西安电子科技大学学报（自然科学版）2023，Vol.50Issue(6)：75-83,9.DOI:10.19665/j.issn1001-2400.20230603
无人机干扰辅助认知隐蔽通信资源优化算法
Resource optimization algorithm for unmanned aerial vehicle jammer assisted cognitive covert communications
摘要
Abstract
Aiming at the covert communication scenario of an unmanned aerial vehicle(UAV)jammer assisted cognitive radio network,a transferred generative adversarial network based resource optimization algorithm is proposed for the UAV's joint trajectory and transmit power optimization problem.First,based on the actual covert communication scenario,the UAV jammer assisted cognitive covert communication model is constructed.Then,a transferred generative adversarial network based resource allocation algorithm is designed,which introduces a transfer learning and generative adversarial network.The algorithm consists of a source domain generator,a target domain generator,and a discriminator,which extract the main resource allocation features of legitimate users not transmitting covert message by transfer learning,then transform the whole covert communication process into an interactive game between the legitimate users and the eavesdropping,alternatively train the target domain generator and discriminator in a competitive manner,and achieve the Nash equilibrium to obtain resource optimization solution for the covert communications.Numerical results show that the proposed algorithm can attain near-optimal resource optimization solution for the covert communication and achieve rapid convergence under the assumptions of knowing the channel distribution information and not knowing the detection threshold of the eavesdropper.关键词
隐蔽通信/无人机/资源优化/迁移学习/生成对抗网络Key words
covert communication/unmanned aerial vehicle/resource optimization/transfer learning/generative adversarial network分类
信息技术与安全科学引用本文复制引用
廖晓闽,韩双利,朱璇,林初善,王海鹏..无人机干扰辅助认知隐蔽通信资源优化算法[J].西安电子科技大学学报（自然科学版）,2023,50(6):75-83,9.基金项目
国家自然科学基金(62201582) （62201582）
陕西省自然科学基金(2022JQ-632) （2022JQ-632）
国防科技大学信息通信学院创新基金(YJKT-ZD-2202) （YJKT-ZD-2202）
