A Novel UAV-Assisted Multi-Mobility Channel Model for Urban Transportation Emergency Communications

With the increasing requirements for unmanned aerial vehicle (UAV) communication in various application scenarios, the UAV-assisted emergency communication in urban transportation scenario has received great attention. In this paper, a novel UAV-assisted UAV-to-vehicle (U2V) geometry-based stochastic model (GBSM) for the urban traffic communication scenario is proposed. The three-dimensional (3D) multi-mobilities of the transmitter (Tx), receiver (Rx), and clusters are considered by introducing the time-variant acceleration and velocity correspondingly. The velocity variation of the clusters is used to simulate the motion of vehicles around the Rx. Moreover, to describe the vehicles’ moving states, Markov chain is adopted to analyze the changes in cluster motion states, including survival, death, dynamic, and static states. By adjusting the scenario-specific parameters, such as the vehicle density ($\rho$) and dynamic–static ratio ($\Omega$), the model can support various urban traffic scenarios. Based on the proposed model, several key statistical properties, namely the root mean square (RMS) delay spread, temporal autocorrelation function (ACF), level-crossing rate (LCR), power delay profile (PDP), and stationary interval, under different clusters and antenna accelerations are obtained and analyzed. The accuracy of the proposed model is verified by the measured data. The results demonstrate the usability of our model, which can be provided as a reference for the design, evaluation, and optimization of future communication networks between UAV and vehicles in urban transportation emergency communications.