This dissertation deals with the accurate backoff process modeling of the IEEE 802.11 Distributed Coordination Function( DCF) and characterization of traffic distribution. The backoff process has a significant impact on the performance of the IEEE 802.11 DCF protocol depending on the offered load conditions on the network; unsaturated or saturated load conditions. In unsaturated load conditions a short backoff' is desrable due to emerging queueing dynamics. While in saturated load conditions where thequeue might be full, a long backoff process will help in avoiding collisions. Several attempts have been made to develop an analytical model to correctly represent the behavior of the actual backoff process in unsaturated and saturated load conditions. However what seems to be lacking in existing approaches is the consideration of offered load as the key parameter to modeling the backoff process. Since the offered load has a critical role in the backoff process modeling assumptions, in this thesis a complete mathematical model of the DCF protocol is developed to provide a framework through which the IEEE 802.11 medium access control (MAC) behavior can be evaluated. The I motivations for this thesis are enumerated below: (i) To enhance existing legacy models on the DCF, as upcoming IEEE 802.11 amendments (versions 11 ac, 11 ad, 11 ah, 11 af, etc.) are based on it. The current enhanced distributed channel access (EDCA) scheme of the IEEE 802.11-2012 standard (IEEE P802.11ac/D3.0 2012) is only a technical extension of DCF. It may also be noted that the upcoming IEEE 802.11ac and .11 ad standard amendments (IEEE 802.H-2012 .2012: IEEE P802.11adiD8.0 2011) are also based on the core MAC of IEEE 802.11-2012. (ii) To revisit assumptions behind existi the vast amount of literature work, issues such as how closely an models in favor of improved accuracy. Despite analytical model captures with the actual DCF back off process have remained open (Tinnirello, Bianchi, and Xiao 2010). One of the key reasons for the lack of accuracy in the models lies in the approximations due to assumptions. Thus, revisiting the assumptions of existing models is still desirable for improved accuracy. (iii) To study the offered load dependency on service time distribution for selecting the appropriate queuing model. In literature (T. Li, Leith, and Malone 2011; Zanella and De Pellegrini 2005) several attempts have been made to study the variation in the mean service time for arbitrary offered loads. However, showing the dependency in the form of patterns could provide a useful tool for selecting the right queuing model and further enhance the accuracy of performance analysis. (iv) To harmonize and unify disjoint approaches to unsaturated and saturated load analysis. In the literature, the unsaturated (Engelstad and Osterbo 2006; Duffy, Malone, and Leith 2005; Tickoo and Sikdar 2008; Pham, Perreau, and Jayasuriya 2005; Vardakas et al. 2007; Dong et al. 2008; Zhao, Tsang, and Sakurai 2011) and saturated load (Tinnirello, Bianchi, and Xiao 2010; Pham, Perreau, and Jayasuriya 2005; Vardakas et al. 2007; Bianchi 2000; Foh and Tantra 2005) performance analysis has been addressed separately and there is a need to have a unified approach. This thesis seeks to address the issues highlighted above and provides a framework for studying the average end-to-end packet delay for arbitrary loads. Furthermore, the characterization of the service time distribution through the dependency patterns is also discussed. The dependency patterns constructed using the newly proposed backoff process model provides greater insight into queueing modeling assumptions. With an accurate backoff process model, the queueing model can be analyzed independent of the IEEE 802.11 DCF model. Thus, traffic modeling can be analyzed separately without the fear of errors emanating from the underlining IEEE 802.11 DCF analytical model. Inaccuracies can thus be treated by observing the traffic pattern and modeling it more closely