Energy-Efficient UAV Edge Computing for Space-Air-Ground Integrated Networks

The space-air-ground integrated network (SAGIN) reveals enormous potential towards ubiquitous access with pros-perous applications for future 6G wireless networks, yet the limited energy presents a significant challenge towards the efficient operation of SAGIN. In this paper, we propose to employ an un-manned aerial vehicle (UAV) to approach the ground nodes to help alleviate the computation burden, where the computed results are then forwarded to the satellite for remote use. We formulate the problem to minimize the weighted energy consumption in terms of data offloading, computation, and results forwarding, along with the UAV propulsion energy, while jointly investigating the transmissions, scheduling, computation, and trajectory strategy design. The problem is then decomposed and solved in a block coordinate descent framework. Simulation results demonstrate that the proposed joint optimization scheme effectively reduces the overall energy consumption compared to benchmark approaches.