Optimizing downlink of CR-NOMA resource allocation: A fairness index approach to balancing system performance and energy efficiency

This study addresses the challenge of optimizing resource allocation in downlink Non-Orthogonal Multiple Access (NOMA) systems within small-cell networks, focusing on balancing user fairness, energy efficiency, and system performance. Conventional methods often result in unequal resource distribution, causing disparities in user data rates and inefficient energy use. To address these limitations, we propose the Fairness Index Average Rate (FIAR) algorithm, an iterative power allocation technique that maximizes network sum rate while meeting minimum user Signal-to-Interference-plus-Noise Ratio (SINR) constraints. By incorporating a fairness index, FIAR ensures equitable data rate distribution, mitigating resource allocation disparities. Simulations demonstrate that FIAR improves energy efficiency by up to 8% compared to state-of-the-art techniques, highlighting its ability to enhance fairness and system performance. The algorithm dynamically adapts to varying user loads and channel conditions, ensuring robust operation in heterogeneous environments. This work underscores NOMA's potential for sustainable and fair resource distribution, paving the way for efficient wireless networks. FIAR represents a significant advancement in next-generation communication systems, offering a practical solution to fairness and energy efficiency challenges in densely populated small-cell networks