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Updated: Oct 4, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
Published on: September 8, 2023
Online machine learning algorithms to optimize performances of complex wireless communication systems
Koji Oshima1,2, Daisuke Yamamoto2, Atsuhiro Yumoto2
1Innovation Design Initiative, National Institute of Information and Communications Technology, Koganei, Tokyo, Japan.
Abstract:
Data-driven and feedback cycle-based approaches are necessary to optimize the performance of modern complex wireless communication systems. Machine learning technologies can provide solutions for these requirements. This study shows a comprehensive framework of optimizing wireless communication systems and proposes two optimal decision schemes that have not been well-investigated in existing research. The first one is supervised learning modeling and optimal decision making by optimization, and the second is a simple and implementable reinforcement learning algorithm. The proposed schemes were verified through real-world experiments and computer simulations, which revealed the necessity and validity of this research.
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