tion and management etc.), but the analytical models only make statistical assumptions and approximations. Therefore, in this thesis, the proposed analytical dimensioning models are validated through simulations. In general the analytical approach is preferred for the dimensioning due to its low effort and feasible implementation, and it can provide analytical expressions representing the dependency of the performance on the various model parameters. For this reason, one of the main goals of this thesis is to propose appropriate analytical models for the dimensioning. The selection of an appropriate analytical model depends on several aspects. 1. The exactly modeled and the approximated elements of the considered network behavior: it is a common approach that the detailed models are applied only to the part 4.4 Dimensioning Approaches of the network that is under the scope of the analysis, but the overall network behavior is described with some reasonably simple model. 2. The required accuracy of the results: different analytical queuing models provide different level of accuracy. The applied model should be as simple as possible to minimize the computational complexity while providing the required accuracy. 3. The performance parameters of interest: the selected simplifying assumptions depend on the performance measure of interest. For example, when the performance measure of interest is the packet delay on the access link the detailed modeling of the individual users is usually not required. Instead, a simplified queuing model describing the aggregate traffic over the link and the transmission rate is sufficient. 4. The feasibility for the model: the applied analytical model should be feasible to implement and apply in the dimensioning process. Figure 4.7 shows an overview of the considered analytical models for the dimensioning of the UTRAN networks in this thesis. Essentially, the analytical dimensioning models are divided into two main categories: models for estimating the user-relevant QoS and models for ev