Robust Secrecy via Aerial Reflection and Jamming: Joint Optimization of Deployment and Transmission

Xiao Tang, Hongliang He, Limeng Dong, Lixin Li, Qinghe Du, Zhu Han

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Reconfigurable intelligent surfaces (RISs) are recognized with great potential to strengthen wireless security, yet the performance gain largely depends on the deployment location of RISs in the network topology. In this article, we consider the anti-eavesdropping communication established through an RIS at a fixed location, as well as an aerial platform mounting another RIS and a friendly jammer to further improve the secrecy. The aerial RIS helps enhance the legitimate signal and the aerial cooperative jamming is strengthened through the fixed RIS. The security gain with aerial reflection and jamming is further improved with the optimized deployment of the aerial platform. We particularly consider the imperfect channel state information issue and address the worst case secrecy for robust performance. The formulated robust secrecy rate maximization problem is decomposed into two layers, where the inner layer solves for reflection and jamming with robust optimization, and the outer layer tackles the aerial deployment through deep reinforcement learning. Simulation results show the deployment under different network topologies and demonstrate the performance superiority of our proposal in terms of the worst case security provisioning as compared with the baselines.

Original languageEnglish
Pages (from-to)12562-12576
Number of pages15
JournalIEEE Internet of Things Journal
Volume10
Issue number14
DOIs
StatePublished - 15 Jul 2023

Keywords

  • Aerial deployment
  • deep reinforcement learning
  • physical-layer security
  • reconfigurable intelligent surface (RIS)

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