The low-altitude wireless network (LAWN), mainly composed of uncrewed aerial vehicles (UAVs), is a promising paradigm for emergency response. However, the implementation of LAWN requires achieving efficient and reliable coordination among multifunctional UAVs. Therefore, how to guarantee communication reliability and realize coordination among heterogeneous UAVs in unpredictable environments remains a key issue. In this article, we propose a novel LAWN framework, where reconnaissance UAVs first collect situational information, relay UAVs forward the sensed data to the fire station for decision-making, and firefighting UAVs execute material delivery according to the returned commands, thereby forming a closed-loop emergency response. Then, we formulate the optimization problem to minimize the total response delay while ensuring the fairness of multipath routing. To tackle the NP-hard problem, we decompose it into two subproblems of the route construction problem (RCP) and firefighting scheduling problem (FSP). We design the regular geometric topology for the UAV deployment, derive the transmission power in closed form to establish feasible links, and RCP is reformulated into a tractable integer linear programming problem. Then, the gray wolf optimization-based firefighting scheduling algorithm (GWO-FSA) is proposed for the task assignment, resource allocation, and path planning of UAVs. Extensive simulation results demonstrate the effectiveness of the proposed scheme in enhancing the emergency response efficiency.
Jia He, Ziye Jia, Can Cui et al.· IEEE Internet of Things Jour...· 0 citations
Low-altitude wireless networks have emerged as a promising platform for enabling the safe and efficient operation of unmanned aerial vehicles (UAVs). However, due to the limited spectrum and airspace resources, it is challenging to efficiently accomplish UAV flight tasks without collisions. In this paper, we propose a sequential framework with two coupled stages that coordinates spectrum allocation and airspace planning to construct efficient low-altitude air corridors. Specifically, the low-altitude airspace is discretized into a set of digital grids, where obstacles are modeled as impermeable units. Then, we formulate an optimization problem to minimize the total traversal cost of air corridors, which is challenging to solve due to the tight coupling between spectrum allocation and path planning.Therefore, we first design a constrained Vickrey-Clarke-Groves (VCG) ascending auction mechanism to allocate the spectrum resources. Then, we propose a joint spectrum and airspace resource allocation algorithm to minimize the total traversal cost of air corridors. Finally, simulation results show that the proposed algorithms achieve lower total costs than the baseline algorithms.
Ya-Fei Guo, Ziye Jia, Lei Zhang et al.· 0 citations
Low-altitude wireless networks have emerged as a promising platform for enabling the safe and efficient operation of unmanned aerial vehicles (UAVs). However, due to the limited spectrum and airspace resources, it is challenging to efficiently accomplish UAV flight tasks without collisions. In this paper, we propose a sequential framework with two coupled stages that coordinates spectrum allocation and airspace planning to construct efficient low-altitude air corridors. Specifically, the low-altitude airspace is discretized into a set of digital grids, where obstacles are modeled as impermeable units. Then, we formulate an optimization problem to minimize the total traversal cost of air corridors, which is challenging to solve due to the tight coupling between spectrum allocation and path planning.Therefore, we first design a constrained Vickrey-Clarke-Groves (VCG) ascending auction mechanism to allocate the spectrum resources. Then, we propose a joint spectrum and airspace resource allocation algorithm to minimize the total traversal cost of air corridors. Finally, simulation results show that the proposed algorithms achieve lower total costs than the baseline algorithms.
Ya-Fei Guo, Ziye Jia, Lei Zhang et al.· 0 citations
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