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 arranged prior to the WLAN experiments, the results confirm the usefulness of ultrafast chaotic sequences for real wireless applications. In addition, we numerically examine the underlining adaptation mechanism of the significantly simplified MAB algorithm implemented in the present study compared with the previously reported chaos-based decision makers. This study provides a first step toward the application of ultrafast chaotic lasers for future high-performance wireless communication networks. IntroductionThe resources for wireless communications are physically limited because of their narrow frequency bandwidth and ever-increasing demands in society [1]. Therefore, dynamic channel selection is among the most important wireless communication elements in dynamically changing electromagnetic environments such that a user can experience improved communication quality by choosing a better channel in terms of, for instance, the communication throughput [2]. The metric could also be minimizing energy consumption, communication delay, etc., depending on the interest of a given system. Autonomous and prompt adaptation is important to the dynamically changing wireless communication environments.Lai et al. modelled the channel selection problem as a multi-armed bandit (MAB) problem [3]; an example of a MAB problem is finding the most highly profitable slot machine among many machines. To find the best machine, one must conduct exploration to search for the high reward machine. However, too much exploration may accompany significant losses whereas a too quick decision may result in missing the best choice. Hence, a difficult tradeoff exists, which is referred to as an exploration-exploitation dilemma [4]. A channel selection problem in wireless networks can be regarded as a MAB problem by associating the communication quality (such as the throughput) to the reward of a slot machine. Recently, Kuroda et al. applied a Tug-of-War algorithm [5] for MAB problems to a wireless local area network (WLAN) to demonstrate its effectiveness [6]. In a wider context, Obayuiwana et al. reviewed network selection problems using a decision-making algorithm [7]. M...

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High-bandwidth irregular oscillations caused by optical time-delayed feedback subjected to the laser cavity, known as laser chaos, have been investigated for various engineering applications. Recently, a fast decision-making algorithm for a multi-arm bandit problem by utilizing laser chaos time series has been demonstrated. Furthermore, the arms order recognition of the reward expectation for each arm has been successfully developed by incorporating the notion of the confidence interval regarding the reward estimate. However, in previous studies, the verification was limited to numerical experiments; real-world demonstrations were not conducted. This study experimentally demonstrated that the arm-order recognition algorithm is successfully operated in channel order recognition in wireless communications while revising the original strategy to take into account the wireless application requirements. Such accurate arm rank recognition involving non-best arms would be useful for various real-world applications such as channel bonding, among others.