Wireless Physical Layer Secure Transmission Against Aerial Eavesdropping

With the mature development and wide application of unmanned aerial vehicle(UAV)technology,UAV communications will play a vital role in future wireless communications.UAVs are flexible and easy to be deployed,and can be applied to a variety of scenarios.For example,the search and rescue activities in mountains and forests,and the temporary deployment in network outage areas.However,due to the broadcast characteristics of wireless channels,it is easy for eavesdroppers to obtain legitimate information.Meantime,UAV eavesdroppers(UEDs)can establish a better line-of-sight eavesdropping link by using their mobility characteristics in airspace.Therefore,compared with ground eavesdroppers,UAV eavesdroppers will bring more server challenges to the physical layer security transmission.On the other hand,the endurance of Internet of things(IoT)devices or UAVs is limited,and it is difficult to ensure the security requirements of communications by using complex encryption algorithms.In this context,it is urgent to study efficient and reliable countermeasure schemes against the malicious eavesdropping attacks from airspace.Aiming at the above problems and research requirements,this paper introduces a jamming UAV to interfere with the potential UEDs of the terrestrial communication system,and proposes two security transmission strategies to improve the average secrecy rate of the system: 1)intelligent deployment of the jamming UAV against aerial eavesdropping;2)energy-saving and efficient deployment of the jamming UAV against aerial eavesdropping.The specific research contents of this paper are summarized as follows:(1)Intelligent deployment of the jamming UAV against aerial eavesdropping1)In order to maximize the average secrecy rate while deploying the jamming UAV as quickly as possible,the joint optimization of three-dimensional trajectory of the jamming UAV and the user association of the ground base station is formulated;2)Since this problem is non-convex optimization problem,it is difficult to directly solve it in polynomial time.This paper proposes an enhanced genetic algorithm,which improves the performance by developing a combined encoding method and a fitness-based crossover method;3)Simulations and analysis verify the efficiency and the convergence performance of the proposed algorithm,compared with other schemes,the proposed scheme can effectively improve the secrecy performance of the system and its convergence time is shorter.(2)Energy-saving and efficient deployment of the jamming UAV against aerial eavesdropping1)In the practical systems,the transmit powers of the jamming UAV and ground base station are limited,so it is necessary to consider the energy-saving requirement of the system while improving the average secrecy rate.This paper jointly optimizes the three dimensional trajectory of the jamming UAV,user association,transmission power of the ground base station and jamming UAV.2)The formulated problem belongs to the non-convex optimization problem and optimizes the transmission power variables,which leads to an increase in the scale of the problem and increases the difficulty of solving.In order to guarantee the feasibility of the solution,a power control and jamming UAV’s trajectory optimization algorithm based on the successive convex approximation is proposed;3)First,this paper decouples the transformed non-convex average secrecy rate maximization problem into three subproblems,that is,user association,trajectory optimization and power optimization subproblems;next,for the user association subproblem,an approximate convex optimization problem is obtained by continuing the variables;for the non-convex trajectory optimization and power optimization subproblems,the successive convex optimization algorithm is applied to perform the convex approximation,respectively.4)On the basis of solving three subproblems,an iterative algorithm based on the alternative algorithm is proposed to obtain an approximate solution to the original problem.Simulation results demonstrate that this algorithm can effectively improve the average secrecy rate.