Physical layer security is a useful tool to prevent confidential information from wiretapping. In this paper, we consider a generalized model of conventional physical layer security, referred to as hierarchical information accessibility (HIA). A main feature of the HIA model is that a network has a hierarchy in information accessibility, wherein decoding feasibility is determined by a priority of users. Under this HIA model, we formulate a sum secrecy rate maximization problem with regard to precoding vectors. This problem is challenging since multiple non-smooth functions are involved into the secrecy rate to fulfill the HIA conditions and also the problem is non-convex. To address the challenges, we approximate the minimum function by using the LogSumExp technique, thereafter obtain the first-order optimality condition. One key observation is that the derived condition is cast as a functional eigenvalue problem, where the eigenvalue is equivalent to the approximated objective function of the formulated problem. Accordingly, we show that finding a principal eigenvector is equivalent to finding a local optimal solution. To this end, we develop a novel method called generalized power iteration for HIA (GPI-HIA). Simulations demonstrate that the GPI-HIA significantly outperforms other baseline methods in terms of the secrecy rate.

中文翻译：

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下行链路 MU-MIMO 中分层信息可访问性的安全传输

物理层安全是防止机密信息被窃听的有用工具。在本文中，我们考虑了传统物理层安全的广义模型，称为分层信息可访问性 (HIA)。HIA 模型的一个主要特点是网络在信息可访问性方面具有层次结构，其中解码的可行性由用户的优先级决定。在此 HIA 模型下，我们针对预编码向量制定了总保密率最大化问题。这个问题具有挑战性，因为多个非平滑函数涉及到满足 HIA 条件的保密率，而且问题是非凸的。为了应对挑战，我们使用 LogSumExp 技术逼近最小函数，然后获得一阶最优条件。一个关键的观察结果是，导出的条件被转换为函数特征值问题，其中特征值等价于公式化问题的近似目标函数。因此，我们表明找到主特征向量等效于找到局部最优解。为此，我们开发了一种称为 HIA 广义幂迭代 (GPI-HIA) 的新方法。模拟表明，GPI-HIA 在保密率方面明显优于其他基线方法。我们开发了一种称为 HIA 广义幂迭代 (GPI-HIA) 的新方法。模拟表明，GPI-HIA 在保密率方面明显优于其他基线方法。我们开发了一种称为 HIA 广义幂迭代 (GPI-HIA) 的新方法。模拟表明，GPI-HIA 在保密率方面明显优于其他基线方法。