论文标题
绩效分析和优化干扰素辅助的多安丹娜无人机秘密通信
Performance Analysis and Optimization for Jammer-Aided Multi-Antenna UAV Covert Communication
论文作者
论文摘要
无人驾驶汽车(UAV)引起了很多研究的关注,因为它们的机动性很高,并且成本低,用作临时航空站(BSS),并为下一代通信网络提供了高数据速率。为了保护用户隐私,同时避免了监狱长的检测,我们研究了一个干扰素的无人机秘密通信系统,该系统的目的是通过优化的传输和阻塞能力来最大化用户的秘密速度。无人机配备了多安田,可同时为多用户服务并提高服务质量。通过考虑一般的复合褪色和阴影通道模型,我们得出了信号与间接式 - 加语比率(SINR)的确切概率密度(PDF)和累积分布函数(CDF)。获得的PDF和CDF用于得出封闭形式的表达式以进行检测误差概率和掩盖率。此外,秘密利率最大化问题被提出为NASH谈判游戏,并引入了NASH谈判解决方案(NBS)以调查用户之间的谈判。为了解决NBS,我们提出了两种算法,即基于粒子群优化的和关节二键量分配算法,以在监狱长的最佳检测阈值下实现掩盖和高数据速率。所有配方的问题均被证明是凸的,并且分析了复杂性。提出了数值结果,以验证理论性能分析,并显示实现我们算法的秘密交流的有效性和成功。
Unmanned aerial vehicles (UAVs) have attracted a lot of research attention because of their high mobility and low cost in serving as temporary aerial base stations (BSs) and providing high data rates for next-generation communication networks. To protect user privacy while avoiding detection by a warden, we investigate a jammer-aided UAV covert communication system, which aims to maximize the user's covert rate with optimized transmit and jamming power. The UAV is equipped with multi-antennas to serve multi-users simultaneously and enhance the Quality of Service. By considering the general composite fading and shadowing channel models, we derive the exact probability density (PDF) and cumulative distribution functions (CDF) of the signal-to-interference-plusnoise ratio (SINR). The obtained PDF and CDF are used to derive the closed-form expressions for detection error probability and covert rate. Furthermore, the covert rate maximization problem is formulated as a Nash bargaining game, and the Nash bargaining solution (NBS) is introduced to investigate the negotiation among users. To solve the NBS, we propose two algorithms, i.e., particle swarm optimization-based and joint twostage power allocation algorithms, to achieve covertness and high data rates under the warden's optimal detection threshold. All formulated problems are proven to be convex, and the complexity is analyzed. The numerical results are presented to verify the theoretical performance analysis and show the effectiveness and success of achieving the covert communication of our algorithms.