基于认知无人机移动中继网络的物理层安全通信研究

Research on Physical Layer Security Communication for Cognitive UAV Mobile Relay Network

针对无线频谱资源稀缺和空对地视距(Line of Sight,LoS)链路的安全隐患问题,提出了一种无人机(Unmanned Aerial Vehicle,UAV)中继辅助的认知无线电网络(Cognitive Radio Network,CRN)安全传输方案,研究了在主用户和窃听者存在的情况下,次用户发射机向次用户接收机发送机密信息,UAV充当解码转发移动中继协助从源节点到合法目的节点的机密传输。目的是在源节点和中继节点的功率约束下,通过优化UAV中继的飞行轨迹、发射功率来实现保密率最大化。由于设计问题是非凸的,采用构造非凸约束代理函数的方法,将原问题近似为凸约束,并利用一种基于连续凸逼近的迭代算法来求解。仿真结果表明,相较于静态中继和无优化方案,本文所提的联合优化方案不仅获得UAV飞行的最佳路径,同时系统的平均保密率分别是传统方案的1.06倍和2.88倍。

In view of the scarcity of wireless spectrum resources and the security problems of air to ground line of sight(LoS)links,a secure transmission scheme of cognitive radio network(CRN)assisted by unmanned aerial vehicle(UAV)relay is proposed,UAV acts as a decode and forward mobile relay to assist the secret transmission from the source node to the legitimate destination node. The purpose is to maximize the security rate by optimizing the flight path and transmit power of UAV relay under the power constraints of source node and relay node. Since the design problem is nonconvex,a surrogate function with nonconvex constraints is constructed to approximate the original problem to convex constraints,and an iterative algorithm based on successive convex approximation is used to solve the problem. The simulation results show that compared with the static relay and no-optimization schemes,the proposed joint optimization scheme not only obtains the optimal path of UAV flight,but also achieves the average security rate of 1. 06 times and 2. 88 times of the traditional schemes,respectively.