Contents I. Introduction
A great number of distributions exist that well describe the statistics of the mobile radio signal. The long-term signal variation is known to follow the Lognormal distribution whereas the short term signal variation is described by several other distributions such as Hoyt, Rayleigh, Rice, Nakagami- , and Weibull. It is generally accepted that the path strength at any delay is characterized by the short-term distributions over a spatial dimension of a few hundred wavelengths, and by the Lognormal distribution over areas whose dimension is much larger [1]. Among the short term fading distributions, Nakagami- has been given a special attention for its ease of manipulation and wide range of applicability. Although, in general, it has been found that the fading statistics of the mobile radio channel may well be characterized by Nakagami- , situations are easily found for which other distributions such as Hoyt, Rice, and Weibull yield better results [1]–[4]. More importantly, situations are encountered for which no distributions seem to adequately fit experimental data, though one or another may yield a moderate fitting. Some researches [2] even question the use of the Nakagami-m distribution because its tail does not seem to yield a good fitting to experimental data, better fitting being found around the mean or median. The well-known fading distributions have been derived assuming a homogeneous diffuse scattering field, resulting from randomly distributed point scatterers. The assumption of a homogeneous diffuse scattering field is certainly an approximation because the surfaces are spatially correlated characterizing a non-linear environment [5]. With the aim at exploring this non-homogeneity, two new fading distributions - the Distribution and Distribution - have been presented in [6]–[8] and to explore the nonlinearity of the propagation medium, which was addressed more recently in a new proposed general fading distribution, the Distribution [9].
