Artificial-noise-resistant eavesdropping in MISO wiretap channels: Receiver construction and performance analysis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

We consider secure communications over MISO wiretap channels, in the presence of a passive eavesdropper with multiple antennas. In this scenario, an artificial-noise-resistant (ANR) eavesdropping behavior is introduced to invalidate the artificial noise (AN) scheme proposed by Goel et al. This novel eavesdropper, by exploiting the statistical filter derived from the collected signals, can completely eliminate the influence of AN by using only two receive antennas. In particular, the received signals are firstly syphered to eliminate the power influence of AN by a linear weight which is generated from the statistical estimation for the signal covariance matrix. In comparison with the original legitimate signals, the weighted signals are however imposed by a phase difference which can be then erased by a weight vector inferred from the available information at the eavesdropper. Based on the two filtering processes, we derive a novel expression of achievable secrecy rate and give an analytical expression for the zero-secrecy-rate distance of eavesdropper to the transmitter. Finally, we characterize the expression of maximum achievable secrecy rate (MASR) and show that the optimal power allocation strategy under an ANR eavesdropping behavior is transformed into no allocation of transmission power to AN. Numerical results are presented to illustrate the damage caused by the investigated eavesdropping behavior. Interestingly, the consequence of AN elimination is not influenced even under large number of transmit antennas.

Original languageEnglish
Title of host publication2017 IEEE 86th Vehicular Technology Conference, VTC Fall 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781509059355
DOIs
StatePublished - 2 Jul 2017
Event86th IEEE Vehicular Technology Conference, VTC Fall 2017 - Toronto, Canada
Duration: 24 Sep 201727 Sep 2017

Publication series

NameIEEE Vehicular Technology Conference
Volume2017-September
ISSN (Print)1550-2252

Conference

Conference86th IEEE Vehicular Technology Conference, VTC Fall 2017
Country/TerritoryCanada
CityToronto
Period24/09/1727/09/17

Keywords

  • Achievable secrecy rate
  • Artificial noise
  • MISO.
  • Physical layer security
  • Statistical eavesdropping

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