Joint subcarrier assignment and power allocation for UAV-assisted full-duplex NOMA emergency communication networks

In the context of future 6G networks, the integration of non-orthogonal multiple access (NOMA) with unmanned aerial vehicles (UAVs) is proposed to significantly enhance high-speed and reliable communication capabilities in emergency scenarios. This study addresses the challenge of maximizing the total sum rate for both downlinks and uplinks in multi-UAV Full-Duplex NOMA emergency networks through the joint optimization of subcarrier scheduling and power allocation. The inherent complexity of this problem arises from the nonconvex nature of the objective function, interdependence of product terms, and combinatorial characteristics of the decision variables. To overcome these challenges, we employ the Big-M method to decouple the product terms, relax the combinatorial subcarrier assignment into continuous variables, and introduce a ℓp-norm-based penalty term in the objective function to penalize nonbinary subcarrier assignments. Although these transformations simplify the problem, it remains nonconvex. To address this challenge, we propose an iterative refinement method with threshold-based rounding (IRM-TR) algorithm. The IRM-TR algorithm iteratively refines subcarrier assignments and power allocation by combining successive convex approximations with a dynamically updating weight tensor of the ℓpnorm to drive the subcarrier assignments toward binary values. A post-convergence threshold-based rounding step is also applied to ensure binary subcarrier assignments. The simulation results validate the proposed approach, demonstrating its effectiveness and efficiency in enhancing communication performance under emergency conditions.