2020/04/14 by Jaeho Choi, Choi, Jaeho, Seunghyeok Oh +3
Computer Science · Engineering · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Physical sciences #Low-power high-performance VLSI design #Other Computer Science (cs.OH) #Quantum Computing Algorithms and Architecture #Quantum Physics (quant-ph) #Quantum-Dot Cellular Automata #cs.OH #quant-ph
paper · pdf · doi:10.48550/arxiv.2004.11229
openalex publication_date 2020/04/14 · arxiv created 2020/09/04 · arxiv updated 2020/09/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper proposes a quantum approximate optimization algorithm (QAOA) method for wireless scheduling problems. The QAOA is one of the promising hybrid quantum-classical algorithms for many applications and it provides highly accurate optimization solutions in NP-hard problems. QAOA maps the given problems into Hilbert spaces, and then it generates Hamiltonian for the given objectives and constraints. Then, QAOA finds proper parameters from classical optimization approaches in order to optimize the expectation value of generated Hamiltonian. Based on the parameters, the optimal solution to the given problem can be obtained from the optimum of the expectation value of Hamiltonian. Inspired by QAOA, a quantum approximate optimization for scheduling (QAOS) algorithm is proposed. First of all, this paper formulates a wireless scheduling problem using maximum weight independent set (MWIS). Then, for the given MWIS, the proposed QAOS designs the Hamiltonian of the problem. After that, the iterative QAOS sequence solves the wireless scheduling problem. This paper verifies the novelty of the proposed QAOS via simulations implemented by Cirq and TensorFlow-Quantum.