Non-orthogonal multiple access (NOMA) with power domain multiplexing and successive interference cancellation (SIC) is one of the promising technologies for future wireless communication. The performance of NOMA is highly dependent on resource allocation such as power allocation and channel assignment. In this paper, we investigate the power allocation (PA) scheme, to optimize the weighted maximin fairness (MMF) for 2-user and 3-user clusters. We utilize the particle swarm optimization (PSO) based algorithm for power allocation due to its promising behavior. Application area of NOMA is becoming broader, then, we considered a cellular network, assisted by an unmanned aerial vehicle (UAV) as the base station (BS) which is integrated with the NOMA system. The PA for weighted MMF problem in NOMA is non-convex, it is difficult to find out the optimal solution directly. Simulation results show the performance of PSO-based algorithm in different adaptive weights and its convergence characteristics. We have also shown that the rate and fairness tradeoff using weighted maximin fairness. Numerical results compare the performance of NOMA and orthogonal multiple access (OMA) and prove the significance of the proposed algorithm.

具有功率域复用和连续干扰消除（SIC）的非正交多址（NOMA）是未来无线通信的有前途的技术之一。NOMA的性能高度依赖于资源分配，例如功率分配和信道分配。在本文中，我们研究了功率分配（PA）方案，以优化2用户和3用户群集的加权最大最大化公平性（MMF）。由于其有希望的行为，我们利用基于粒子群优化（PSO）的算法进行功率分配。NOMA的应用领域越来越广泛，因此，我们考虑了一个蜂窝网络，并以无人驾驶飞机（UAV）作为与NOMA系统集成的基站（BS）作为辅助。NOMA中加权MMF问题的PA是非凸的，很难直接找到最佳解决方案。仿真结果表明了基于PSO算法在不同自适应权重下的性能及其收敛特性。我们还显示了使用加权极大值公平性进行费率和公平性的权衡。数值结果比较了NOMA和正交多址（OMA）的性能，并证明了该算法的重要性。