hapter, the impact of overbooking is presented and various important aspects that have influence on overbooking are investigated. For a given radio access network, through dimensioning the backbone link, an appropriate overbooking can be derived. Thus, the analytical approaches which are proposed in this chapter for dimensioning the multi-lub RAN are applied to calculate optimum overbooking for the lub backbone link. By comparing with simulation results, the proposed analytical approaches are proven to give accurate estimations on the overbooking and the related dimensioning results. 8.1 Overview and Objectives The structure of a star topology multi-lub RAN is presented in Figure 1.2 (b). It consists of a number of last mile links each connected to one Node B and a backbone link that is connected to the RNC with an aggregate router or switch. For dimensioning such a radio access network, the bandwidths, which need to be assigned to each last mile link and the backbone link, have to be determined. The goal of dimensioning is to guarantee the QoS requirements with the maximum utilization of transport resources on both last mile link and backbone link. Thus, the overall network costs can be minimized. This chapter mainly presents the dimensioning of a multi-lub transport network to guarantee user QoS requirements as the objective of dimensioning. As specified in section 4.1.2.1, the relevant user QoS for the elastic traffic is end-to-end application throughput or delay. For the circuit-switched traffic the considered user QoS is the connection reject ratio. X. Li, Radio Access Network Dimensioning for 3G UMTS, DOI 10.1007/978-3-8348-8111-3 8 Vieweg+Teubner Verlag | Springer Fachmedien Wiesbaden GmbH 2011 8 Dimensioning for Multi-lub RAN Scenario In the previous chapters for a single lub link scenario, processor sharing models have been presented to estimate the application throughput or the delay of the elastic traffic; and the Erlang-B or multi-dimensional Erlang-B formula has been used to calculate the connection 