轨迹和干扰功率联合优化的无人机主动窃听算法

研究一种无人机(UAV)作为合法窃听器的无线通信窃听算法.首先,将一个合法窃听器(UAV(E))用于窃听可疑发射器(UAV(B))发送到地面可疑接收器的可疑信息.然后,利用可疑系统的特点,提出一种有效的主动干扰方案,从而最大限度地提高有效窃听速率;针对构造的原问题是一个优化变量耦合的混合非凸优化问题,应用更新速率辅助的块坐标下降和连续凸优化技术,在每次迭代中交替优化无人机轨迹和干扰功率.最后,针对非凸的无人机轨迹优化和干扰功率优化问题,分别利用连续凸优化算法将原非凸问题转化为近似的次优化问题,再使用凸优化方法进行求解.仿真结果表明:相较于其他基准算法,文中算法具有更高的有效窃听速率.

Unmanned Aerial Vehicle Proactive Eavesdropping Algorithm Using Joint Optimization of Trajectory and Jamming Power

Research a wireless communication eavesdropping algorithm of unmanned aerial vehicle(UAV)as a legitimate eavesdropper. Firstly, a legitimate eavesdropper(UAV(E))attempts to eavesdrop the suspicious messages sent from the suspicious transmitter(UAV(B))to the suspicious receiver on the ground. Secondly, using the characteristics of the suspicious system, an effective proactive jamming scheme is proposed to maximize increase the effective eavesdropping rate. For the constructive original problem is a hybrid non-convex optimization problem with optimized variable coupling, the update rate-assisted block coordinate descent and successive convex optimization technology are applied to alternately optimize the UAV trajectory and jamming power in each iteration. Finally, for the problem of non-convex UAV trajectory optimization and jamming power optimization, the successive convex approximation algorithm is used to transform the original non-convex problem into an approximate sub-optimization problem, furthermore, use the convex optimization method to get the solution. The simulation results show that the proposed algorithm has a higher effective eavesdropping rate than other benchmark algorithms.