Quantum-Classical Autoencoder Architectures for End-to-End Radio Communication

Quantum-Classical Autoencoder Architectures for End-to-End Radio Communication

End-to-end radio communication needs to be optimized against noisy channel conditions and other distortion effects. This paper presents a novel concept, a set of hybrid quantum-classical autoencoder architectures with a comprehensive feasibility study using standard encoded radio signals, to evaluat...

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Bibliographic Details
Main Authors: Zsolt I. Tabi, Bence Bako, Daniel T. R. Nagy, Peter Vaderna, Zsofia Kallus, Peter Haga, Zoltan Zimboras
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Quantum machine learning
quantum autoencoder
radio communication
Online Access:https://ieeexplore.ieee.org/document/10981758/
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https://ieeexplore.ieee.org/document/10981758/

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