Unmanned aerial vehicle network transmitting power distribution method and device based on reinforcement learning

Abstract

The invention discloses an unmanned aerial vehicle network transmitting power distribution method and device based on reinforcement learning, and the method comprises the steps: initializing the states of an unmanned aerial vehicle and a user, and defining the parameters of an action space and a neural network; initializing a value function and a Q value of a current network state; interacting with the environment to receive reward feedback and calculating a Q value for adopting a current action; selecting an optimal action according to the maximum value of the reward obtained by feedback; updating the next state of the system and storing the next state into the experience pool; judging whether the experience number reaches an expected value or not, if so, starting deep reinforcement learning, and if not, continuing circulation; obtaining an instant reward according to a Bellman equation, carrying out deep learning by adopting a DPPO algorithm, and carrying out reinforcement learning by taking long-term reward function maximization as a target; and judging whether the value of the long-term reward function tends to converge, and terminating learning when the value tends to converge, thereby completing resource allocation optimization of the unmanned aerial vehicle wireless ad hoc network.

Description

technical field [0001] The present invention relates to the technical field of wireless communication networks based on drones, and in particular to a method and device for allocating transmission power of drone networks based on reinforcement learning in a wireless ad hoc network scenario for multiple drones. Background technique [0002] Unmanned Aerial Vehicle (UAV) has become an important partner in the field of wireless communication technology to provide effective wireless connection services due to its flexible controllability, high mobility, and good air-to-ground line-of-sight links. , Massive and other communication scenarios provide efficient solutions. UAV can be used as a mobile aerial base station to provide high-quality communication for users on the ground and improve the capacity of wireless networks. Compared with traditional ground communication systems, flexibility and low time cost are the advantages of UAV systems. With the help of UAV, a LOS communic...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a UAV network transmission power allocation method and device based on reinforcement learning, to solve the problems of wasting channel resources and low power allocation efficiency in the resource allocation mechanism of the current UAV wireless ad hoc network. Artificial intelligence-based UAV wireless network resource allocation scheme

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