Potential and Pitfalls of Multi-Armed Bandits for Decentralized Spatial Reuse in WLANs

Abstract

Spatial Reuse (SR) has recently gained attention to maximize the performance of IEEE 802.11 Wireless Local Area Networks (WLANs). Decentralized mechanisms are expected to be key in the development of SR solutions for next-generation WLANs, since many deployments are characterized by being uncoordinated by nature. However, the potential of decentralized mechanisms is limited by the significant lack of knowledge with respect to the overall wireless environment. To shed some light on this subject, we show the main considerations and possibilities of applying online learning to address the SR problem in uncoordinated WLANs. In particular, we provide a solution based on Multi-Armed Bandits (MABs) whereby independent WLANs dynamically adjust their frequency channel, transmit power and sensitivity threshold. To that purpose, we provide two different strategies, which refer to selfish and environment-aware learning. While the former stands for pure individual behavior, the second one considers the performance experienced by surrounding networks, thus taking into account the impact of individual actions on the environment. Through these two strategies we delve into practical issues of applying MABs in wireless networks, such as convergence guarantees or adversarial effects. Our simulation results illustrate the potential of the proposed solutions for enabling SR in future WLANs. We show that substantial improvements on network performance can be achieved regarding throughput and fairness.

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• Distributed Learning in Multi-Armed Bandit with Multiple Players
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Cited by in corpus (7)

• Wi-Fi Meets ML: A Survey on Improving IEEE 802.11 Performance with Machine Learning
• Potential and Pitfalls of Multi-Armed Bandits for Decentralized Spatial Reuse in WLANs
• IEEE 802.11bn Multi-AP Coordinated Spatial Reuse with Hierarchical Multi-Armed Bandits
• Multi-Armed Bandits for Decentralized AP selection in Enterprise WLANs
• The TMB path loss model for 5 GHz indoor WiFi scenarios: On the empirical relationship between RSSI, MCS, and spatial streams
• Komondor: a Wireless Network Simulator for Next-Generation High-Density WLANs
• Evolution of Small Cell from 4G to 6G: Past, Present, and Future