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After a brief review of the known description of time-variant channels by means of system and correlation functions, a consistent extension of this description to directional time-variant channels is described in the present paper. This extension allows a clear distinction between time-and space-variant effects in directional mobile radio channels. The major intention of the described directional extension however is the derivation of a statistical modeling approach for small-scale fading effects in time-variant wideband directional channels, which can be regarded as a consistent extension of the well established Rayleighor Rice-fading approach for nondirectional time-variant narrowband channels. The approach, which is based on the time and aperture-variant transfer function, appears to be preferable to the frequently used statistical modeling of the time-variant angle-resolved impulse response for several reasons. The major advantage is that the approach can cope with the demand for a great number of superimposing components as the basis for statistical modeling. The correlation between adjacent values is proposed to be achieved by filtering with appropriate directional scattering functions. The description of the modeling approach, as done in the present paper, is intended to be general and universal; for the application on certain channel types statistical distribution functions and parameters to be used with the approach can readily be determined from appropriate measurements.

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The statistical distribution of amplitudes and phases of paths are investigated for Time-Variant Impulse Responses that have been measured in 63 different scenarios in indoor environment. Each measurement consists of 89 consecutive impulse response samples. In contrast to investigations by other authors the occurrence of time-variant changes of path lengths has been taken into account for the detection of paths by applying an algorithm denoted as "path-tracking". Evaluation is done by the examination of frequency distributions for the remaining errors when fitting theoretical curves to distributions from measurements. A Weibull distribution shows the best fit for the distribution of path amplitudes. The results for the Nakagami distribution and the Rice distribution turn out to be rather similar to the results for the Weibull distribution, whereas Rayleigh and lognormal distribution seem to be less appropriate. The path phases are shown to be extremely good uniform distributed. A modeling approach that takes into account deterministic influences, especially the correlation between adjacent impulse responses, is also briefly discussed.

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