A Composite Shadowed Fading Model Based on the McKay Distribution and Meijer G Functions
The McKay density function has been cited in the study of wireless channels in connection with the analysis of diversity. It is also a forerunner of the \(\upeta \)-\(\upmu \) and \(\upeta \)-\(\uplambda \)-\(\upmu \) distributions in wireless channels. Starting with a physical description of fading in terms of clustering and using the existing results from the original work of Nakagami, the probability density function of the signal-to-noise ratio has been shown to match the three parameter McKay distribution. It is demonstrated that the McKay density also allows for the modeling of wireless channels exhibiting fading levels far worse than what is seen in Nakagami channels, allowing the amount of fading to vary from 0 to \(\infty \). The shadowing in wireless channels is then incorporated in the model using the cascading concept to describe the shadowing. The error rates in such a McKayMeijer G model are studied using the example of a coherent binary shift keying modem. With the availability of closed form expressions for the density, cumulative distribution function, error rates and outage probabilities, the McKayMeijer G model offers a very flexible means to study the performance of modems in composite shadowed fading channels.
mckay distribution meijer g function shadowed fading channels generalized hoyt density correlated gamma variables cascaded channels