A Geometry-Based Stochastic Channel Model for UAV-to-Ground Integrated Sensing and Communication Scenarios

Integrated sensing and communication (ISAC) is one of the key technologies in the sixth generation wireless communication network (6G). The wireless channel modeling for 6G should not only consider the communication channel, but also include the sensing channel. In this paper, we propose an air-to-ground (A2G) channel model for ISAC based on an unmanned aerial vehicle (UAV). We first calculate the channel impulse response (CIR), which sufficiently considers the characteristics of UAV (e.g., UAV wobbles, moving speed, and moving direction), the movement of scatterers, and the moving of user equipment (UE) on the ground. Secondly, we derive the statistical characteristics of the communication channel, including the space-time-frequency correlation function (STF-CF), the Doppler power spectral density (PSD), and the delay PSD. In addition, we model the echo signals from the UE and the scatterers (including the shared scatterers and the unshared scatterers) and investigate the estimation of time delay and Doppler. In addition, we analyzed the impact of UAV random wobbles, moving direction, and height, along with the scatter distributions on channel propagation characteristics. Finally, we simulate the probability of detection (Pd) and present interesting conclusions on the sensing performance related to the modulated waveform and the sensing signal-to-noise ratio (SNR). The simulation results show that the modulation waveform with constant modulus exhibits superior sensing performance compared to the modulation waveform with non-constant modulus. This work is helpful for the theoretical exploration and system design of ISAC based on UAVs.