Intelligent Wireless Resource Allocation Algorithm for Unmanned Aerial Vehicle Integrated Communication and Sensing Networks in Railway Emergency Scenarios
In railway emergency scenarios with ground infrastructure vulnerable to damage from harsh natural environments,an Unmanned Aerial Vehicle(UAV)integrated communication and sensing wireless access network architecture is proposed in this paper,enabling real-time environmental sensing and information backhaul.Given the limited endurance of UAVs,a train braking distance model and a UAV energy consumption model are established,which are then jointly utilized to adjust the UAV flight speed and communication transmit power,optimizing overall UAV energy consumption while satisfying communication performance requirements during information backhaul and environmental sensing.Analysis reveals that this optimization problem conforms to the Markov Decision Process(MDP).Consequently,an intelligent wireless resource allocation algorithm for UAV integrated communication and sensing,grounded in the Double Deep Q Network(DDQN),is proposed to tackle the problem.The simulation results demonstrate that the proposed algorithm exhibits excellent convergence performance and maximizes the operational duration of UAV communications,while meeting the requirements for environmental sensing and information backhaul in railway emergency scenarios.
Railway emergency communicationUnmanned Aerial Vehicle(UAV)Integrated communication and sensingWireless resource allocationDeep reinforcement learning
万方数据
维普
