Hybrid Quantum-Classical Autoencoders for End-to-End Radio Communication

Quantum neural networks are emerging as poten-tial candidates to leverage noisy quantum processing units for applications. Here we introduce hybrid quantum-classical au-to encoders for end-to-end radio communication. In the physical layer of classical wireless systems, we study the performance of si...

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Bibliographic Details

Published in:	2022 IEEE/ACM 7th Symposium on Edge Computing (SEC) pp. 468 - 473
Main Authors:	Tabi, Zsolt, Bako, Bence, Nagy, Daniel T. R., Vaderna, Peter, Kallus, Zsofia, Haga, Peter, Zimboras, Zoltan
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.12.2022
Subjects:	Physical layer quantum autoencoder Quantum computing quantum machine learning radio communication Radio transmitters Receivers Robustness Symbols variational quantum algorithms Wireless communication
Online Access:	Get full text
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