etail is tricky for precisely this reason. The measurements made in developing the Hata-Okumura model were made under conditions in and around Tokyo that are, in some sense, internal assumptions in the model. The Walfisch-Ikegami model specifies these parameters explicitly. Thus we can think of the distribution of these conditions as the parameter assumptions for street orientations and rooftop heights in the Hata-Okumura model. The good news for us CDMA growth planners is that the absolute path gain levels are less important than the relative levels. It sounds cavalier to wave away what might be a 15-dB difference between two propagation models, but most of the CDMA capac- ity issues involve small cells where user terminals have high path gains (low path losses) between themselves and their base stations. As a wireless telephone system grows denser, the cells get smaller, the serving radius gets smaller, and the path gains get larger. The CDMA equations in Sec. 28.1 make it clear that the relative path gains between user terminals and base stations determine the capacity of a CDMA system. It is good for CDMA capacity when each serving area has one cell sector with much higher path gain than the others, and it is bad when there are large areas of nearly equal radio path gains. The absolute levels of these path gains become less important as the system grows. Terrain-Based Models The Hata-Okumura and Walfisch-Ikegami models are excellent propagation models that depend on the distance from the user terminal to the base station. The next level of refinement is to add terrain data so that we can form path-elevation contours to pre- dict radio propagation. We divide the service area into small regions called bins. These are laid out in a rec- tangular (x, y) grid. The terrain database starts with an elevation, typically height above sea level, for each (x, y) bin. Some terrain databases have more detail, including the vegetation and building density (what the weather radar reports sometimes call "ground clutter"), in 