A Sequential WLAN Channel Selection Adaptive to Factors Outside the System

We propose a sequential channel allocation method based on the multi-objective multi-armed bandit (MOMAB) problem to identify the best channel set among model-based solutions. A solution obtained from pre-designed objective functions cannot always be the best channel set due to external factors in the wireless environment. It is difficult to take into account external factors in advance, so we propose to allocate channels based on several performance metrics that can only be measured by operating access points. The fine-tuning during actual operation involves a trade-off between exploration and exploitation for the best channel set. In addition, we should utilize a channel set that performs not so good on some metrics but well on other metrics. By using MOMAB, we can balance between exploration and exploitation of Pareto optimal channel sets for multiple metrics. The experimental results demonstrate that the proposed method successfully identifies a Pareto optimal channel set.