SummaryThe solution of resource allocation is based on NOMA and OMA structures that are suboptimal to satisfy the demanding QoS and higher data rate requirements compared to EE requirements in 5G cellular networks. In this work, the resource allocation problem in the hybrid MC‐NOMA system is solved. The system achieves the trade‐off between spectral and energy efficiency (EE) with the lowest rate of user requirements. The system's resource allocation, including power allocation, is considered the crucial factor and is identified as a single‐objective problem. The suggested work focuses on user pairing and allocation on paired users following processing. The user grouping is designed to connect near‐ and far‐users with high C3 to increase the fairness of NOMA. As a result, this work considers multiple goals, such as C3 maximization, spectrum efficiency, and energy efficiency. This paper aims to present a novel hybrid optimization model with the combination of coati and bald eagle optimization algorithms, to solve the defined optimization problem. The experimental results show that the suggested system outperforms the conventional algorithms by evaluating different performance measures such as channel correlation, spectrum efficiency, energy efficiency, and power allocation.

中文翻译：

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配对用户中的资源分配：优化辅助用户分组以提高 NOMA 的公平性

摘要资源分配解决方案基于 NOMA 和 OMA 结构，与 5G 蜂窝网络中的 EE 要求相比，这些结构无法满足苛刻的 QoS 和更高的数据速率要求。在这项工作中，解决了混合MC-NOMA系统中的资源分配问题。该系统以最低的用户需求率实现了频谱和能源效率（EE）之间的权衡。系统的资源分配，包括功率分配，被认为是关键因素，并被确定为单目标问题。建议的工作重点是用户配对以及处理后配对用户的分配。用户分组旨在连接具有高 C3 的近端和远端用户，以增加 NOMA 的公平性。因此，这项工作考虑了多个目标，例如 C3 最大化、频谱效率和能源效率。本文旨在提出一种结合浣熊优化算法和秃头鹰优化算法的新型混合优化模型，以解决定义的优化问题。实验结果表明，通过评估信道相关性、频谱效率、能源效率和功率分配等不同性能指标，所提出的系统优于传统算法。