Enhancing downlink NOMA performance: A pareto optimization approach for superior power allocation

This paper proposes a novel Pareto-Optimization Algorithm (POA) for dynamic power allocation in downlink Non-Orthogonal Multiple Access (NOMA) systems operating within heterogeneous network environments. The proposed POA framework effectively addresses the critical trade-off between spectral efficiency and user fairness by integrating adaptive modulation schemes (BPSK, QPSK, 16-QAM, 64-QAM) with demand-aware resource categorisation based on Signal-to-Noise-plus-Interference Ratios (SNIR) and User Equipment (UE) requirements. The optimisation process utilises Lagrange multipliers and Karush-Kuhn-Tucker (KKT) conditions to ensure fair and optimal power allocation under total power constraints. Extensive simulation results demonstrate that the proposed POA achieves substantial performance improvements, attaining a 92% fairness index (versus 71% for Water Filling), a spectral efficiency of 5.3 bps/Hz, and a peak data rate of 390 Mbps. A comparative analysis against existing schemes, including Fixed Power Allocation (FPA), Fractional Transmit Power Allocation (FTPA), Water Filling Algorithm (WFA), and Particle Swarm Optimisation Algorithm (PSOA), confirms the superiority of POA in enhancing fairness-efficiency trade-offs. These results highlight the POA's suitability for dynamic, heterogeneous 5 G and beyond wireless networks, offering improved scalability and real-time adaptability under diverse channel and traffic conditions.