Considering multi-user downlink ultra-high reliability and low latency communications (URLLC), this paper employs the artificial noise (AN) technique to establish a secure and covert broadcast communication paradigm for the first time. Specifically, a multi-antenna transmitter (Alice) broadcasts the confidential information to multiple legitimate users in the presence of a multi-antenna malicious warden (Willie) and a multi-antenna eavesdropper (Eve). It is well known that AN is an effective technique for securing the physical layer security (PLS) of signal transmissions. Nevertheless, AN emission also exposes the signal transmission and decreases the signal covertness. Taking into account the impact of short-packet URLLC transmissions, we investigate the joint optimization of the precoder and AN to maximize the secrecy rate under the covertness constraint. Although the considered problem is nonconvex, we propose a branch-reduce-and-bound (BRB)-based algorithm to solve it optimally. However, the nested-loop structure of the BRB-based algorithm incurs a high computational complexity. To strike a balance between the performance and computational complexity, we also propose a low-complexity penalty successive convex approximation (SCA)-based algorithm, whose performance approaches that of the optimal BRB-based algorithm, particularly in the low to medium transmit power regime. Simulation results demonstrate the excellent performance of our proposed optimization algorithms compared with various benchmark algorithms and unveil the importance of exploiting AN for secrecy provisioning.

中文翻译：

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在有限块长度的广播频道中实现隐蔽性和安全性

考虑到多用户下行超高可靠低时延通信（URLLC），本文首次采用人工噪声（AN）技术建立了一种安全隐蔽的广播通信范式。具体来说，多天线发射器 (Alice) 在多天线恶意管理员 (Willie) 和多天线窃听者 (Eve) 存在的情况下将机密信息广播给多个合法用户。众所周知，AN 是一种确保信号传输的物理层安全 (PLS) 的有效技术。然而，AN发射也暴露了信号传输并降低了信号的隐蔽性。考虑到短包 URLLC 传输的影响，我们研究了预编码器和 AN 的联合优化，以在隐蔽性约束下最大化保密率。尽管所考虑的问题是非凸的，但我们提出了一种基于分支归约定界 (BRB) 的算法来优化解决它。然而，基于 BRB 的算法的嵌套循环结构会产生很高的计算复杂度。为了在性能和计算复杂度之间取得平衡，我们还提出了一种基于低复杂度惩罚逐次凸逼近 (SCA) 的算法，其性能接近基于最佳 BRB 的算法，特别是在中低发射功率范围内. 仿真结果证明了我们提出的优化算法与各种基准算法相比具有出色的性能，并揭示了利用 AN 进行保密配置的重要性。