Deep learning-assisted resource allocation and channel modeling for UAV to ground communication in ultra-wideband environments

Unmanned aerial vehicles (UAVs) are increasingly deployed in ultra-wideband (UWB) environments to support applications that demand high data rates and reliable connectivity. However, effective communication between UAVs and ground terminals is challenged by six-dimensional (6D) posture-induced signal variation, non-stationary channel behavior, and dynamic resource constraints. Existing models are limited in addressing 6D posture-aware fading, frequency non-stationarity, and spatiotemporal variab