 (6.3) involves only two. Therefore it is easier to solve the local balance equations. The detailed steps to solve the state probabilities for the one-dimensional state transition diagram (Figure 6.1) using local balance equations can be found in [Ive04]. The state probability formula is given in equation (6.5). It is also called as Erlang's first formula. (0<i<n) (6.5) It can be noted that if n is infinite, i.e. n = 80, the above Erlang loss system becomes simple Poisson distribution, where An important property of the Erlang loss model (with Poisson arrivals) is its insensitivity property stating that the state probabilities (i.e. the equilibrium distribution of the number of connections present) are insensitive to the form of the service time (or holding time) distribution and requires only the mean service time [Coh79, Ive04]. Erlang-B formula Knowing the state probabilities, the blocking probability pb that a new call arriving at the circuit network is rejected can be calculated. According to the PASTA-theorem (Poisson Arrivals See Time Averages) [Wol82], the blocking probability pb is equal to the probability that the system is in state n (i.e. all n channels are busy). Thus pb can be derived from (6.5) with i = n. 6.2 Dimensioning for Circuit-Switched Traffic (6.6) This is SO called Erlang-B formula (1917, [EHA48]). It is also called as Erlang first formula. It is assumed that the offered traffic A (in Erlang) are offered to n channels. Figure 6.2 plots blocking probability pb as a function of the offered traffic A (in Erlang) for different n for the Erlang loss model calculated with Erlang-B formula (6.6). As mentioned above, the Erlang loss model has the insensitive property. This property is also possessed by the Erlang-B formula. That means that the blocking probability pb is insensitive to the form of the holding time distribution but depends only on the first moment of the holding time. This property will be validated via simulations in section 6.2.4. Another property of the Erlang-B formula is that 