Energy-Efficient Uplink Communication in UAV-Enabled MEC Networks with Pinching Antennas

Unmanned aerial vehicle (UAV)-enabled multi-access edge computing (MEC) is a transformative paradigm that delivers ubiquitous communication and computing services for next-generation wireless networks. By incorporating a reconfigurable pinching antenna (PA) system, this paper proposes a novel framework to enhance energy efficiency in UAV-aided uplink communication, effectively addressing mobility-related challenges such as line-of-sight (LoS) propagation, Doppler effects, and stringent energy constraints. The framework jointly optimizes UAV trajectories, task offloading ratios, transmit powers, and PA positions to minimize total energy consumption while ensuring reliable data rates, collision avoidance, and comprehensive coverage of ground target points. A mixed-integer non-linear program is formulated, which is efficiently solved using a block coordinate descent (BCD) algorithm combined with successive convex approximation (SCA) and one-dimensional grid search. The simulation results demonstrate that the proposed approach reduces energy consumption by 20–45% compared to baseline methods while maintaining robust communication performance and near-perfect coverage across diverse system configurations.