Statistical multiplexing, admission region, and contention window optimization in multiclass wireless LANs

Authors:
Yu Cheng;Xinhua Ling;Lin X. Cai;Wei Song;Weihua Zhuang;Xuemin Shen;Alberto Leon-Garcia
Affiliations:
Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL;Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada;Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada;Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada;Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada;Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada;Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada
Venue:
Wireless Networks
Year:
2009

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Abstract

This paper presents an analytical model for evaluating the statistical multiplexing effect, admission region, and contention window design in multiclass wireless local area networks (WLANs). We consider distributed medium access control (MAC) which provisions service differentiation by assigning different contention windows to different classes. Mobile nodes belonging to different classes may have heterogeneous traffic arrival processes with different quality of service (QoS) requirements. With bursty input traffic, e.g. on/off sources, our analysis shows that the WLAN admission region under the QoS constraint can be significantly improved, when the statistical multiplexing effect is taken into account. We also analyze the MAC resource sharing between the short-range dependent (SRD) on/off sources and the long-range dependent (LRD) fractional Brownian motion (FBM) traffic, where the impact of the Hurst parameter on the admission region is investigated. Moveover, we demonstrate that the proper selection of contention windows plays an important role in improving the WLAN's QoS capability, while the optimal contention window for each class and the maximum admission region can be jointly solved in our analytical model. The analysis accuracy and the resource utilization improvement from statistical multiplexing gain and contention window optimization are demonstrated by extensive numerical results.