The Fluctuating Two-Ray Fading Model With Independent Specular Components

Olyaee, Maryam; Cortes, José A.; López‐Martínez, F. Javier; Paris, José F.; Romero-Jerez, Juan M.

doi:10.1109/tvt.2022.3229238

Cited by 6 publications

(11 citation statements)

References 20 publications

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“…Proof: See Appendix A. Note that, in contrast to the PDF and CDF expressions given in [5], ( 8) and ( 9) are valid for arbitrary values of m 1 and m 2 , and therefore this is also true for all the performance metrics derived from them.…”

Section: New Representation Of the Iftr Fading Modelmentioning

confidence: 99%

“…In spite of the apparent similitude in the formal definition of the FTR and IFTR fading models, there are major differences between them, both in terms of the fitting results to experimental measurements and in the involved mathematical derivations. On the one hand, the IFTR fading model has been shown to provide a (sometimes remarkable) better fit than FTR fading (as well as other generalized fading models such as κ-µ shadowed [10] and two-wave with diffuse power -TWDP- [9]) to experimental data in very different environments, including line-of-sight (LOS) millimeter-wave, land-mobile satellites (LMS), and underwater acoustic communications (UAC) [5]. On the other hand, the independence of the two specular components in the IFTR model imposes new mathematical challenges, as now a two-fold nested integration always appear in its statistical characterization.…”

mentioning

confidence: 99%

“…Although both the probability density function (PDF) and cumulative distribution function (CDF) of the IFTR model were presented in [5], their use is rather limited for two reasons: on the one hand they are not completely general, as they require assuming one of the model parameters m 1 or m 2 to be integer, while they can take any arbitrary positive real value in realistic propagation scenarios; on the other hand, the known PDF and CDF are given in terms of a generalized hypergeometric function, which is actually a multifold infinite summation, which is very difficult to manipulate to obtain analytical expressions for most performance metrics in wireless communication systems.…”

mentioning

confidence: 99%

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Statistical Characterization of the Multicluster Two-Wave Fading Model

Olyaee¹,

Peña-Martín²,

López‐Martínez³

et al. 2022

2022 5th International Conference on Advanced Communication Technologies and Networking (CommNet)

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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 cochannel interference, and the bit error rate (BER), which are verified by Monte Carlo simulations.

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Section: New Representation Of the Iftr Fading Modelmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Statistical Characterization of the Multicluster Two-Wave Fading Model

Olyaee¹,

Peña-Martín²,

López‐Martínez³

et al. 2022

2022 5th International Conference on Advanced Communication Technologies and Networking (CommNet)

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show abstract

“…In the latter, the received signal is structured into clusters of waves, where each cluster is composed by groups of scattered waves with similar delays. Ray-based formulations include popular fading models in the literature suc as Durgin's Two-Wave with Diffuse Power (TWDP) [10] and other generalizations [11][12][13][14]. On the other hand, clusterbased models include Yacoub's κ-µ and η-µ models [6], ans subsequent extensions [8,[15][16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

The Lomax Distribution for Wireless Channel Modeling: Theory and Applications

Sánchez,

López-Martínez

2024

IEEE Open J. Veh. Technol.

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We investigate the application of the Lomax distribution for wireless fading modeling purposes. By a proper redefinition of its scale parameter, we present closed-form expressions for its main statistics: probability density function, cumulative distribution function, raw moments and Laplacedomain statistics. Then, relevant performance indicators are derived, including the amount of fading, channel capacity, outage probability and error rate. Other applications include diversity reception using selection combining, as well as composite fading modeling. The Lomax distribution is compared to the relevant case of Rayleigh fading, and to other benchmark distributions of similar complexity used in the literature.

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“…Recently, the independent fluctuating two-ray (IFTR) [8] channel model has been presented to characterize multipath propagation, which includes several well-known distributions, namely Rayleigh, Rician, Hoyt (Nakagami-q), Rician Shadowed, and Nakagami-m, as special or limiting cases. The IFTR model consists of two dominant (specular) waves plus a diffuse component, due to the aggregation of multiple low-power scattered waves, modeled as a complex Gaussian random variable (RV), where the specular components are assumed to fluctuate independently following Nakagami-m fading.…”

Section: Introductionmentioning

confidence: 99%

A Tractable Statistical Representation of IFTR Fading With Applications

Olyaee,

Hashemi,

Romero-Jerez

2024

IEEE Trans. Commun.

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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.

show abstract

The Fluctuating Two-Ray Fading Model With Independent Specular Components

Cited by 6 publications

References 20 publications

Statistical Characterization of the Multicluster Two-Wave Fading Model

Statistical Characterization of the Multicluster Two-Wave Fading Model

The Lomax Distribution for Wireless Channel Modeling: Theory and Applications

A Tractable Statistical Representation of IFTR Fading With Applications

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