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Throughput Modeling of Large-Scale 802.11 Networks

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.