Resource management for multi-drone communications in next-generation NOMA-enabled wireless networks

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.