Quantum-Assisted Joint Caching and Power Allocation for Integrated Satellite-Terrestrial Networks

LowEarth orbit (LEO) satellite network can complement terrestrial networks for achieving global wireless coverage and improving delay-sensitive Internet services. This paper proposes an integrated satellite-terrestrial network (ISTN) architecture to provide ground users with seamless and reliable content delivery services. For optimal service provisioning in this architecture, we formulate an optimization model to maximize the network throughput by jointly optimizing content delivery policy, cache placement, and transmission power allocation. The resulting optimization model is a large-scale mixed-integer nonlinear program (MINLP) that is intractable for classical computer solvers. Inspired by quantum computing techniques, we propose a hybrid quantum-classical generalized Benders' decomposition (HQCGBD) algorithm to address this challenge. Specifically, we first exploit the generalized Benders' decomposition (GBD) to decompose the problem into a master problem and a subproblem and then leverage the state-of-the-art quantum annealer to solve the challenging master problem. Furthermore, a multi-cut strategy is designed in HQCGBD to accelerate the solution process by leveraging the quantum advantages in parallel computing. Simulation results demonstrate the superiority of the proposed HQCGBD algorithm and validate the effectiveness of the proposed cache-enabled ISTN architecture.