Quantum-Assisted Resource Management for Data Access in Space-Air-Ground Integrated Networks

Xinliang Wei, Jiyao Liu, Lei Fan, Yuanxiong Guo, Yanmin Gong, Zhu Han, Yu Wang

Abstract: Space-air-ground integrated networks can provide better connectivity and improved performance to ground users and thus have been well-recognized as the innovative trend for future 6G and beyond wireless systems. However, such heterogeneous and complex integrated communication systems also pose many new challenges for joint performance optimization. In this paper, we study the data delivery optimization problem in a space-air-ground network, where joint resource management decisions on user association, bandwidth allocation, cache placement, and high-altitude platform (HAP) location selection have to be optimized. To tackle this complex and challenging mixed integer programming optimization problem, we introduce a quantum-assisted method, named the Hybrid quantum-classical Benders’ Decomposition (HyBD) algorithm, which leverages the strengths of both quantum and classical computing. Experiments on the commercial quantum annealing machine demonstrate the effectiveness and robustness of the proposed HyBD method, with up to 64.3% improvement of iteration number and 82.8% improvement of average computation time over the classical Benders’ Decomposition algorithm on classical CPUs even at small scales, which demonstrates the quantum advantage.

External IDs:dblp:journals/twc/WeiLFGGHW26