论文标题
空中认知无线网络的联合轨迹设计和用户计划
Joint Trajectory Design and User Scheduling of Aerial Cognitive Radio Networks
论文作者
论文摘要
无人驾驶汽车(UAV)已被广泛用于增强无线通信的端到端性能,因为无人机和陆地节点之间的链接具有很高的可能性。但是,LOS链接中信号传播的广播特征使其容易被恶意窃听器窃听,这对无线通信的安全构成了巨大的挑战。本文研究了空中认知无线网络(CRN)的安全性。空降基站使用与主网络相同的频谱将机密消息传输给二级用户。空中基站传输干扰信号,以抑制窃听器以提高保密性能。考虑了窃听节点位置的不确定性,并且通过优化多个用户的计划,无人机的轨迹和传输功率来最大化认知用户的平均保密率。为了解决混合多个整数可变问题的非凸优化问题,我们提出了一种基于块坐标下降和连续凸近近似的迭代算法。数值结果验证了我们提出的算法的有效性,并证明我们的方案有益于提高空中CRN的保密性能。
Unmanned aerial vehicles (UAVs) have been widely employed to enhance the end-to-end performance of wireless communications since the links between UAVs and terrestrial nodes are line-of-sight (LoS) with high probability. However, the broadcast characteristics of signal propagation in LoS links make it vulnerable to being wiretapped by malicious eavesdroppers, which poses a considerable challenge to the security of wireless communications. This paper investigates the security of aerial cognitive radio networks (CRNs). An airborne base station transmits confidential messages to secondary users utilizing the same spectrum as the primary network. An aerial base station transmits jamming signals to suppress the eavesdropper to enhance secrecy performance. The uncertainty of eavesdropping node locations is considered, and the average secrecy rate of the cognitive user is maximized by optimizing multiple users' scheduling, the UAVs' trajectory, and transmit power. To solve the non-convex optimization problem with mixed multiple integers variable problem, we propose an iterative algorithm based on block coordinate descent and successive convex approximation. Numerical results verify the effectiveness of our proposed algorithm and demonstrate that our scheme is beneficial to improving the secrecy performance of aerial CRNs.