In this study, the authors consider the problem of secure and reliable communication with uncertain channel state information (CSI) and present a new solution named active secure coding which combines the machine-learning methods with the traditional physical-layer secure coding scheme. First, the authors build a detectable wiretap channel model by combining the hidden Markov model with the compound wiretap channel model, in which the varying of channel block CSI is a Markov process and the detected information is a stochastic emission from the current CSI. Next, the authors present a CSI-learning scheme to learn the CSI from the detected information by the Baum–Welch and Viterbi algorithms. Then the authors construct explicit secure polar codes based on the learned CSI, and combine it with the CSI-learning scheme to form the active secure polar coding scheme. Simulation results show that an acceptable level of reliability and security can be achieved by the proposed active secure polar coding scheme.

中文翻译：

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基于CSI学习的可检测窃听通道主动安全编码方案

在这项研究中，作者考虑了具有不确定信道状态信息（CSI）的安全可靠通信问题，并提出了一种新的解决方案，称为主动安全编码，该解决方案将机器学习方法与传统的物理层安全编码方案相结合。首先，作者将隐藏的马尔可夫模型与复合窃听通道模型相结合，建立了可检测的窃听通道模型，其中，通道块CSI的变化是马尔可夫过程，检测到的信息是来自当前CSI的随机发射。接下来，作者提出了一种CSI学习方案，以通过Baum-Welch和Viterbi算法从检测到的信息中学习CSI。然后作者根据学习到的CSI构造显式的安全极性代码，并将其与CSI学习方案结合起来，形成主动安全极性编码方案。仿真结果表明，所提出的主动安全极性编码方案可以达到可接受的可靠性和安全性水平。