alculate the probability that traffic occupies all n channels or is even higher at that point in time. (The offered traffic load may be higher than n even though actual traffic can never exceed n.) We get this by subtracting from 1 the probability that traffic is smaller than n according to (2.6). Figure 2.25 illustrates the procedure we just carried out and shows an example where average offered traffic intensity A = 1 erlangs and the number of available channels n = 3. The probability density function P(x) in the fig- ure tells the probability for each value of X, that is, the number of occupied channels. The probability that all channels are free (x = 0) is P(0) = 0.37, one channel is occupied is P(1) = 0.37, and two channels are occupied (and one is free) is P(2) = 0.18. We subtract the sum of these probabilities from 1 and get the blocking probability, that is, the probability that the number of occupied channels X 3. We get the result, when there are three channels available and average offered traffic is 1 Erl (i.e., on average, one call on all the time), that the blocking probability is 8%. This means that every twelfth call the user makes is blocked and a busy signal is received. Note that this blocking rate allows that only one channel is in use, two channels are free, and only one-third of the capacity can be utilized on average. Equation (2.6) is based on following assumptions [2]: Poisson arrival rate; Poisson-distributed call attempts; Equal traffic volume per source; Lost calls held; calls that are blocked stay in the system and wait for the free channel (subscriber dials and dials again) [3]; Infinite number of sources; if some sources are blocked or making a call, this does not affect the total offered traffic. Let us consider another example: Total offered average traffic during the busy hour is 2 Erl (A = 2); and the number of servers, for example, Introduction to Telecommunications Network Engineering Blocking does not occur; Blocking occurs; there are 0, 1, or 2 channels are 3 or more active 