• Corpus ID: 67855738

Decentralized AP selection using Multi-Armed Bandits: Opportunistic {\epsilon}-Greedy with Stickiness

@article{Carrascosa2019DecentralizedAS,
  title={Decentralized AP selection using Multi-Armed Bandits: Opportunistic \{\epsilon\}-Greedy with Stickiness},
  author={Marc Carrascosa and Boris Bellalta},
  journal={arXiv: Networking and Internet Architecture},
  year={2019}
}
WiFi densification leads to the existence of multiple overlapping coverage areas, which allows user stations (STAs) to choose between different Access Points (APs). The standard WiFi association method makes the STAs select the AP with the strongest signal, which in many cases leads to underutilization of some APs while overcrowding others. To mitigate this situation, Reinforcement Learning techniques such as Multi-Armed Bandits can be used to dynamically learn the optimal mapping between APs… 

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