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<p>Optical intelligent reflecting surfaces (IRS) represent a breakthrough technology for enhancing free-space optical (FSO) communication flexibility and coverage. However, inherent optical signal characteristics render these systems critically vulnerable to malicious jamming, demanding robust resilience analysis. This work conducts a comprehensive jamming impact analysis under two practical scenarios: destination-directed and IRS-directed jamming. We develop novel channel models capturing the combined effects of path loss, atmospheric turbulence, pointing errors, and angle-of-arrival fluctuations. Closed-form expressions for the average bit error rate and outage probability are established for both intensity modulation/direct detection and heterodyne detection schemes. Asymptotic analyses reveal the diversity order and coding gain in high signal-to-noise ratio regimes. Monte Carlo validations demonstrate how jamming active probability, atmospheric conditions, and geometric alignment fundamentally govern system security. This study delivers essential design guidelines for optimizing IRS-assisted FSO systems against evolving jamming threats.</p>

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Jamming-resilient optical IRS-assisted FSO communications: performance analysis under destination- and IRS-directed jamming

  • 期刊论文

  • 发表日期：

    2025年12月8日

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  • Jingyu Wang,
  • Dingshan Gao,
  • Deqiang Ding,
  • Xinliang Zhang

摘要

Optical intelligent reflecting surfaces (IRS) represent a breakthrough technology for enhancing free-space optical (FSO) communication flexibility and coverage. However, inherent optical signal characteristics render these systems critically vulnerable to malicious jamming, demanding robust resilience analysis. This work conducts a comprehensive jamming impact analysis under two practical scenarios: destination-directed and IRS-directed jamming. We develop novel channel models capturing the combined effects of path loss, atmospheric turbulence, pointing errors, and angle-of-arrival fluctuations. Closed-form expressions for the average bit error rate and outage probability are established for both intensity modulation/direct detection and heterodyne detection schemes. Asymptotic analyses reveal the diversity order and coding gain in high signal-to-noise ratio regimes. Monte Carlo validations demonstrate how jamming active probability, atmospheric conditions, and geometric alignment fundamentally govern system security. This study delivers essential design guidelines for optimizing IRS-assisted FSO systems against evolving jamming threats.