Statistical Model of Accurately Estimating Service Delay Behavior in Saturated IEEE 802.11 Networks Based on 2-D Markov Chain

To accurately estimate the service delay behavior of IEEE 802.11 networks, this paper comprehensively considers four main factors that affect performance networks and establishes a model with statistical characteristics. We analyzed operation mechanism DCF, using backoff stage counter to portray dynamic change characteristics system regarding data frame transmission states. Afterward, we calculated one-step transition probability these states, establishing 2-D Markov model, including ICS procedure procedure. Based on constructed steady-state equations derive relationship between collision for each node queue. By analyzing delay, obtained generating function (PGF) average idle time. The analytical expressions other delays, such as successful time collided time, were derived obtain PGF total delay. In numerical simulation, compared first two moments Nav it was found our evaluation results significantly better than traditional results. in all scenarios larger proposed due lack model. Since DIFS duration is generally much shorter random duration, saves bandwidth improves efficiency.