论文标题
用MMWave无人机网络的基于指纹的PHY层身份验证的功率分配
Power Allocation for Fingerprint-Based PHY-Layer Authentication with mmWave UAV Networks
论文作者
论文摘要
物理层安全性（PLS）技术可以帮助保护无线网络免受窃听攻击。在本文中，我们考虑使用嵌入指纹嵌入的身份验证技术来捍卫5G蜂窝网络，该网络使用窃听者和入侵者使用无人机（UAV）系统。由于毫米波（MMWave）蜂窝网络使用狭窄和定向光束，因此PL可以进一步优势3D空间尺寸，以改善无人机用户的身份验证。考虑到多用户MMWave蜂窝网络，我们提出了一种功率分配技术，该技术共同考虑了预编码器和身份验证标签之间的发射功率的分裂，该验证标签既可以管理保密和可实现的速率。我们的结果表明，我们可以获得预期保密的最佳可实现率。
Physical layer security (PLS) techniques can help to protect wireless networks from eavesdropper attacks. In this paper, we consider the authentication technique that uses fingerprint embedding to defend 5G cellular networks with unmanned aerial vehicle (UAV) systems from eavesdroppers and intruders. Since the millimeter wave (mmWave) cellular networks use narrow and directional beams, PLS can take further advantage of the 3D spatial dimension for improving the authentication of UAV users. Considering a multi-user mmWave cellular network, we propose a power allocation technique that jointly takes into account splitting of the transmit power between the precoder and the authentication tag, which manages both the secrecy as well as the achievable rate. Our results show that we can obtain optimal achievable rate with expected secrecy.
