Research On Resource Optimization Technology For Cognitive UAV Network With Interference Cooperation

The rapid development of mobile communications and the explosive growth of Internet of Things devices have led to serious spectrum shortages.At the same time,due to the emergence of emerging network structures that require high transmission rates,such as augmented reality,smart homes,smart transportation,and smart cities,the communication quality of service mobile users is becoming increasingly unsatisfactory.Cognitive UAV networks can improve spectrum efficiency through spectrum sharing,as well as,it can take advantage of the controllable maneuverability and flight flexibility of UAVs to increase the transmission rate of user information.However,due to the inherent broadcast characteristics of wireless communication and the strong line-of-sight between the UAV and the ground user,the confidential information sent by the UAV is more likely to be eavesdropped by eavesdroppers,and the security communication of the cognitive UAV network is seriously challenged.Therefore,aiming at the problems of spectrum scarcity,insufficient information transmission rate,and challenging for mobile users secure communications,the focus is on researching the resource allocation technology for cognitive UAV networks with interference cooperation,establishing an optimization problem framework to maximize the average secrecy rate of secondary users,and designing resources allocation strategy that maximize average secrecy rate of secondary users.The specific research results are as follows.1.Resource allocation and trajectory optimization for cognitive UAV network with interference cooperationAiming at the problems of spectrum scarcity,insufficient information transmission rate,and challenging for mobile users secure communications,the system model of cognitive UAV networks with interference cooperation is studied,and a framework for maximizing the average secrecy rate of secondary users is established.Making use of a sub-optimal iterative algorithm based on alternate optimization method and SCA method,a resource allocation strategy for jointly optimizing UAV trajectory and transmission power is proposed to maximize the average secrecy rate of secondary users.The simulation results show that by jointly optimizing the UAV trajectory and transmission power,the scheme can effectively ensure the secure communication of secondary users.At the same time,compared with the benchmark scheme,the proposed joint optimization of UAV trajectory and transmission power resource allocation strategy can better improve the secure performance of the system.2.Robust resources allocation and trajectory optimization for cognitive UAV network with interference cooperationAiming at the actual situation that the location information of the eavesdropping user and the primary user cannot be accurately obtained in the cognitive UAV network with interference cooperation,the resource optimization problem under the bounded position estimation error model is studied,and the problem frame of maximizing the average secrecy rate of the secondary user in the worst case is established.Making use of the robust convex optimization theory,a resource allocation strategy for jointly optimizing the robust trajectory and transmission power of the UAV is proposed to maximize the average secrecy rate of secondary users.The simulation results show that by jointly optimizing the robust trajectory and transmission power of the UAV,the scheme can effectively guarantee the safe communication of the secondary users in the worst case.At the same time,compared with the benchmark scheme,the proposed resource allocation strategy for jointly optimizing the UAV robust trajectory and transmission power can better improve the secure performance of the system.