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We identify common hypotheses on which a large number of distinct mathematical models of WLANs employing IEEE 802.11 are founded. Using data from an experimental test bed and packet-level ns-2 simulations, we investigate the veracity of these hypotheses.We demonstrate that several of these assumptions are inaccurate and/or inappropriate. We consider hypotheses used in the modeling of saturated and unsaturated 802.11 infrastructure mode networks, saturated 802.11e networks, and saturated and unsaturated 802.11s mesh networks. In infrastructure mode networks, we find that even for small numbers of stations, common hypotheses hold true for saturated stations and also for unsaturated stations with small buffers. However, despite their widespread adoption, common assumptions used to incorporate station buffers are erroneous. This raises questions about the predictive power of all models based on these hypotheses. For saturated 802.11e models that treat differences in arbitration interframe space (AIFS), we find that the two fundamental hypotheses are reasonable. For 802.11s mesh networks, we find that assumptions are appropriate only if stations are lightly loaded and are highly inappropriate if they are saturated. In identifying these flawed suppositions, this work identifies areas where mathematical models need to be revisited and revised if they are to be used with confidence by protocol designers and WLAN network planners.

Wireless Local Area Networks (WLANs) have been widely developed during this decade, due to their mobility and exibility. During this period, IEEE 802.11 has become the dominant WLAN protocol. This thesis reports on research into WLANs, especially IEEE 802.11 networks. Since IEEE 802.11 denes rules at the MAC and Physical (PHY) layers, which are introduced in Chapter 1, the rst part (Chapters 2, 3 and 4) of this thesis deals with analytical models for the Distributed Coordination Function (DCF) of the IEEE 802.11 MAC, while the second part (Chapters 5 and 6) focuses on the transmission rates provided by the IEEE 802.11 PHY layer. Analytical models are widely adopted in research into WLANs, especially IEEE 802.11 networks. Despite dierences in details of published analytical models, most of them share common hypotheses. To ensure condence in the predictions made by the analytical models that are based on these common hypotheses, Chapter 2 identies these common hypotheses, and investigates them. By statistically analyzing simulation-based and experimental data, we found the appropriateness of these fundamental hypotheses only exists under some specic limitations. One of the common hypotheses investigated in Chapter 2 is the assumption that the conditional collision probability is constant and independent of the transmission history that is revealed by the back-o stage (the collision-decoupling assumption). Chapter 3 analyzes the relationship between the conditional collision probability and the back-o stage, by building an explorative analytical model without the commonly adopted collision-decoupling assumptions. Thus, Chapter 3 provides an analytical way to the understanding of the collision-decoupling assumption. Another common hypothesis investigated in Chapter 2 is the assumption that the probability of having a non-empty queue after each packet transmission is constant and independent of the transmission history (the queue-decoupling assumption). Although this que

We identify common hypotheses on which a large number of distinct mathematical models of WLANs employing IEEE 802.11 are founded. Using data from an experimental test bed and packet-level ns-2 simulations, we investigate the veracity of these hypotheses.We demonstrate that several of these assumptions are inaccurate and/or inappropriate. We consider hypotheses used in the modeling of saturated and unsaturated 802.11 infrastructure mode networks, saturated 802.11e networks, and saturated and unsaturated 802.11s mesh networks. In infrastructure mode networks, we find that even for small numbers of stations, common hypotheses hold true for saturated stations and also for unsaturated stations with small buffers. However, despite their widespread adoption, common assumptions used to incorporate station buffers are erroneous. This raises questions about the predictive power of all models based on these hypotheses. For saturated 802.11e models that treat differences in arbitration interframe space (AIFS), we find that the two fundamental hypotheses are reasonable. For 802.11s mesh networks, we find that assumptions are appropriate only if stations are lightly loaded and are highly inappropriate if they are saturated. In identifying these flawed suppositions, this work identifies areas where mathematical models need to be revisited and revised if they are to be used with confidence by protocol designers and WLAN network planners.

Wireless Local Area Networks (WLANs) have been widely developed during this decade, due to their mobility and exibility. During this period, IEEE 802.11 has become the dominant WLAN protocol. This thesis reports on research into WLANs, especially IEEE 802.11 networks. Since IEEE 802.11 denes rules at the MAC and Physical (PHY) layers, which are introduced in Chapter 1, the rst part (Chapters 2, 3 and 4) of this thesis deals with analytical models for the Distributed Coordination Function (DCF) of the IEEE 802.11 MAC, while the second part (Chapters 5 and 6) focuses on the transmission rates provided by the IEEE 802.11 PHY layer. Analytical models are widely adopted in research into WLANs, especially IEEE 802.11 networks. Despite dierences in details of published analytical models, most of them share common hypotheses. To ensure condence in the predictions made by the analytical models that are based on these common hypotheses, Chapter 2 identies these common hypotheses, and investigates them. By statistically analyzing simulation-based and experimental data, we found the appropriateness of these fundamental hypotheses only exists under some specic limitations. One of the common hypotheses investigated in Chapter 2 is the assumption that the conditional collision probability is constant and independent of the transmission history that is revealed by the back-o stage (the collision-decoupling assumption). Chapter 3 analyzes the relationship between the conditional collision probability and the back-o stage, by building an explorative analytical model without the commonly adopted collision-decoupling assumptions. Thus, Chapter 3 provides an analytical way to the understanding of the collision-decoupling assumption. Another common hypothesis investigated in Chapter 2 is the assumption that the probability of having a non-empty queue after each packet transmission is constant and independent of the transmission history (the queue-decoupling assumption). Although this que