t be using it, but we have lit- tle idea what services people will fancy when all the 3G choices become available. In making these predictions, there are two important issues we can take into account. First, it is important to distinguish business services from consumer services. The methods for predicting demand and for pricing for each of these are very different. Sec- ond, it is important to realize that demand is a function of price. As North American 3G data services are rolling out, vendors are taking very different approaches on this is- sue. Some, concerned with rapidly recouping the high cost of deployment, are setting a high price for data services. Others are charging a low rate, hoping to capture market share and more willing to risk being swamped with demand. In addition, some vendors are choosing to offer very limited usage in the basic package and a high charge for ad- ditional use. Others are offering a flat rate for unlimited or high-limit use, which al- lows them to estimate demand at a fixed price. As before, in voice and data, we should use Eq. (31.1) and add up the gross estimated usage of these other services. Also, we should create a geographic distribution estimate for use in later stages of planning our system layout. 31.4 Estimating Cell Count For voice telephony, we compute the total peak-time demand in erlangs e. Then we mul- tiply that by the voice data rate R, Eb/No, and activity factor U in Eq. (31.1) for a gross usage in chips per second. The values of R and Eb/No are determined by the air inter- face described in Sec. 30.7. This gives us a gross chip rate y for voice. For data services, we have to add up multiple services. We concentrate on services that have low delay requirements. For each low-delay data service, we use our forecast demand in erlangs e, the data rate R, its Eb/No requirement, and its activity factor U. The voice telephony y value is added to the sum of the gross chip rate y values for all the data services. Other services also have demands in erlangs e, data rat