Abstract
In this article, we investigate a fairness issue between uplink and downlink flows in IEEE 802.11 Wireless Local Area Networks (WLANs). We propose a cross-layer adaptive algorithm which dynamically adjusts the minimum contention window size of access point according to the amount of downlink users and channel conditions to achieve per-flow fairness. In case that uplink and downlink transmissions are with different bandwidth demands for various applications, our algorithm can efficiently find the optimal minimum contention window size which provides weighted fairness based on their resource requirements. The simulation results demonstrate that our scheme can effectively provide both per-flow fairness and weighted fairness in a varying WLAN environment.
Highlights
In recent years, IEEE 802.11 Wireless Local Area Networks (WLAN) [1,2] have become increasingly popular with the wide deployment of infrastructures and the prevalence of mobile/handheld devices
If uplink and downlink flows are with different bandwidth demands for various applications, our algorithm can adaptively tune the contention window size to provide weighted fairness based on their resource requirements
The contribution of this article is that we present a cognitive algorithm based on a cross-layer design which can sense the changes of wireless environments, and adapts the system parameters intelligently to achieve per-flow fairness or weighted fairness
Summary
IEEE 802.11 Wireless Local Area Networks (WLAN) [1,2] have become increasingly popular with the wide deployment of infrastructures and the prevalence of mobile/handheld devices. We propose a cross-layer adaptive algorithm which dynamically adjusts the minimum contention window size of AP based on the amount of downlink flows to achieve per-flow fairness.
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