Aerial-IRS-Assisted Securing Communications Against Eavesdropping: Joint Trajectory and Resource Allocation

Ya Gao, Yang Zhang, He Geng, Xingwang Li*, Daniel Benevides Da Costa, Ming Zeng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Intelligent reconfigurable surface (IRS) is an innovative and promising technology to achieve intelligent reconfigurable wireless environment, and thus, enables cost-effective and energy-efficient wireless communications. Due to the broadcasting nature of the wireless signals, the reflected signal in IRS-assisted wireless communications networks might suffer from eavesdropping. Thus, it is essential to tackle the secrecy aware problems in IRS-assisted wireless communications networks. In this article, we consider an aerial IRS (AIRS) assisted wireless relay network scenario, where IRS is mounted on the aerial platform. The artificial noise is added to interrupt the eavesdropping. A secrecy rate maximization problem is formulated subject to the total transmit power and reflecting phase shift constraints. To solve this problem, we first divide the secrecy maximization problem into three subproblems, i.e., transmit power allocation, AIRS trajectory design, and reflecting phase shift optimization. These three subproblems are solved alternately until convergence to maximize the secrecy rate. Especially, for the AIRS trajectory design and reflecting phase shift optimization, we employ the successive convex approximation (SCA) and positive semidefinite relaxation (SDR) technologies to convert the nonconvex optimization problems into convex problems, respectively. The intercept probability of the proposed optimal schemes is derived and the theoretical analyses show that the intercept probability can be reduced by increasing the numbers of IRS elements. Simulation results show that the joint optimization of transmit power, AIRS trajectory and reflecting phase shift can effectively improve the secrecy rate.

Original languageEnglish
Pages (from-to)11974-11985
Number of pages12
JournalIEEE Internet of Things Journal
Volume11
Issue number7
DOIs
StatePublished - 1 Apr 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • Aerial intelligent reflecting surface
  • artificial noise (AN)
  • intercept probability (IP)
  • resource allocation
  • secrecy rate

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

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