Aerial IRS-Aided Vertical Backhaul FSO Networks over Fisher-Snedecor F Turbulence Channels

Abstract

Free-space optics (FSO)-based, high-altitude plat form (HAP)-assisted backhaul network has recently attracted research efforts worldwide. Nevertheless, one of the critical concerns on HAP-assisted FSO links is cloud coverage, which may block the FSO connections completely. This paper explores a novel solution that uses multiple unmanned aerial vehicles (UAVs) equipped with an intelligent reflecting surface (IRS) array. These UAVs are deployed to diverse the FSO link from HAP-to-ground base station (BS) to avoid cloud coverage. We assume the Fisher-Snedecor $\mathcal{F}$ model for the atmospheric turbulence and use a selection combing (SC) receiver to obtain signals from multiple UAVs. We analytically derive the probability density function (PDF) of the received end-to-end signal-to-noise ratio (SNR) by employing the moment matching method, which can obtain an accurate approximation of PDF to the product of $\mathcal{F}$ variables. Using the derived statistics, we investigate different system performance metrics, including outage probability, outage capacity, and average bit error rate (BER). Finally, Monte Carlo simulations are provided to validate analytical results.