On the Utility of the Inverse Gamma Distribution in Modeling Composite Fading Channels. We introduce a general approach to characterize composite fading models based on inverse gamma (IG) shadowing. We first determine to what extent the IG distribution is an adequate choice for modeling shadow fading, by means of a comprehensive test with field measurements and other distributions conventionally used for this purpose. Then, we prove that the probability density function and cumulative density function of any IGbased composite fading model are directly expressed in terms of a Laplacedomain statistic of the underlying fast fading model, and in some relevant cases, as a mixture of wellknown stateoftheart distributions. We exemplify our approach by presenting a composite IGtwowave with diffuse power fading model, for which its statistical characterization is directly attained in a simple form.

Accurate and Practical Energy Detection over xcexb1xcexbc Fading Channels In this study, a novel and exact closedform expression for detection probability of energy detection (ED) in terms of Meijerxe2x80x99s Gfunction over xcexb1xcexbc generalized fading channels was derived. It is more accurate and practical than the existing exact expressions and has wide application prospects in the performance evaluations in various areas of wireless communications, especially in the wireless sensor network (WSN) and the cognitive radio network (CRN). Furthermore, an exact and simple analytical solution for the sample size meeting the desired detection performance in terms of the probability mass function of a Poisson distribution was also solved. Simulations verified the detection performance and accuracy of our derived expressions with a small sample size compared to the existing exact expressions and approximations.