is normally for the cases of a desired end-to-end delay factor close to 1. For validation, in the following examples the target end-to-end delay factor farget varies between 1.1 to 1.3. Thus, the expected end-to-end delay T = Tmin flarget The offered traffic amount on the last mile is 1060kbps, and thus the total carried traffic at the backbone link is 1060kbps * 4 (number of Node Bs). The validation of the applicability of the approach (1) for dimensioning the last mile link and the backbone link is performed with the following steps: Step 1: given the desired end-to-end delay factor ftarget assign the target delay factor for the last mile link and backbone link individually according to the approach (1), i.e. Step 2: for each link, applying the proposed extended M/G/R-PS model (to resolve the equation (6.26) and (6.27) numerically) to calculate the required link bandwidth for the assigned target delay factor; Step 3: apply the calculated bandwidths into the simulation; Step 4: after running the simulation, measure the average application delays from the simulation and compare it with the expected end-to-end delays. The graph in Figure A.30 (a) shows the average end-to-end delays T for different desired end-to-end delay factors as the QoS criteria. Every point of the curve represents the delay measured in the simulation for the corresponding target end-to-end delay factor. In addition to the simulated mean values, the expected end-to-end delays (target delays) are given in the same graph for comparison. Figure A.30 (b) evaluates the differences of the simulated delays A.18 Validating Dimensioning Approaches for Multi-lub IP RAN and the expected end-to-end delay. It is seen from both graphs that with the bandwidths calculated from the proposed approach (1) for the last mile link and the backbone link (given in Table A.8) in the simulation, the obtained average end-to-end delays from the simulations are close to the target end-to-end delays, i.e. the desired user application QoS is met well. Though it can be obser