Abstract: The massive amount of heterogeneous data generated by the widespread use of mobile devices has placed higher demands on data communication networks.In this context,the sixth-generation(6G) mobile network is expected to meet the needs of various mobile devices executing computation-intensive and latency-sensitive mobile applications.Currently,the novel Space-Air-Ground Integrated Network(SAGIN),which results from the organic combination of network components in space,air,and ground,has become a key component of the 6G architecture.Compared with traditional terrestrial communication paradigms,SAGIN can effectively enhance the coverage and throughput of mobile communication networks by utilizing non-terrestrial network components such as satellites,high-altitude platforms,and UAVs.This makes it well-suited to meet the needs of a large number of mobile devices in infrastructure-less areas.Despite the significant potential of SAGIN in various aspects for infrastructure-less regions,its application still faces practical challenges such as resource constraints,dynamic changes in network topology,and service requirements of mobile devices.To address these challenges,this paper considers the impact of user mobility on system energy efficiency under real-world scenarios,and investigates a joint optimization problem of computation offloading and UAV trajectory in SAGIN.To solve the targeted joint optimization problem,an efficient and novel algorithm based on convex optimization techniques is designed,decoupling the target problem into two sub-problems.These sub-problems are solved separately using the SCA and the Dinkelbach method,to obtain an approximate optimal solution to the target optimization problem.Numerical simulation results demonstrate that the proposed algorithm outperforms other benchmark algorithms in terms of performance.

Key words: Space-Air-Ground Integrated Network, UAV trajectory, Computation offloading, User mobility