Automating Antenna Scheduling Problems Using Quantum Computing and Deep Reinforcement Learning

Wilson, Brian; Goh, Edwin; Guillaume, Alex; Alimo, Ryan; Claudet, Thomas; Venkataram, Hamsa Shwetha

doi:10.1109/igarss46834.2022.9884342

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium 2022

DOI: 10.1109/igarss46834.2022.9884342

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Automating Antenna Scheduling Problems Using Quantum Computing and Deep Reinforcement Learning

Brian Wilson

Edwin Goh

Alex Guillaume

et al.

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2024

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Quantum-compliant users scheduling optimization in joint transmission mobile access networks

Volpe,

Cirillo,

Fantini

et al. 2024

Quantum Inf Process

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Joint Transmission (JT) is the dynamic coordination of transmission and/or reception at multiple geographically separated sites to improve end-user service quality. When user equipment receives signals from multiple sites, downstream performance improves. An optimization problem arises in selecting the best user subset for JT within a multiple-input–multiple-output (MIMO) system. Unfortunately, a pure brute-force approach is not feasible due to exponential time growth with user combinations, unsuitable for real-time selection in mobile networks with users continuously changing in time. This article proposes quantum-compliant heuristics using quadratic unconstrained binary optimization (QUBO) for JT user scheduling. QUBO handles initial user selection, followed by brute-force exploration for the solution. Numerical results indicate that quantum-compliant methods decrease solution time without substantial accuracy loss compared to brute-force methods.

show abstract

Quantum-compliant users scheduling optimization in joint transmission mobile access networks

Volpe,

Cirillo,

Fantini

et al. 2024

Quantum Inf Process

View full text Add to dashboard Cite

show abstract

Evaluating the practicality of quantum optimization algorithms for prototypical industrial applications

Vandelli,

Lignarolo,

Cavazzoni

et al. 2024

Quantum Inf Process

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Automating Antenna Scheduling Problems Using Quantum Computing and Deep Reinforcement Learning

Cited by 2 publications

References 2 publications

Quantum-compliant users scheduling optimization in joint transmission mobile access networks

Quantum-compliant users scheduling optimization in joint transmission mobile access networks

Evaluating the practicality of quantum optimization algorithms for prototypical industrial applications

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