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Abstract
This paper proposes an application algorithm based on a quantum approximate optimization algorithm (QAOA) for wireless scheduling problems. QAOA is one of the promising hybrid quantum-classical algorithms to solve combinatorial optimization problems and it provides great approximate solutions to non-deterministic polynomial-time (NP) hard problems. QAOA maps the given problem into Hilbert space, and then it generates the Hamiltonian for the given objective and constraint. Then, QAOA finds proper parameters from the classical optimization loop in order to optimize the expectation value of the generated Hamiltonian. Based on the parameters, the optimal solution to the given problem can be obtained from the optimum of the expectation value of the Hamiltonian. Inspired by QAOA, a quantum approximate optimization for scheduling (QAOS) algorithm is proposed. The proposed QAOS designs the Hamiltonian of the wireless scheduling problem which is formulated by the maximum weight independent set (MWIS). The designed Hamiltonian is converted into a unitary operator and implemented as a quantum gate operation. After that, the iterative QAOS sequence solves the wireless scheduling problem. The novelty of QAOS is verified with simulation results implemented via Cirq and TensorFlow-Quantum.
Highlights
Nowadays, quantum computing and communications have received a lot of attention from academia and industry research communities
The proposed quantum approximate optimization for scheduling (QAOS) designs the Hamiltonian of the wireless scheduling problem which is formulated by the maximum weight independent set (MWIS)
Quantum computing-based non-deterministic polynomial-time (NP) hard problem solving is of great interest [1,2,3,4]
Summary
Quantum computing and communications have received a lot of attention from academia and industry research communities. The quantum approximate optimization algorithm (QAOA) is one of the well-known quantum computing-based optimization solvers, and it has been verified that the QAOA outperforms others in many combinatorial problems that are closely related to wireless scheduling problems [5,6,7,8,9]. Due to the fact that the MWIS problem is an NP-hard problem, heuristic algorithms are desired; a QAOA application algorithm, quantum approximate optimization for scheduling (QAOS), is designed to solve MWIS-based wireless scheduling problems. The optimal solution of the MWIS problem can be obtained by the measurement of the expectation value of the problem Hamiltonian on the state generated by optimal parameters. QAOS is a novel attempt to carry out application research on wireless communication via QAOA.
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