Variational Quantum Eigensolver for Optimizing Network Scheduling Using QUBO Formulation

A wireless multihop network is characterized by nodes capable of direct communication or extending their reach beyond the transmission range by employing other nodes as relays. The significance of multihop networks is underscored by their advantages, including expanded coverage, reduced interference, increased spectrum reuse, and lower energy consumption. These networks find applications in wireless sensor networks, Internet of Things (IoT), and ad-hoc networks, among others. Effective operation of these networks relies on scheduling, where a subset of nodes is activated for specific durations while the rest remain inactive. This scheduling challenge falls within the domain of combinatorial optimization problems, which can be NP-hard for large-scale scenarios on classical computers. Quantum computers can offer a potential solution by transforming such problems into Quadratic Unconstrained Binary Optimization (QUBO) problems, presenting a possible speedup in certain instances or with scaling. This paper demonstrates how to formulate the multihop wireless network scheduling problem as a QUBO problem and solve it on a quantum computer using variational quantum eigensolver (VQE). The aim is to explore the practical application of quantum computing in the noisy intermediate-scale quantum (NISQ) era and assess potential benefits in real-world scenarios.