The Multi-Cluster Fluctuating Two-Ray Fading Model
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Vega Sánchez, José David; López-Martínez, F. Javier; Paris, José F.; Moreno Jerez, Juan ManuelEditorial
IEEE
Materia
Generalized fading channels wireless channel modeling moment generating function
Date
2024-05-05Referencia bibliográfica
Vega Sánchez, J.D. et. al. IEEE Transactions on Wireless Communication. [https://doi.org/10.1109/TWC.2023.3315732]
Sponsorship
Junta de Andalucía, the European Union; European Fund for Regional Development Fund—FEDER under Grant EMERGIA20-00297; Grant P21-00420; Grant P18-RT-3175; MCIN/AEI/10.13039/501100011033 under Grant PID2020- 118139RB-I00Abstract
We introduce and characterize the Multi-cluster
Fluctuating Two-Ray (MFTR) fading channel, generalizing both
the fluctuating two-ray (FTR) and the κ-μ shadowed fading models
through a more general yet equally mathematically tractable
model. We derive all the chief probability functions of the MFTR
model such as probability density function (PDF), cumulative
distribution function (CDF), and moment generating function
(MGF) in closed-form, having a mathematical complexity similar
to other fading models in the state-of-the-art.We also provide two
additional analytical formulations for the PDF and the CDF: (i) in
terms of a continuous mixture of κ-μ shadowed distributions, and
(ii) as an infinite discrete mixture of Gamma distributions. Such
expressions enable to conduct performance analysis under MFTR
fading by directly leveraging readily available results for the κ-μ
shadowed or Nakagami-m cases, respectively. We demonstrate
that the MFTR fading model provides a much better fit than
FTR and κ-μ shadowed models for small-scale measurements of
channel amplitude in outdoor Terahertz (THz) wireless links.
Finally, the performance of wireless communications systems
undergoing MFTR fading is exemplified in terms of classical
benchmarking metrics like the outage probability, both in exact
and asymptotic forms, and the amount of fading.