Multipath propagation is characterized by multipath fading (including amplitude and phase), delay spread, direction of arrival (DOA, determined by the azimuth and the elevation angle) and polarization. Doppler effects are the frequency-domain expression of the time-domain fast fading, where the direct relationship between Doppler spread and the path DOAs can be found. Several channel models have been developed to generate complex channel impulse responses, for example the Wide-Sense Stationary Uncorrelated Scattering (WSSUS) model, which is used in COST 207 project, and the Stochastic Radio Channel Model (SRCM), which is developed in the COST 259 project.

The common purpose for the WSSUS model and SRCM is to get the Channel impulse response, which is required for simulations. The WSSUS model characterizes the channel by means of correlation functions, equivalently power spectral densities, where the radio channel is represented by a tapped delay line. In WSSUS channel model, the polarization informaton is not contained, and for the DOA, the uniform spectrum is reasonably assumed in the azimuth angle, but the elevation information, which can not be considered as uniform but depends on the enviroment, is ignored. The multipath characteristics in WSSUS model may be more realistic for the stationary outdoor channel.

The SRCM is a parametric model which is characterized by a set of parameters, and all the propagation effects whcih have an impact on the system performance are taken into account. Thus, SRCM is essentially an extension of the WSSUS model and also exhibit the wide-sense-stationary uncorrelated-scattering property of the radio channel. However, in contrast to the conventional WSSUS model, the SRCM includes the waves' polarization and allows to consider systems in which the polarization and space diversity is exploited, i.e., the smart antennas are used. The SRCM is advantageous compared to other channel models for the indoor communications, where the situation is very different from the ourdoor. Obviously, the consideration of all aspects leads to a rather high computational complexity of the SRCM. But it has demonstrated that for indoor radio wave propagation the dominated waves exhibit discrete character, where the incident waves exhibit a clustering pattern in delay, azimuth and elevation. Then, in a specific indoor situation, according to the transmission constellation or the needed accuracy, some effects that have only little impact to the system performance can be neglected and different levels of model complexity can be introduced, which may result in a considerable reduction of the model complexity. Thus, to simplify the model it is necessary to identify the different types of indoor envionment and different indoor services.