Spatio-Temporal Wireless-Optical Planning for Multi-UAV Networks

2026-09-30

AI Summary

This study addresses the congestion problem in dense UAV networks caused by neglecting optical backhaul load, and proposes the STWO algorithm. This method introduces a novel spatiotemporal wireless-optical joint sensing mechanism that updates backhaul occupancy status in real time during sequential planning. By jointly optimizing flight distance, wireless link quality, and dynamic optical link load ratio, it achieves collaborative congestion-avoidance scheduling for multiple UAVs. Experimental results demonstrate that the proposed algorithm reduces peak optical load by 56.4% and decreases the congestion rate by 72.6%, significantly enhancing network transmission reliability.

Abstract

Multi-unmanned aerial vehicle (UAV) networks in urban low-altitude environments couple UAV mobility, wireless access, and optical backhaul resources. Existing path-planning methods optimize flight distance or wireless signal quality, but can still concentrate traffic on shared optical backhaul links. We present Spatio-Temporal Wireless-Optical (STWO) planner, a backhaul-aware path-planning algorithm that jointly considers flight distance, wireless link quality, and time-varying optical-link offered-load ratio. STWO updates backhaul occupancy during sequential multi-UAV planning, allowing later UAVs to avoid congested optical paths while maintaining wireless connectivity. Experiments show that STWO reduces peak optical-link offered-load ratio by up to 56.4\% and congestion ratio by up to 72.6\% under dense UAV deployment, demonstrating the importance of wireless-optical awareness for reliable multi-UAV transmission.

Problem

• Multi-UAV networks
• Path planning
• Optical backhaul congestion
• Wireless-optical coupling

Innovation

• Multi-UAV Networks
• Path Planning
• Optical Backhaul
• Spatio-Temporal Optimization
• Load Balancing