, and we can control the environment of a simulated system and do experi- ments that would not be practical, or even possible, on a real system. We start with a collection of base stations. Each base station has a physical location, an (x, y) location, and a tower height. A base station has a collection of antenna faces for sectors, and each antenna face has its own radiation pattern and antenna gain Each antenna face has a collection of CDMA carriers using whatever air-interface tech- nology we are simulating in our system. The physical environment is represented by (x, y) bins covering the entire service area. For each of these bins we have a radio path gain that comes from terrain-driven propagation calculations. If there is a subscriber community that makes calls from significantly higher or lower elevation, such as an elevated highway, the upper floors of an office complex, or an underground shopping mall, then we may need another set of bins with another set of radio gains for the other elevation. The subscriber demand is represented by a call volume for each bin, some number erlangs. Each different service in the system has its own demand profile, its own er- lang count, for each bin. Now we have a representation of the entire system in our computer memory. We have cells, sectors, terrain, propagation, and subscriber demand for each service. The simu- lation program is our way of putting the system into motion. Simulated subscribers start their calls in proportion to the erlang counts of their bins. These calls are created by random numbers generated by the computer program. Each service type has its own distribution of call duration. Once calls appear in the sys- tem, we simulate their access and paging messages, and once the calls are active, we simulate the forward and reverse CDMA channel, including power control. As the call continues, the user terminal can move, and it may change radio conditions by doing SO. This leads to power changes in the CDMA channel that may lead to hand- offs, which may be so