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Research Article | Open Access | Download PDF
Volume 13 | Issue 9 | Year 2026 | Article Id. IJECE-V13I9P112 | DOI : https://doi.org/10.14445/23488549/IJECE-V13I9P112

Performance Improvement in QoS Metrics: Implementing Dynamic Power Allocation using Surrogate Optimization in Clustered NOMA for 5G and Beyond 5G Networks

Lekshmi Nair M, Neelakantan PC

Received Revised Accepted Published
05 Jun 2026 12 Aug 2026 19 Aug 2026 29 Sep 2026

Citation :

Lekshmi Nair M, Neelakantan PC, "Performance Improvement in QoS Metrics: Implementing Dynamic Power Allocation using Surrogate Optimization in Clustered NOMA for 5G and Beyond 5G Networks," International Journal of Electronics and Communication Engineering, vol. 13, no. 9, pp. 195-207, 2026. Crossref, https://doi.org/10.14445/23488549/IJECE-V13I9P112

Abstract

This paper proposes a regression-based surrogate optimization framework for dynamic power allocation in downlink clustered Non-Orthogonal Multiple Access systems (NOMA). The inherent non-convexity of the power allocation problem is addressed, and user power coefficients are adaptively optimized using a Karush-Kuhn-Tucker-based closed-form expression. Simulation results demonstrate that dynamic power allocation using the proposed surrogate method significantly reduces outage probability as low as 10-4 at higher transmit power levels. The cluster average data rate is enhanced by approximately 8% over static NOMA and achieves nearly eight times higher performance compared to Orthogonal Multiple Access (OMA). At the individual user level, dynamic power allocation provides a substantial user rate improvement than static power allocation, indicating enhanced fairness and efficient utilization of resources. The simulation results confirm that the proposed surrogate optimization framework effectively transforms the non-convex power allocation problem into a tractable form. This enables adaptive power control that improves SINR, mitigates interference, and maximizes spectral efficiency. Also, the proposed dynamic power allocation strategy offers a robust and scalable solution for enhancing both reliability and throughput, making it suitable for future generations of wireless networks.

Keywords

Cluster, Dynamic power allocation, Karush-Kuhn-Tucker condition, Outage probability. Power Domain NOMA, Surrogate optimization.

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