Ahmad Sajed, Zain Ul Abideen Syed, Kamal Mian Muhammad, Al-Khasawneh M A, Issa Ghassan F, Ullah Najib, Alfarraj Osama, Tolba Amr, Sheraz Muhammad, Chuah Teong Chee
College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen, 518060, China.
School of Electronic and Communication Engineering, Quanzhou University of Information Engineering, Quanzhou, 362000, People's Republic of China.
Sci Rep. 2025 Jul 2;15(1):23585. doi: 10.1038/s41598-025-09459-0.
The communication network of Unmanned Aerial Drones (UAD) is expected to become a vital element in the development of next-generation wireless networks, offering flexible infrastructure that extends network coverage to remote or disaster-stricken locations while enhancing capacity during critical events and large-scale emergencies. As UAD technology evolves, its role in ensuring consistent, widespread connectivity becomes more essential, though it faces challenges such as high latency, low spectral efficiency, and fairness issues across multiple drones. This research presents an optimization framework designed for multi-UAD communication networks based on Non-Orthogonal Multiple Access (NOMA) to address these difficulties. The framework focuses on optimizing ground user-to-UAD associations and drone power allocation to maximize spectral efficiency. The primary optimization problem is a mixed-integer, nonconvex, and nonlinear task, which seeks to maximize the sum-rate while addressing issues of UAD-user association and power distribution, complicated by interference and binary decision variables. To manage this complexity, we first optimize UAD-user associations under fixed NOMA power allocation and then optimize the power allocation for each NOMA-enabled ground user connected to the drones. Our numerical results show that this framework provides better performance than traditional orthogonal multiple access (OMA)-based optimization methods and other benchmark NOMA-based techniques, offering improved spectral efficiency, lower complexity, and faster convergence, making it an effective solution for enhancing UAD network performance across a range of dynamic scenarios.
无人空中无人机（UAD）的通信网络有望成为下一代无线网络发展的关键要素，提供灵活的基础设施，将网络覆盖范围扩展到偏远或受灾地区，同时在关键事件和大规模紧急情况下提高容量。随着UAD技术的发展，其在确保一致、广泛连接方面的作用变得更加重要，尽管它面临着诸如高延迟、低频谱效率以及多架无人机之间的公平性问题等挑战。本研究提出了一种基于非正交多址接入（NOMA）的多UAD通信网络优化框架，以解决这些难题。该框架专注于优化地面用户与UAD之间的关联以及无人机的功率分配，以最大化频谱效率。主要的优化问题是一个混合整数、非凸且非线性的任务，它旨在在解决UAD与用户关联和功率分配问题的同时最大化总和速率，而这些问题因干扰和二元决策变量而变得复杂。为了应对这种复杂性，我们首先在固定的NOMA功率分配下优化UAD与用户的关联，然后为连接到无人机的每个支持NOMA的地面用户优化功率分配。我们的数值结果表明，该框架比传统的基于正交多址接入（OMA）的优化方法和其他基于NOMA基准技术具有更好的性能，提供了更高的频谱效率、更低的复杂度和更快的收敛速度，使其成为在一系列动态场景中增强UAD网络性能的有效解决方案。
