AI-based 6G Space-Air-Ground Integrated Network Resource Allocation Algorithm

A two-stage intelligent optimization algorithm for 6G space-air-ground integrated network resource configuration is proposed. The configuration process is divided into two stages: short-term stage and long-term stage. In the short-term stage, an approximate solution and a low-complexity solution are proposed to solve the problem of association and power allocation. In the approximate solution, a binary linear optimization problem is constructed and solved to find the optimal association, and then the power allocation is optimized using Taylor expansion approximation. In the latter solution, a low-complexity method based on frequency segmentation technology is proposed to solve the problem of association and power allocation. On the other hand, in the long-term stage, an efficient algorithm based on recursive shrinkage and reordering process is proposed to optimize the positions of airborne mobile base stations and the intelligent collaborative optimization of air and ground. Finally, simulation experiments are conducted to verify the effectiveness and superiority of the algorithm.