Joint Data Collection and Transmission in 6G Aerial Access Networks

The aerial access network (AAN) is a significant issue in the sixth generation (6G) technologies. In this work, we focus on the terrestrial data collection and transmission by AAN. In detail, high altitude platforms (HAPs) are considered as the aerial access devices and low earth orbit (LEO) satellites assist the data collected by HAPs to complete transmission. To deal with the intractable dynamic topology of AAN, the time expanding graph (TEG) is employed to represent the multiple resources and depict the data flow transmission process. Based on TEG, we aim to maximize the total data received at the ground data processing center, considering the multiple resource restrictions of HAPs and LEO satellites, as well as the flow conservation constraints in TEG. The problem is in the form of mixed integer programming, and it is intractable to obtain the optimal solution, especially in large-scale AAN. To alleviate the intractability, we propose the Benders decomposition based algorithm to obtain the optimal solution within an acceptable time complexity. Simulations are conducted and numerical results verify the effectiveness and efficiency of the proposed algorithm.