LAUSR

Cellular networks are difficult to meet emergency rescue due to the destruction of base stations and infrastructure caused by natural disasters. Unmanned Ground Vehicles (UGVs) and other mobile communication devices encounter significant challenges when operating in disaster areas due to limited coverage and resources. To tackle this problem, this paper integrates Unmanned Aerial Vehicles (UAVs) into the emergency communication network and constructs an air-ground integration network architecture with UAV-UGV collaboration. Specifically, multi-UGV collaborate to collect disaster information, and multi-aerial intelligent reflecting surfaces with high maneuverability can effectively assist UGVs in transmitting the collected data to the remote control center. However, there is also a serious challenge to optimize the collaboration strategy between UGVs and UAVs. To address the concern, the collaboration between UAVs and UGVs is modeled as bipartite graph, where UAVs and UGVs belong to different sets of nodes, respectively. The problem is transformed into a matching game based on the bipartite graph. A stable Bidirectional Matching Game (BMG) algorithm is proposed, where matching players maximize the utility by adjusting the selection strategy. Extensive experimental results show that the proposed BMG algorithm outperforms other benchmark algorithms in terms of utility for both UAVs and UGVs.