An Artificial-Noise-Based Approach for the Secrecy Rate Maximization of MISO VLC Wiretap Channel with Multi-Eves

Ge Shi, Yong Li, Wei Cheng, Xiang Gao, Wenjie Zhang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

In this paper, we consider improving the secure performance of multiple-input single-output visible light communication channel in the presence of multiple eavesdroppers with multiple photodiodes. Our goal is to design an optimal artificial-noise (AN) aided transmission strategy to maximize the achievable secrecy rate subject to both sum power constraint and peak amplitude constraint. We consider a joint optimization of the transmit covariance and AN covariance for the non-convex secrecy rate maximization (SRM) problem. In order to solve it, the SRM problem is transformed into a series of single-variable semidefinite programming (SDP) problems without losing any optimality, and a one-dimensional search based algorithm is proposed to handle the converted problem, with polynomial complexity. By exploiting Karush-Kuhn-Tucker conditions of the problem, beamforming is found to be optimal for the confidential information transmission. Simulation results show the superior performance of the proposed AN-aided method compared with two other AN-aided methods and no AN-aided method.

Original languageEnglish
Article number9302525
Pages (from-to)651-659
Number of pages9
JournalIEEE Access
Volume9
DOIs
StatePublished - 2021

Keywords

  • Artificial noise
  • physical layer security
  • secrecy rate maximization
  • visible light communication

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