The Divided-QUBO-Based Quantum Algorithm for Optimal Wireless Link Scheduling

Abstract

Link scheduling in wireless communication aims to minimize interference and maximize channel utilization. When accurate channel state information (CSI) is available, optimal scheduling can be achieved by modeling link interference as a conflict graph and solving the weighted maximum independent set problem (WMIS). However, the NP-hard nature of WMIS presents significant computational challenges in obtaining high-quality solutions efficiently. To tackle this challenge, we first propose a divided QUBO model, which formulates the original problem into sub-models within non-overlapping subspaces. Building upon this, we then develop a corresponding algorithm called DQAOA, which further narrows the search space within solution bounds established by classical greedy algorithms and semi-definite programming. Using a specialized mixing operator (the XY-mixer), the algorithm confines the evolution to each reduced subspace and runs in parallel. Additionally, an auxiliary Hamiltonian inspired by counter-diabatic driving is introduced into the core evolution equation to accelerate convergence. The experimental results on the IBM Qiskit platform demonstrate that DQAOA outperforms classical methods and other QAOA variants, providing an efficient and reliable solution for optimal link scheduling in wireless networks.