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