n of fac_i=fbb, = the assigned target delay factor for the ith last mile link and the backbone link can be calculated with equation (8.6). T_Tminaa1 (8.6) if (fac_i = fbs), then Approach (1) is only suitable for the case with small end-to-end delay factors, i.e. the application QoS requirement is relative high. Approach (2) and (3) can be used for the case with large target delay factors. If the network operators try to minimize the transport costs spent on the last mile links, approach (2) is suggested. As in a real network usually the number of last mile links is much larger than the number of backbone links, SO if every last mile link is assigned a minimum bandwidth the overall network costs can be low. The main 8.3 Dimensioning for Elastic Traffic in ATM-Based UTRAN drawback of the approach (2) is that there will be low overbooking gain over the backbone link, since the last mile links will be highly utilized and the backbone link has a lower target delay factor than the last mile links. If there are no specific requirements on the transport costs for the last mile and the backbone links, approach (3) can be used as a general dimensioning solution which assigns the same delay factor to both last mile and backbone links. Approach (3) is also valid for the case of a small end-to-end delay factor. When ftarget is close to 1, the calculated delay factor for the last mile link and the backbone link from the approach (3) will be similar to the ones obtained from the approach (1). Given a properly assigned delay factor for each link using the above suggested approaches, the minimum bandwidths of the individual links can be calculated with the same processor sharing model as used in the single link scenarios. Thus the developed analytical dimensioning approach for a star-structured multi-lub RAN is illustrated in Figure 8.8. In this approach, the last mile link and the backbone link are dimensioned individually with a processor sharing model to meet the individual assigned target delay factors fac_i (for ith last mil