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Physical layer security for massive MIMO: An overview on passive eavesdropping and active attacks

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journal contribution
posted on 2016-04-05, 13:39 authored by Dzevdan Kapetanovic, Gan Zheng, Fredrik Rusek
This article discusses opportunities and challenges of physical layer security integration in massive multiple-input multiple-output (MaMIMO) systems. Specifically, we first show that MaMIMO itself is robust against passive eavesdropping attacks. We then review a pilot contamination scheme which actively attacks the channel estimation process. This pilot contamination attack is not only dramatically reducing the achievable secrecy capacity but is also difficult to detect. We proceed by reviewing some methods from literature that detect active attacks on MaMIMO. The last part of the paper surveys the open research problems that we believe are the most important to address in the future and give a few promising directions of research to solve them.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Communications Magazine

Volume

53

Issue

6

Pages

21 - 27

Citation

KAPETANOVIC, D., ZHENG, G. and RUSEK, F., 2015. Physical layer security for massive MIMO: An overview on passive eavesdropping and active attacks. IEEE Communications Magazine, 53(6), pp. 21-27.

Publisher

© IEEE

Version

  • AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2015

Notes

(c) 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

ISSN

0163-6804

Language

  • en