Unmanned aerial vehicle(UAV)communications are subject to the severe spectrum scarcity problem.Cognitive UAV networks are promising to tackle this issue while the confidential information is susceptible to be eavesdro...Unmanned aerial vehicle(UAV)communications are subject to the severe spectrum scarcity problem.Cognitive UAV networks are promising to tackle this issue while the confidential information is susceptible to be eavesdropped.A UAV jamming assisted scheme is proposed.A joint resource allocation and trajectories optimization problem is formulated in a UAV-assisted jamming cognitive UAV network subject to diverse power and trajectory constraints.An alternative optimization algorithm is proposed to solve the challenging non-convex joint optimization problem.Extensive simulation results demonstrate the superiority of our proposed scheme and many meaningful insights are obtained for the practical design of cognitive UAV networks.展开更多
基金This work was supported in part by the National Natural Science Foundation of China(No.62031012,62071223,and 62061030)in part by the National Key Research and Development Project of China(2018YFB1404303,2018YFB14043033,and 2020YFB1807602)+2 种基金in part by the National Key Scientific Instrument and Equipment Development Project(61827801)in part by the Open Project of the Shaanxi Key Laboratory of Information Communication Network and Security(ICNS201701)by Young Elite Scientist Sponsorship Program by CAST,and by Graduate Innovation Foundation of Jiangxi Province(YC2019-S0350).
文摘Unmanned aerial vehicle(UAV)communications are subject to the severe spectrum scarcity problem.Cognitive UAV networks are promising to tackle this issue while the confidential information is susceptible to be eavesdropped.A UAV jamming assisted scheme is proposed.A joint resource allocation and trajectories optimization problem is formulated in a UAV-assisted jamming cognitive UAV network subject to diverse power and trajectory constraints.An alternative optimization algorithm is proposed to solve the challenging non-convex joint optimization problem.Extensive simulation results demonstrate the superiority of our proposed scheme and many meaningful insights are obtained for the practical design of cognitive UAV networks.
