Improving throughput using multi-armed bandit algorithm for wireless LANs

Recently, various mobile communication systems have been widely deployed, and mobile traffic is increasing. However, the bandwidth available for mobile communications is limited, hence the scarcity of radio resources in mobile communications is a serious problem. As an approach to solve this problem, cognitive wireless communication models have been proposed. These model search for vacant time slots in multi-channel wireless communication systems. Although previous studies have shown that frequency utilization efficiency can be improved by multi-armed bandit algorithms, channels are assumed to be independent. However, channels used in 2.4 GHz wireless LANs (such as IEEE802.11b or IEEE802.11g) are not independent because these channels overlap with adjacent channels. In this paper, we propose an extended multi-armed bandit algorithm that uses continuous-valued rewards, which is applicable to wireless communication systems with overlapping channels. We show the effectiveness of the proposed method by experimental demonstrations.