nsioning for Single ATM-Based lub FP PDU interarrival time measured trace data Figure 6.46: CDF of FP PDU inter-arrival time log(u) measured traffic liner regression Figure 6.47: Self-similarity of the aggregated UTRAN traffic (Hurst Parameter) In order to capture the important statistical properties of the arrival traffic, analytically tractable models are preferred. However, the characterization of the aggregated traffic across the lub interface cannot be represented with the simple Poisson traffic model any more, since the Poisson model is typically used for studying the classical telephone networks and it is not able to capture the bursty nature of the UMTS traffic. In this thesis, two arrival process models are proposed: the Markov Modulated Poisson Process (MMPP) and the Batch Markovian Arrival Process (BMAP) models. 6.4.3 Analytical Dimensioning Models with MMPP This section presents the dimensioning approach based on MMPP for the lub dimensioning devoted to the TNL delay performance. The mathematical definition of the MMPP model is introduced in the following section 6.4.3.1. Section 6.4.3.2 and 6.4.3.3 present the corresponding queuing models with the MMPP arrival process and give their analytical calculations on the queuing delay. The closed form of the queuing delay distributions and their approximations are given. Section 6.4.3.4 explains in detail how to 6.4 Dimensioning for Transport Network Performance apply these queuing models in the dimensioning framework to estimate the necessary lub bandwidth for satisfying a certain lub delay performance. In section 6.4.3.5, the proposed analytical dimensioning approach is validated by simulations. 6.4.3.1 Markov Modulated Poisson Process (MMPP) The Markov-Modulated Poisson Process (MMPP) is an appropriate and practical analytical model, which is able to qualitatively model the time-varying arrival rate and capture some of the important correlations between the interarrival times while still remaining analytically tractable. Therefore, the MMPP model has been