Dynamic channel selection in wireless communications via a multi-armed bandit algorithm using laser chaos time series
Shungo Takeuchi, Mikio Hasegawa, Kazutaka Kanno, Atsushi Uchida,, Nicolas Chauvet, Makoto Naruse

TL;DR
This paper demonstrates the use of laser chaos time series in a multi-armed bandit algorithm for dynamic channel selection in WLANs, showing ultrafast decision-making and improved communication quality in changing environments.
Contribution
It introduces a novel application of laser chaos time series in a MAB algorithm for wireless channel selection, validated through experimental WLAN tests.
Findings
Successful experimental implementation in IEEE802.11a WLAN
Ultrafast chaotic sequences enhance real-time channel decision-making
Simplified MAB algorithm effectively adapts to dynamic environments
Abstract
Dynamic channel selection is among the most important wireless communication elements in dynamically changing electromagnetic environments wherein a user can experience improved communication quality by choosing a better channel. Multi-armed bandit (MAB) algorithms are a promising approach by which the difficult tradeoff between exploration to search for better a channel and exploitation to experience enhanced communication quality is resolved. Ultrafast solution of MAB problems has been demonstrated by utilizing chaotically oscillating time series generated by semiconductor lasers. In this study, we experimentally demonstrate a MAB algorithm incorporating laser chaos time series in a wireless local area network (WLAN). Autonomous and adaptive dynamic channel selection is successfully demonstrated in an IEEE802.11a-based, four-channel WLAN. Although the laser chaos time series is…
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