Safeguarding multiuser communication using full‐duplex jamming and Q‐learning algorithm

Abstract

In this study, the authors consider secure communications in multiuser wireless networks where full-duplex (FD) jamming operates to enhance physical layer security. The considered multiuser system is equipped with FD legitimate receivers in contrast to conventional frameworks where a half-duplex (HD) receiver is at hand. This study investigates an alternative solution in which the authors take advantage of FD capability of the receivers to send jamming signals against the eavesdropper. Under these assumptions, the impact of self-interference and channel interference on physical layer security is investigated. They derive the expressions of secrecy outage probability and ergodic secrecy rate in the proposed system. Two FD jammer selection schemes are proposed to further improve the security. In addition, they apply a reinforcement learning technology, called Q-learning, to model the interaction between the source and multiple jamming users. The preliminary results show that the application of FD jamming and user selection scheme leads to a significant improvement in the wireless network security.