Vision-Assisted UAV Relay Triggering for Proactive Blockage Mitigation in Air–Ground Integrated mmWave V2X Networks
TL;DR
A vision-assisted unmanned aerial vehicle (UAV) relay triggering framework that uses roadside multi-camera images to predict the future link state of a target vehicle and triggers a UAV decode-and-forward (DF) relay before the direct roadside-unit (RSU)–vehicle link becomes unreliable.
Abstract
Millimeter-wave (mmWave) vehicular-to-everything (V2X) links are highly vulnerable to sudden blockages in dense urban traffic. Since terrestrial roadside links can degrade rapidly, and alternative ground paths are often limited, maintaining reliable service with only ground networking resources remains challenging. To enhance link reliability by exploiting aerial relay resources in air–ground integrated networks, this paper proposes a vision-assisted unmanned aerial vehicle (UAV) relay triggering framework. The framework uses roadside multi-camera images to predict the future link state of a target vehicle and triggers a UAV decode-and-forward (DF) relay before the direct roadside-unit (RSU)–vehicle link becomes unreliable. To enable target-specific prediction, a template-guided image-matching module is developed to localize the target vehicle in multi-view images. The matched features are fused and temporally modeled to predict future LoS, NLoS, and Absent states, with the predicted NLoS probability further used to determine the UAV activation decision through a probability-based triggering policy. Simulation results on a 3D ray-tracing urban V2X dataset show that the proposed dual-view predictor achieves about 99% validation accuracy, compared with about 87% for the single-view baseline. The proposed relay triggering scheme reduces the outage probability from 15.08% for RSU-only transmission and 4.49% for reactive relaying to 0.76%, and improves the 5th-percentile rate from 11.72 Mbps to 22.49 Mbps over reactive relaying.