On the Generation of White Samples in Severe Fading Conditions

The aim of this letter is three-fold: 1) to propose a simple and efficient algorithm to generate white samples for the envelope of the <inline-formula> <tex-math notation="LaTeX">${\kappa }$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">${\mu }$ </tex-math></inline-formula> fading model over the multipath fading clustering parameter within <inline-formula> <tex-math notation="LaTeX">${0< \mu < 0.5}$ </tex-math></inline-formula>, filling an existing gap in the generation of samples of the <inline-formula> <tex-math notation="LaTeX">${\kappa }$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">${\mu }$ </tex-math></inline-formula> distribution; 2) to propose a simple algorithm to generate white samples for the envelope of the <inline-formula> <tex-math notation="LaTeX">${\alpha }$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">${\eta }$ </tex-math></inline-formula>- <inline-formula> <tex-math notation="LaTeX">${\kappa }$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">${\mu }$ </tex-math></inline-formula> fading model; and 3) to propose a simple and near 100% efficient algorithm to generate <inline-formula> <tex-math notation="LaTeX">$ {\kappa }$ </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">$ {\mu }$ </tex-math></inline-formula> Extreme white samples. The algorithms make use of the acceptance–rejection method. The goodness-of-fit is objectively measured via the Kolmogorov–Smirnov test. An application example is given in order to illustrate the use of the algorithms.