RT Journal Article
T1 A Tractable Statistical Representation of IFTR Fading with Applications
A1 Olyaee, Maryam
A1 Hashemi, Hadi
A1 Romero-Jerez, Juan Manuel
K1 Montecarlo, Método de
K1 Modelos matemáticos
K1 Distribución (Teoría de probabilidades)
AB The recently introduced independent fluctuating two-ray (IFTR) fading model, consisting of two specular components fluctuating independently plus a diffuse component, has proven to provide an excellent fit to different wireless environments, including the millimeter-wave band. However, the original formulations of the probability density function (PDF) and cumulative distribution function (CDF) of this model are not applicable to all possible values of its defining parameters, and are given in terms of multifold generalized hypergeometric functions, which prevents their widespread use for the derivation of performance metric expressions. A new formulation of the IFTR model is here presented as a countable mixture of Gamma distributions which greatly facilitates the performance evaluation for this model in terms of the metrics already known for the much simpler and widely used Nakagami- m fading, and is shown to provide a better fit to empirical measurements than the original formulation. Additionally, a closed-form expression is presented for the generalized moment generating function (GMGF), which permits to readily obtain all the moments of the distribution of the model, as well as several relevant performance metrics. Based on these new derivations, performance results are presented for the IFTR model considering different metrics, which are verified by Monte Carlo simulations.
PB IEEE
YR 2023
FD 2023-07-12
LK https://hdl.handle.net/10630/31005
UL https://hdl.handle.net/10630/31005
LA eng
NO M. Olyaee, H. Hashemi and J. M. Romero-Jerez, "A Tractable Statistical Representation of IFTR Fading with Applications," in IEEE Transactions on Communications,
NO Funding for open accesscharge: Universidad deMálaga
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026