el (different service time distributions) In Figure 6.10, the state probabilities for normal, uniform, constant and exponential holding time distributions are shown, and also validated with the Erlang-B model. This figure 6 Dimensioning for Single ATM-Based lub demonstrates that the Erlang loss model with the Poisson arrival process and furthermore the Erlang-B formula is not sensitive to the holding time distributions, and thus the probability of the number of busy connections in the system is not influenced by different holding time distributions, but only depends on the mean value. With this property, the Erlang-B formula can be widely applied for a range of circuit-switched traffic with Poisson arrival process but arbitrary holding time distributions. 6.2.5 Dimensioning Results The following gives the dimensioning with a fixed blocking probability (CAC reject ratio) by applying the Erlang-B formula. For proper operation, a loss system should be dimensioned for a low blocking probability. In practice, the bandwidth is typically designed SO that the blocking probability is around 1% to avoid overload. Table 6.3 shows the required number of channels n in the network for a fixed CAC reject ratio (B= 1%, 5%) for different amount of the offered traffic A in Erlang. The results are derived from the Erlang-B formula (6.6). Because it is configured that each voice connection reserves 12.4 kbps bandwidth, the required number of channels n for a fixed CAC reject ratio can be converted to the required transport bandwidth on the lub link in kbps. Figure 6.11 and Figure 6.12 present the required lub bandwidth obtained from both Erlang-B formula and simulations for the fixed CAC reject ratio of 1% and 5% respectively, over different offered voice traffic demands (in kbps). In both figures, the left chart give the required lub bandwidth in kbps for the guaranteed CAC reject ratio and the right one illustrates the relative error that is calculated as the difference in bandwidth of the Erlang-B model and the simulations as a r