ation time. The degree of determinism is also re- parative overview of these models include such issues as lated to the accuracy of environment representation. For database accuracy sensitivity, computation time, diffuse example, the adoption of a very accurate, full wave FDTD scattering modelling, and performance metrics. Since method in an environment described in terms of soil usage reliability and cost of input databases represent major and building density would be a nonsense. Commercially concerns, Subsection 4.7.3.2 is fully devoted to this topic. available urban databases are not very accurate and de- The various models are then treated starting from the tailed. Therefore, some propagation effects which are more rigourous, complex (4.7.3.3) to the more simplified critically sensitive to database accuracy (e.g. fast fading, ones (4.7.3.7). diffuse scattering, phase, polarisation, etc.) must be necessarily neglected or treated in a statistical way. 4.7.3.2 Input database issues Deterministic propagation models have advantages and drawbacks with respect to statistical models such as Deterministic propagation models require as input Hata-like models or statistical channel models. De- a proper description of the environment. In the case of terministic models are physically meaningful, accurate and urban propagation modelling, which is of interest here, flexible. Statistical models on the other hand are simpler, both a geometrical and an electromagnetic description Propagation modelling and channel characterisation CHAPTER 4.7 of each object (building, wall, terrain) must be provided permittivity (Er) and the conductivity (a) of each class of and stored in the database. Outdoor databases can be materials. For example, Er = 5 and o = 10-2 are usually extracted from aerial views using stereo-photogram- adopted for typical building walls in European cities. metry, from digital cadastre data or by digitising ana- Each environment type (indoor, dense urban, suburban, logue maps. If the space domain is discretised in