一种面向无人机通信的协作干扰安全传输技术

Cooperative Interference Secure Transmission in UAV Communication System

  • 摘要: 本文利用无人机的高机动特性带来信道的动态变化这一机理,通过合理地控制无人机位置,靠近合法节点并远离窃听节点,增加合法节点的信道增益,削弱窃听节点的信道增益,从而提高信源端和目的端的安全通信容量。已有的无人机空地信道模型大多仅考虑视距传输链路,本文在此基础上增加了非视距链路(Not Line of Sight, NLOS),并且在窃听者位置存在估计误差条件下,建立了两架无人机协同通信场景,在上述场景下通过合理规划两架无人机飞行轨迹,增强合法信道增益,削弱窃听信道增益,并联合无人机的功率分配,实现最大化平均保密速率。该优化问题为非凸问题,因此采用了连续凸近似(Successive Convex Approximation, SCA)以及块坐标下降算法 (Block Coordinate Descent Algorithm, BCD)来解决问题。仿真结果表明在视距链路和非视距链路同时存在的前提下,通过规划两架无人机的飞行轨迹,信号功率,能有效提升无人机通信系统的保密速率。

     

    Abstract: ‍ ‍In this paper, we argue that the high mobility of unmanned aerial vehicles (UAVs) can bring about the dynamic changes of channels, so that the legitimate channel gain can be enhanced and the eavesdropping channel gain can be weakened by controlling UAV position reasonably, thereby improving the secrecy rate between the legitimate nodes. Different from most existing UAV air-ground channel models, in which only the line-of-sight (LOS) transmission link is considered, this paper investigates the physical security scheme under a channel that includes the non-line-of-sight (NLOS) and LOS links. Further we establish UAVs cooperative communication scenarios under the presenc of estimation error of the eavesdropper’s position. The joint optimization of the UAV flight trajectory and the transmit power is studied to achieve the maximum secrecy rate, which is a non-convex optimization problem in the above scenario. To deal with the optimization problem, Successive Convex Approximation (SCA) and Block Coordinate Descent Algorithm (BCD) are used to solve this problem. The simulation results show that with the existence of both line-of-sight and non-line-of-sight links, by effectively planning the UAVs flight trajectory and transmit power, the secrecy rate of UAV communication system can be greatly improved.

     

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