Temporal Correlation and Long-Term Average Performance Analysis of Multiple UAV-Aided Networks

In multiple unmanned aerial vehicles (UAVs)-aided networks, the time-varying channel caused by the impact of the line of sight (LOS) and nonline of sight (NLOS) leads to signal fluctuations; moreover, the UAV’s agility and the constraint of the spatial distribution of blind areas on the UAV’s deployment result in interference topology fluctuations. Accordingly, the instantaneous signal-to-interference ratio is fluctuant and cannot accurately reflect network performance. Considering a multi-UAV-aided network with UAV spatial dependence, this article derives the semiclosed expression of long-term average throughput considering the fluctuations of the channel and topology, which are measured by calculating correlation coefficients of the signal and interference. Specifically, the time-varying channel is characterized by incorporating the link-state conversions and randomness of small-scale fading into channel gains, the time-varying network topology is quantified by considering the effect of distance variation caused by mobility on interference topology. In addition, considering multiple UAVs are clustered in corresponding blind areas, UAV networks are modeled as matern cluster processes (MCP), and time-averaged performances at intracluster and extracluster are analyzed, respectively. The numerical results show the effects of clustering parameters and deployment parameters on temporal correlation and long-term average network performance.