A Tractable Statistical Representation of IFTR Fading with Applications

TL;DR

This paper introduces a new, mathematically tractable formulation of the IFTR fading model as a mixture of Gamma distributions, enabling easier performance analysis in wireless communication systems.

Contribution

It provides a Gamma mixture-based formulation of the IFTR model and closed-form GMGF, simplifying the derivation of performance metrics compared to previous hypergeometric function-based expressions.

Findings

Accurate modeling of wireless channels with the new formulation.

Simplified calculation of capacity, outage, and BER metrics.

Validation of results through Monte Carlo simulations.

Abstract

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. In this paper we present a new formulation of the IFTR model 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. 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, the IFTR model is evaluated for the average channel capacity, the outage probability with and without co-channel interference, and the bit error rate (BER), which are verified by Monte Carlo simulations.