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<p>Intelligent reflecting surface (IRS)-enabled non-orthogonal multiple access (NOMA) energy harvesting (EH) cognitive radio (CR) networks integrate pioneering wireless technologies encompassing IRS, EH, NOMA, CR with anticipation of high throughput and energy efficiency. Despite their potential advantages, these networks encounter practical hurdles like channel severity, interference from licensed users, and non-linear EH. To evaluate their performance under these circumstances, this paper presents closed-form formulas for key metrics, accounting for Nakagami-<i>m</i> fading. Findings expose that these circumstances can hinder system performance. However, by carefully selecting system settings, we can enhance performance, optimize it, and even eliminate complete outages. Furthermore, the study reveals that these networks outperform conventional IRS-assisted orthogonal multiple access EH CR networks.</p>

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Performance Evaluation of IRS-Assisted NOMA Energy Harvesting Cognitive Radio Networks

  • 期刊论文

  • 发表日期：

    2025年10月21日

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  • Toi Le-Thanh,
  • Cuong Tran-Minh,
  • Khuong Ho-Van

摘要

Intelligent reflecting surface (IRS)-enabled non-orthogonal multiple access (NOMA) energy harvesting (EH) cognitive radio (CR) networks integrate pioneering wireless technologies encompassing IRS, EH, NOMA, CR with anticipation of high throughput and energy efficiency. Despite their potential advantages, these networks encounter practical hurdles like channel severity, interference from licensed users, and non-linear EH. To evaluate their performance under these circumstances, this paper presents closed-form formulas for key metrics, accounting for Nakagami-m fading. Findings expose that these circumstances can hinder system performance. However, by carefully selecting system settings, we can enhance performance, optimize it, and even eliminate complete outages. Furthermore, the study reveals that these networks outperform conventional IRS-assisted orthogonal multiple access EH CR networks.