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<p>This paper proposes a novel approach for resource allocation in Non Orthogonal Multiple Access Cognitive Radio Networks, named Enabled Stackelberg Pairing and Allocation (CRN-NOMA-ESPA) technique. This study comprehensively addresses the major resource allocation challenges of spectral efficiency, user fairness, and interference management in the presence of a heterogeneous ultra-dense network. The proposed ESPA technique exploits a two-step optimization process: a matching-based user-channel assignment followed by a two-level Stackelberg game-theoretic power allocation. The performance is evaluated based on different benchmarks such as system sum rate, fairness index, outage probability, energy efficiency, and interference to primary users. Extensive simulation results verify that proposed CRN-NOMA-ESPA achieve up to 23.6% higher system sum rate, 12.6% better fairness, and 2.1% of magnitude lower outage probability compared with state of art techniques includes Orthogonal Frequency-Division Multiple Access (OFDMA), Non-Continuous OFDM (NC-OFDM), Non-Cooperative Game-Based OFDMA (NC-Game-OFDMA), Energy-Efficient Stackelberg Pairing and Power Allocation (ES-PPA), Radio Access Network Pairing and Power Allocation (RAN-PPA), Orthogonal Multiple Access (OMA), Full-Duplex Non-Orthogonal Multiple Access (F-NOMA), Cognitive Radio Non-Orthogonal Multiple Access (CR-NOMA), and Optimal Power Allocation in Non-Orthogonal Multiple Access (OPA-NOMA) at the cost of low energy efficiency and highly controlled interference to primary users.</p>

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Enabled Stackelberg Pairing and Allocation Technique for Efficient Resource Management in NOMA-Based Cognitive Radio Networks

  • 期刊论文

  • 发表日期：

    2025年3月1日

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  • R. Surender,
  • S. Oudaya Coumar,
  • M. Raja,
  • S. Thiyagarajan

摘要

This paper proposes a novel approach for resource allocation in Non Orthogonal Multiple Access Cognitive Radio Networks, named Enabled Stackelberg Pairing and Allocation (CRN-NOMA-ESPA) technique. This study comprehensively addresses the major resource allocation challenges of spectral efficiency, user fairness, and interference management in the presence of a heterogeneous ultra-dense network. The proposed ESPA technique exploits a two-step optimization process: a matching-based user-channel assignment followed by a two-level Stackelberg game-theoretic power allocation. The performance is evaluated based on different benchmarks such as system sum rate, fairness index, outage probability, energy efficiency, and interference to primary users. Extensive simulation results verify that proposed CRN-NOMA-ESPA achieve up to 23.6% higher system sum rate, 12.6% better fairness, and 2.1% of magnitude lower outage probability compared with state of art techniques includes Orthogonal Frequency-Division Multiple Access (OFDMA), Non-Continuous OFDM (NC-OFDM), Non-Cooperative Game-Based OFDMA (NC-Game-OFDMA), Energy-Efficient Stackelberg Pairing and Power Allocation (ES-PPA), Radio Access Network Pairing and Power Allocation (RAN-PPA), Orthogonal Multiple Access (OMA), Full-Duplex Non-Orthogonal Multiple Access (F-NOMA), Cognitive Radio Non-Orthogonal Multiple Access (CR-NOMA), and Optimal Power Allocation in Non-Orthogonal Multiple Access (OPA-NOMA) at the cost of low energy efficiency and highly controlled interference to primary users.