 an appropriate network dimensioning approach, firstly correct methods need to be developed to estimate the user QoS on an end-to- end basis. The following section 8.3.1 presents the proposed analytical methods for estimating the end-to-end application performance, taking into account the individual impact of last mile link and the backbone link. Based on the proposed methods, several dimensioning approaches are suggested in section 8.3.2 to determine the bandwidths for the last mile link and the backbone link separately. 8.3.1 Estimation of End-to-End Application Performance The system model of a multi-lub network is shown in Figure 8.4. The elastic traffic is transmitted through the network between the two ends: the end user (i.e. UE) and the corresponding node in the external networks (e.g. Internet). The required end-to-end QoS requirement is the average throughput Dt, which each flow receives for data transactions, or that an amount of Xt bytes can be transferred within an expected time period Tt. The expected end-to-end delay is mainly influenced by the UMTS radio access network, subject to the assigned Radio Access Bearer (RAB) rate and the limited transport capacities over the lub interface. In the star or tree-structured access network, every link over the transport path can be the bottleneck and cause considerable impact on the end-to-end delay. Thus, in the presented star-structured access network, both the last mile link and the backbone link shall be considered for estimating the end-to-end application delay performance. Moreover, the additional delays within the UMTS core network and the external networks are modeled as an extra delay value added to the TCP Round Trip Time (RTT). (x,,T)),D,,f corresponding node (p1, Cac_1)--fac_1 Internet Node B 1 (,C fbb Node B 2 (P2,Cac_2) switch/router r peak (Pn, Cac_n) fac_n Node Bn lub Interface Figure 8.4: System model for elastic traffic in the multi-lub RAN 8.3 Dimensioning for Elastic Traffic in ATM-Based UTRAN It is assumed that there are n Node Bs in the