Ground-Aerial UAV-Assisted Hybrid PLC-FSO Integrated Communication Networks: A Performance Analysis

The use of aerial platforms has recently attracted significant interest in Internet of Things (IoT) based heterogeneous communication networks to support flexible and efficient network connection. This work investigates the performance of a ground-aerial unmanned aerial vehicle (UAV)-assisted hybrid power line communication (PLC)/free-space optical (FSO) communication system employing both decode-and-forward (DF) and fixed-gain amplify-and-forward (AF) relaying protocols. It is assumed that the PLC channel gain is Log-normally distributed while the Bernoulli-Gaussian random process models the PLC channel noise. The FSO link established between the FSO transmitter and the UAV, considers the combined influence of the generalized Málaga distributed atmospheric turbulence (AT), random fog, non-zero boresight pointing errors, and angle-of-arrival (AoA) fluctuations of the UAV. Based on this, we evaluate the cumulative distribution function (CDF) and probability density function (PDF) of the end-to-end signal-to-noise ratio (SNR). Further, capitalizing on the statistical characterization of CDF and PDF, we derive series-based expressions for average symbol error rate (ASER), outage probability (OP), and average channel capacity (ACC) utilizing both heterodyne (HD) and direct detection (DD) techniques. Additionally, we conduct an asymptotic analysis of ASER in terms of the coding gain and diversity order in a high SNR regime. Likewise, a detailed analysis is carried out to find the optimal value of the field-of-view (FOV) angle and average SNR to achieve minimum ASER under the combined influence of the aforementioned channel conditions using the DF relaying scheme. Furthermore, the impact of all the considered channel parameters and impairments is demonstrated through the numerical results.