Priority-Aware Layered Offloading in Cooperative UAV-MEC Networks via SPC-NOMA

UAV-based Multi-Access Edge Computing (MEC) systems are vital solutions in disaster scenarios by providing temporary radio and processing resources to rescue teams and survivors. However, recent schemes in the literature typically treat offloaded tasks as one indivisible units and fail to account for heterogeneous reliability requirements, leading to non-optimal resource utilization and performance deterioration under such emergency conditions. Moreover, the joint optimization of communication, computation, and UAV path planning in cooperative setup remains inadequately addressed. This paper proposes a priority-aware layered task offloading framework for cooperative UAV-MEC networks based on Superposition Coding (SPC) and non-orthogonal access. The proposed design separates tasks into reliability-critical base-layer (BL) and enhancement-layer (EL) components, to assure reliable and timely transmission and execution. BL data is prioritized via intra- and inter-user constraints, while EL data is adaptively processed locally or offloaded via a cooperative UAVs. A joint latency minimization problem is formulated and tackled using an alternating optimization framework with successive convex approximation (AO-SCA). Simulation results demonstrate that the proposed scheme significantly outperforms baseline methods. For 20 users, it achieves a processing efficiency of 92.3%, compared to over 83% for baseline schemes. As the number of users increases to 120, the proposed method maintains superior efficiency at 63.1%, outperforming NC-SPC (40.3%), FT-Coop (51.3%), SL-NOMA (52.4%), and L-OMA (45.3%), highlighting its robustness and scalability in meeting reliability and low-latency requirements in post-disaster scenarios.