DQN-based decentralized multi-agent JSAP resource allocation for UAV swarm communication

作     者：LI Jie DANG Xiaoyu LI Sai LI Jie;DANG Xiaoyu;LI Sai

作者机构：College of Electronic and Information EngineeringNanjing University of Aeronautics and AstronauticsNanjing 211106China 

出 版 物：《系统工程与电子技术：英文版》 (Journal of Systems Engineering and Electronics)

年 卷 期：2023年第34卷第2期

页      面：289-298页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 

基　　金：supported by the National Natural Science Foundation of China(62031017 61971221) 

主　　题：joint spectrum and power(JSAP) unmanned aerial vehicle(UAV)swarm communication deep Q-learning network(DQN) UAV to UAV(U2U) 

摘      要：It is essential to maximize capacity while satisfying the transmission time delay of unmanned aerial vehicle(UAV)swarm communication *** order to address this challenge,a dynamic decentralized optimization mechanism is presented for the realization of joint spectrum and power(JSAP)resource allocation based on deep Q-learning networks(DQNs).Each UAV to UAV(U2U)link is regarded as an agent that is capable of identifying the optimal spectrum and power to communicate with one *** convolutional neural network,target network,and experience replay are adopted while *** findings of the simulation indicate that the proposed method has the potential to improve both communication capacity and probability of successful data transmission when compared with random centralized assignment and multichannel access methods.