HAPS Assisted Cooperative Offloading for Space–Air–Ground Integrated Networks

Abstract

Mobile edge computing (MEC) has significantly enhanced computational capabilities at the network edge, enabling computation-intensive applications. However, traditional MEC implementations face significant challenges in areas without reliable terrestrial network infrastructure, such as rural regions or disaster-affected zones. To address this, we present a novel MEC-enabled space–air–ground integrated network (SAGIN) framework that combines high-altitude platform station (HAPS) and low Earth orbit (LEO) satellite to ensure comprehensive coverage and reduce execution delays for ground users (GUs) in areas lacking terrestrial infrastructure. By leveraging the complementary capabilities of HAPS, which provide wide-area coverage and reliable connectivity, and LEO satellites, which offer high-throughput communication, the proposed SAGIN framework enhances computation offloading. We propose a cooperative approach between GUs and the LEO satellite via the HAPS to maximize offloaded data while satisfying stringent delay constraints under a partial offloading mode. A nonlinear optimization problem is formulated to minimize execution delay while increasing offloaded data by jointly optimizing task offloading decisions and resource allocation between the HAPS and LEO satellite. Simulation results show that the proposed cooperative offloading scheme significantly outperforms random and non-cooperative schemes considering execution delay. These results highlight that the proposed cooperative, HAPS-assisted SAGIN framework effectively enables low-delay edge computing in infrastructure-limited regions. © 2025 Elsevier GmbH