We introduce the α-κ-µ shadowed (α-KMS) fading distribution as a natural generalization of the versatile α-κ-µ and α-η-µ distributions. The α-KMS fading distribution unifies a wide set of fading distributions, as it includes the α-κ-µ, αη-µ, α-µ, Weibull, κ-µ shadowed, Rician shadowed, κ-µ and ηµ distributions as special cases, together with classical models like Rice, Nakagami-m, Hoyt, Rayleigh and one-sided Gaussian. Notably, the α-KMS distribution reduces to a finite mixture of α-µ distributions when the fading parameters µ and m take positive integer values, so that performance analysis over α-KMS fading channels can be tackled by leveraging previous (existing) results in the literature for the simpler α-µ case. As application examples, important performance metrics like the outage probability and average channel capacity are analyzed.Index Terms-α-µ fading, channel capacity, κ-µ shadowed fading, outage probability, stochastic channel modeling.

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 IG-based composite fading model are directly expressed in terms of a Laplace-domain statistic of the underlying fast fading model, and in some relevant cases, as a mixture of well-known state-of-the-art distributions. We exemplify our approach by presenting a composite IG/two-wave with diffuse power fading model, for which its statistical characterization is directly obtained in a simple form.

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 distribution function of any IG-based composite fading model are directly expressed in terms of a Laplace-domain statistic of the underlying fast fading model and, in some relevant cases, as a mixture of wellknown state-of-the-art distributions. Also, exact and asymptotic expressions for the outage probability are provided, which are valid for any choice of baseline fading distribution. Finally, we exemplify our approach by presenting several application examples for IG-based composite fading models, for which their statistical characterization is directly obtained in a simple form.

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The physical layer security (PLS) performance of a wireless communication link through a large reflecting surface (LRS) with phase errors is analyzed. Leveraging recent results that express the LRSbased composite channel as an equivalent scalar fading channel, we show that the eavesdropper's link is Rayleigh distributed and independent of the legitimate link. The different scaling laws of the legitimate and eavesdroppers signal-to-noise ratios with the number of reflecting elements, and the reasonably good performance even in the case of coarse phase quantization, show the great potential of LRS-aided communications to enhance PLS in practical wireless set-ups.