know that voice calls compete with data services for resources. However, we may not realize how alternative data services, perhaps for different customer communities, compete with each other for system resources. Having enough common channels for rapid-access, high-speed packet access may limit not only voice traffic but also e-mail and dedicated virtual-circuit data services. 22.7 Conclusion Many of the practical rules of thumb we follow in making good business and engineer- ing decisions actually have a source in quantitative models from economics, engineer- ing, and other disciplines. When we have a problem that has a precise definition and we have enough time and money to spend on it, creating a model of our system and making decisions based on optimization of the model are extremely beneficial. How- ever, in the far more common case of needing to make decisions quickly when a num- ber of elements are not well defined, we need to be able to fall back on less precise tools such as common sense and clear thinking. Downloaded from Digital Engineering Library @ McGraw-Hill (www.digitalengineeringlibrary.com) Copyright © 2004 The McGraw-Hill Companies. All rights reserved. Any use is subject to the Terms of Use as given at the website. Source: CDMA CAPACITY AND QUALITY OPTIMIZATION Chapter Traffic Engineering for Voice and Data To engineer any telephone system, wireless or landline, we need some way of estimat- ing telephony demand and criteria for satisfying that demand. Traffic engineering is the process of assigning facilities to satisfy a demand. Traffic engineering is particu- larly important inside the public switched telephone network (PSTN), the Internet, the cellular backhaul network, and other networks where demand from multiple users is carried over shared channels. Statistical methods can be applied to estimate demand and design facilities to meet peak demand. In this chapter we will explain those meth- ods. First, we will look at the methods traditionally used in telephony, which assumed that all circ