Secrecy Analysis of Cell-free Massive MIMO-enabled UAV Communications

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Abstract

This paper studies physical layer security for cell-free (CF) massive multiple-input-multiple-output (mMIMO)-enabled unmanned aerial vehicles (UAV) communication under threats from multiple UAV eavesdroppers (UAV-Eves). We consider spatially correlated Rician fading channels and two eavesdropping modes: non-colluding and colluding UAV-Eves. To counter multi-antenna UAV-Eves with successive interference cancellation capabilities, we propose an artificial noise (AN)-aided secure transmission scheme. Incorporating active pilot attacks and user-centric (UC) clustering, we derive a closed-form secrecy rate lower bound under conjugate beamforming. Numerical results show that UC clustering significantly improves security compared to CF architecture, whereas pilot attacks degrade secrecy performance. Moreover, colluding UAV-Eves exhibit substantially higher security threats than non-colluding ones. The proposed AN-aided scheme ensures robust secrecy enhancement, particularly against advanced UAV-Eves.

Original languageEnglish
Title of host publicationProceedings of 2025 IEEE 15th International Conference on Signal Processing, Communications and Computing, ICSPCC 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331565466
DOIs
StatePublished - 2025
Event15th IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2025 - Hong Kong, China
Duration: 18 Jul 202521 Jul 2025

Publication series

NameProceedings of 2025 IEEE 15th International Conference on Signal Processing, Communications and Computing, ICSPCC 2025

Conference

Conference15th IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2025
Country/TerritoryChina
CityHong Kong
Period18/07/2521/07/25

Keywords

  • artificial noise-aided
  • cell-free massive MIMO
  • physical layer security
  • unmanned aerial vehicles
  • user-centric clustering

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