The Multi-Cluster Fluctuating Two-Ray Fading Model

We introduce and characterize the Multi-cluster Fluctuating Two-Ray (MFTR) fading channel, generalizing both the fluctuating two-ray (FTR) and the \kappa - \mu shadowed fading models through a more general yet equally mathematically tractable model. We derive all the chief probability functions of...

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Veröffentlicht in:IEEE transactions on wireless communications 2024-05, Vol.23 (5), p.4199-4213
Hauptverfasser: Sanchez, Jose David Vega, Lopez-Martinez, F. Javier, Paris, Jose F., Romero-Jerez, Juan M.
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creator Sanchez, Jose David Vega
Lopez-Martinez, F. Javier
Paris, Jose F.
Romero-Jerez, Juan M.
description We introduce and characterize the Multi-cluster Fluctuating Two-Ray (MFTR) fading channel, generalizing both the fluctuating two-ray (FTR) and the \kappa - \mu 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 \kappa - \mu 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 \kappa - \mu shadowed or Nakagami- m cases, respectively. We demonstrate that the MFTR fading model provides a much better fit than FTR and \kappa - \mu 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.
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Javier ; Paris, Jose F. ; Romero-Jerez, Juan M.</creator><creatorcontrib>Sanchez, Jose David Vega ; Lopez-Martinez, F. Javier ; Paris, Jose F. ; Romero-Jerez, Juan M.</creatorcontrib><description><![CDATA[We introduce and characterize the Multi-cluster Fluctuating Two-Ray (MFTR) fading channel, generalizing both the fluctuating two-ray (FTR) and the <inline-formula> <tex-math notation="LaTeX">\kappa </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">\mu </tex-math></inline-formula> 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: (<inline-formula> <tex-math notation="LaTeX">{i} </tex-math></inline-formula>) in terms of a continuous mixture of <inline-formula> <tex-math notation="LaTeX">\kappa </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">\mu </tex-math></inline-formula> 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 <inline-formula> <tex-math notation="LaTeX">\kappa </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">\mu </tex-math></inline-formula> shadowed or Nakagami-<inline-formula> <tex-math notation="LaTeX">m </tex-math></inline-formula> cases, respectively. We demonstrate that the MFTR fading model provides a much better fit than FTR and <inline-formula> <tex-math notation="LaTeX">\kappa </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">\mu </tex-math></inline-formula> shadowed models for small-scale measurements of channel amplitude in outdoor Terahertz (THz) wireless links. 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We also provide two additional analytical formulations for the PDF and the CDF: (<inline-formula> <tex-math notation="LaTeX">{i} </tex-math></inline-formula>) in terms of a continuous mixture of <inline-formula> <tex-math notation="LaTeX">\kappa </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">\mu </tex-math></inline-formula> 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 <inline-formula> <tex-math notation="LaTeX">\kappa </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">\mu </tex-math></inline-formula> shadowed or Nakagami-<inline-formula> <tex-math notation="LaTeX">m </tex-math></inline-formula> cases, respectively. We demonstrate that the MFTR fading model provides a much better fit than FTR and <inline-formula> <tex-math notation="LaTeX">\kappa </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">\mu </tex-math></inline-formula> shadowed models for small-scale measurements of channel amplitude in outdoor Terahertz (THz) wireless links. 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Javier</creatorcontrib><creatorcontrib>Paris, Jose F.</creatorcontrib><creatorcontrib>Romero-Jerez, Juan M.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on wireless communications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Sanchez, Jose David Vega</au><au>Lopez-Martinez, F. Javier</au><au>Paris, Jose F.</au><au>Romero-Jerez, Juan M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Multi-Cluster Fluctuating Two-Ray Fading Model</atitle><jtitle>IEEE transactions on wireless communications</jtitle><stitle>TWC</stitle><date>2024-05</date><risdate>2024</risdate><volume>23</volume><issue>5</issue><spage>4199</spage><epage>4213</epage><pages>4199-4213</pages><issn>1536-1276</issn><eissn>1558-2248</eissn><coden>ITWCAX</coden><abstract><![CDATA[We introduce and characterize the Multi-cluster Fluctuating Two-Ray (MFTR) fading channel, generalizing both the fluctuating two-ray (FTR) and the <inline-formula> <tex-math notation="LaTeX">\kappa </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">\mu </tex-math></inline-formula> 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: (<inline-formula> <tex-math notation="LaTeX">{i} </tex-math></inline-formula>) in terms of a continuous mixture of <inline-formula> <tex-math notation="LaTeX">\kappa </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">\mu </tex-math></inline-formula> 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 <inline-formula> <tex-math notation="LaTeX">\kappa </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">\mu </tex-math></inline-formula> shadowed or Nakagami-<inline-formula> <tex-math notation="LaTeX">m </tex-math></inline-formula> cases, respectively. We demonstrate that the MFTR fading model provides a much better fit than FTR and <inline-formula> <tex-math notation="LaTeX">\kappa </tex-math></inline-formula>-<inline-formula> <tex-math notation="LaTeX">\mu </tex-math></inline-formula> 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.]]></abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TWC.2023.3315732</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0001-5094-7735</orcidid><orcidid>https://orcid.org/0000-0002-3305-1109</orcidid><orcidid>https://orcid.org/0000-0003-0233-6942</orcidid><orcidid>https://orcid.org/0000-0001-7844-4574</orcidid><oa>free_for_read</oa></addata></record>
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subjects Analytical models
Channel models
Clusters
Distribution functions
Fading
Fading channels
fluctuating two-ray
Formulations
Generalized fading channels
Mathematical models
Mixtures
moment generating function
multipath propagation
Probability density function
Probability density functions
Rician channels
wireless channel modeling
Wireless communication
Wireless communication systems
title The Multi-Cluster Fluctuating Two-Ray Fading Model
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