CSI learning based active secure coding scheme for detectable wiretap channel

Abstract

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.