Throughput Modeling of Large-Scale 802.11 Networks

Abstract

The success of dynamic spectrum access through simple listen-before-talk etiquettes has made way for opening up the spectrum. However, many problems still remain in this kind of networks. Stations might not be able to sense as much transmissions and hence defer channel access less often than their neighbors. This can lead to unfairness or (worst-case) starvation of certain terminals. In this paper we model the throughput of a large-scale 802.11 network. Although the fairness issues in these networks are known, network modeling is still focusing on small-scale rigid networks. We want to open up this research toward large-scale randomly distributed topologies. A new model is developed to predict the long-term throughput of flows inside such a large-scale 802.11 network. Our model is validated through ns-2 simulations.

Beamforming techniques for enabling spatial-reuse in MCCA 802.11s networks

“…However, this comes at the cost of a higher number of exposed nodes hence degrading the spatial-reuse gain. In [10], it is shown that the exposed node problem, when relying on distributed resource allocation, should not be avoided but that there is an optimal trade-off between the two problems. No MAC-layer techniques only is capable of removing the inefficiencies of the hidden versus exposed node problems.…”