h a little more mathematical hand waving, we can figure that two independent servers are busy 20 percent of 20 percent of the time, a net blocking rate of 4 percent for 0.4 erlang of demand. As loose as this approximation is, it helps us believe that two servers can serve 0.38 erlang at 5 percent blocking. The last line of Table 23.1 has the puzzling number of 100 channels serving 104.11 erlangs at 10 percent blocking. How can this be? The answer is that only 93.7 erlangs are actually served, and the other 10.4 erlangs are turned away, the 10 percent who are blocked. Another view of system capacity is occupancy, the fraction of the time the channels are in use. Table 23.2 shows the same information in terms of occupancy rather than erlangs of demand. The relationship is Occupancy channels Tables 23.3 and 23.4 show the Erlang-B capacity and occupancy data for 24-trunk DS-1 and 30-trunk E-1 links. We also can do this calculation for very low blocking rates and larger numbers of channels in Tables 23.5 and 23.6. These are more typical values for the large trunk groups found inside the public switched telephone network (PSTN). Knowing the demand is a critical part of wireless telephone system. Planning engi- neers rely on forecasts for initial planning, but wireless system growth can be based on measured demand. Measuring demand is easy when blocking rates are low. If nobody is blocked, then us- age is the same as demand. The demand in erlangs is the total of the call durations di- vided by the time interval chosen. Typical telephone company engineering is for the highest-demand time of day, the "busy hour." Measuring blocking rate by itself is not useful because we do not know how often callers retry when their calls are blocked. Instead, we can measure the occupancy and use the formulas that generated Tables 23.1 through 23.4. We measure the call min- utes used during the busy hour, divide by the available call minutes, and use that ra- tio as the occupancy in estimating demand. 4While this is high school algebra, 