:10.1109/TVT.2019.2940226

2019-12-01

PRE

Mohammad Taghi Dabiri

Seyed Mohammad Sajad Sadough *

Imran Shafique Ansari

DOI：10.1109/TVT.2019.2940226

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摘要

En 中文

More recently, the research on potential use of free-space optical (FSO) link as a powerful communication link between unmanned aerial vehicles (UAVs) has created much interest in academia and industry. Due to the need of higher number of UAV-based FSO links relative to the conventional ground-based FSO links, the optimum design of UAV-based FSO system parameters (such as optimum values for beam divergence angle, photodetector size, receiver lens radius, and transmit power, among many others) is muchmore needful and challenging relative to the ground-based counterpart. Moreover, to avoid the time consumed in Monte-Carlo simulations, existence of a simple and tractable channel model is very important and necessary. To address this need, in this paper, for the weak turbulence conditions, we construct a novel channel model for the considered system model under the effect of log-normal atmospheric turbulence channel. Then, for moderate to strong turbulence conditions, a novel closed-form statistical channel model is derived for Gamma-Gamma turbulence channel. The provided channel models, despite being simple and tractable, include the combined effects of atmospheric turbulence as well as the pointing errors. These also include the effects of receiver field-of-view limitation and inherent position, and orientation deviations of UAVs. Subsequently, for better performance analysis, the closed-form expressions for the outage probability and bit error rate (BER) are derived. Finally, the validity of the proposed novel channelmodels as well as the closed-form expressions for the outage probability and BER are confirmed by employing Monte-Carlo simulations. The developed results can therefore be applied as a benchmark for finding the optimal tunable parameters of UAV-based FSO links under different channel conditions and different levels of UAV instability without resorting to time-consuming Monte-Carlo simulations.

Keyword:

Angle-of-arrival fluctuations

atmospheric turbulence

free-space optics

unmanned aerial vehicles