Intelligent Reflecting Surface Assisted Secrecy Communication: Is Artificial Noise Helpful or Not?

By Xinrong Guan, Qingqing Wu, Rui Zhang. IEEE Wireless Communications Letters, 2019

456 citations recorded by the source corpus.

In this letter, we investigate whether the use of artificial noise (AN) is helpful to enhance the secrecy rate of an intelligent reflecting surface (IRS) assisted wireless communication system. Specifically, an IRS is deployed nearby a single-antenna receiver to assist in the transmission from a multi-antenna transmitter, in the presence of multiple single-antenna eavesdroppers. Aiming to maximize the achievable secrecy rate, a design problem for jointly optimizing transmit beamforming with AN or jamming and IRS reflect beamforming is formulated, which is however difficult to solve due to its non-convexity and coupled variables. We thus propose an efficient algorithm based on alternating optimization to solve the problem sub-optimally. Simulation results show that incorporating AN in transmit beamforming is beneficial under the new setup with IRS reflect beamforming. In particular, it is unveiled that the IRS-aided design without AN even performs worse than the AN-aided design without IRS as the number of eavesdroppers near the IRS increases.

Subfields: Electrical and Electronic Engineering, Genetics

View Paper: https://www.semanticscholar.org/paper/af7b5182f092e0e43ecdc0e5a41f67cae729e29f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

  1. Rui Zhang
  2. Yuanwei Liu
  3. Qingqing Wu
  4. Merouane Debbah
  5. Chau Yuen
  6. M. Di Renzo
  7. Xidong Mu
  8. Changsheng You

In Genetics

  1. Changsheng You
  2. Rui Zhang
  3. Qingqing Wu
  4. M. Di Renzo
  5. Shuowen Zhang
  6. Beixiong Zheng
  7. Dusist Niyato
  8. Merouane Debbah

Citations in the corpus