Improving Spatial Reuse of Wireless LANs Using Contextual Bandits

Spatial reuse is an important factor in building highly efficient wireless local area networks. The key to maximizing spatial reuse is to support concurrent transmissions while avoiding packet losses due to interference. However, the current medium access control uses a conservative approach that di...

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Veröffentlicht in:IEEE transactions on wireless communications 2024-07, Vol.23 (7), p.6735-6749
Hauptverfasser: Kim, Hyerin, Na, Gwanwoo, Im, Heeseon, So, Jungmin
Format: Artikel
Sprache:eng
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Zusammenfassung:Spatial reuse is an important factor in building highly efficient wireless local area networks. The key to maximizing spatial reuse is to support concurrent transmissions while avoiding packet losses due to interference. However, the current medium access control uses a conservative approach that discourages concurrent transmissions, and the recently introduced spatial reuse operation leads to a lot of packet collisions. This paper proposes two methods, CB-DCF (Contextual Bandit - Distributed Coordination Function) and CB-OBSS/PD (Contextual Bandit - Overlapping Basic Service Set / Preamble Detection), that can improve throughput and fairness of the network. In the proposed methods, nodes run contextual bandit agents that learn to transmit or defer under given states. In CB-DCF, a state consists of the packet destination, the interferer, and the interferer's destination. Nodes periodically exchange Q tables to prevent concurrent transmissions from destroying the ongoing packet. In CB-OBSS/PD, instead of exchanging Q tables, a node reduces its transmit power when concurrently transmitting with the ongoing packet. While CB-OBSS/PD is simpler to implement, performance of CB-DCF is superior to CB-OBSS/PD. Through extensive simulations with the ns-3 simulator, we show that the proposed methods can achieve high throughput and fairness by intelligently controlling transmissions under various interference conditions.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2023.3328358