Beamforming optimization via quantum algorithms using Variational Quantum Eigensolver and Quantum Approximate Optimization Algorithm

This study investigates the application of quantum algorithms, specifically the Variational Quantum Eigensolver (VQE) and the Quantum Approximate Optimization Algorithm (QAOA), to design optimal sensor configurations for beamforming, enhancing signal quality and overall system performance. We propos...

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Bibliographic Details
Published in:IET quantum communication Vol. 6; no. 1
Main Authors: Dhara, Bidisha, Agrawal, Monika, Dutta Roy, Sumantra
Format: Journal Article
Language:English
Published: Shenzhen John Wiley & Sons, Inc 01.01.2025
Subjects:
Algorithms
Arrays
Beamforming
Configuration management
Design optimization
Lagrange multiplier
Maximization
Optimization algorithms
Sensors
Signal processing
Signal quality
ISSN:2632-8925, 2632-8925
Online Access:Get full text
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Summary:This study investigates the application of quantum algorithms, specifically the Variational Quantum Eigensolver (VQE) and the Quantum Approximate Optimization Algorithm (QAOA), to design optimal sensor configurations for beamforming, enhancing signal quality and overall system performance. We propose two distinct optimization formulations: one aimed at maximising array gain while the other aimed at maximising signal‐to‐noise‐interference ratio (SINR). Our findings show that the outputs obtained from quantum algorithms are consistent with those derived from classical methods.
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ISSN:2632-8925
2632-8925
DOI:10.1049/qtc2.12120