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...
Gespeichert in:
Veröffentlicht in: | IEEE transactions on wireless communications 2024-05, Vol.23 (5), p.4199-4213 |
---|---|
Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 4213 |
---|---|
container_issue | 5 |
container_start_page | 4199 |
container_title | IEEE transactions on wireless communications |
container_volume | 23 |
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. |
doi_str_mv | 10.1109/TWC.2023.3315732 |
format | Article |
fullrecord | <record><control><sourceid>proquest_RIE</sourceid><recordid>TN_cdi_ieee_primary_10268918</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>10268918</ieee_id><sourcerecordid>3053297941</sourcerecordid><originalsourceid>FETCH-LOGICAL-c287t-2915c58a1e7880477fbc5999adff4da51abd4271aa615df3da8e1ead4e7708cb3</originalsourceid><addsrcrecordid>eNpNkMFLwzAUh4MoOKd3Dx4KnlPzkqZJjlLcFDYEqXgMWfOqHXWdSYvsv7dlO3h6vwff7z34CLkFlgIw81B-FClnXKRCgFSCn5EZSKkp55k-n7LIKXCVX5KrGLeMgcqlnBFefmGyHtq-oUU7xB5DsmiHqh9c3-w-k_K3o2_ukCycn9Z157G9Jhe1ayPenOacvC-eyuKZrl6XL8XjilZcq55yA7KS2gEqrVmmVL2ppDHG-brOvJPgNj7jCpzLQfpaeKcR0PkMlWK62og5uT_e3YfuZ8DY2203hN340gomBTfKZDBS7EhVoYsxYG33ofl24WCB2cmMHc3YyYw9mRkrd8dKg4j_cJ5rA1r8AX_pXhI</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3053297941</pqid></control><display><type>article</type><title>The Multi-Cluster Fluctuating Two-Ray Fading Model</title><source>IEEE Electronic Library (IEL)</source><creator>Sanchez, Jose David Vega ; Lopez-Martinez, F. 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. 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.]]></description><identifier>ISSN: 1536-1276</identifier><identifier>EISSN: 1558-2248</identifier><identifier>DOI: 10.1109/TWC.2023.3315732</identifier><identifier>CODEN: ITWCAX</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>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</subject><ispartof>IEEE transactions on wireless communications, 2024-05, Vol.23 (5), p.4199-4213</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c287t-2915c58a1e7880477fbc5999adff4da51abd4271aa615df3da8e1ead4e7708cb3</cites><orcidid>0000-0001-5094-7735 ; 0000-0002-3305-1109 ; 0000-0003-0233-6942 ; 0000-0001-7844-4574</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/10268918$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/10268918$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Sanchez, Jose David Vega</creatorcontrib><creatorcontrib>Lopez-Martinez, F. Javier</creatorcontrib><creatorcontrib>Paris, Jose F.</creatorcontrib><creatorcontrib>Romero-Jerez, Juan M.</creatorcontrib><title>The Multi-Cluster Fluctuating Two-Ray Fading Model</title><title>IEEE transactions on wireless communications</title><addtitle>TWC</addtitle><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. 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.]]></description><subject>Analytical models</subject><subject>Channel models</subject><subject>Clusters</subject><subject>Distribution functions</subject><subject>Fading</subject><subject>Fading channels</subject><subject>fluctuating two-ray</subject><subject>Formulations</subject><subject>Generalized fading channels</subject><subject>Mathematical models</subject><subject>Mixtures</subject><subject>moment generating function</subject><subject>multipath propagation</subject><subject>Probability density function</subject><subject>Probability density functions</subject><subject>Rician channels</subject><subject>wireless channel modeling</subject><subject>Wireless communication</subject><subject>Wireless communication systems</subject><issn>1536-1276</issn><issn>1558-2248</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkMFLwzAUh4MoOKd3Dx4KnlPzkqZJjlLcFDYEqXgMWfOqHXWdSYvsv7dlO3h6vwff7z34CLkFlgIw81B-FClnXKRCgFSCn5EZSKkp55k-n7LIKXCVX5KrGLeMgcqlnBFefmGyHtq-oUU7xB5DsmiHqh9c3-w-k_K3o2_ukCycn9Z157G9Jhe1ayPenOacvC-eyuKZrl6XL8XjilZcq55yA7KS2gEqrVmmVL2ppDHG-brOvJPgNj7jCpzLQfpaeKcR0PkMlWK62og5uT_e3YfuZ8DY2203hN340gomBTfKZDBS7EhVoYsxYG33ofl24WCB2cmMHc3YyYw9mRkrd8dKg4j_cJ5rA1r8AX_pXhI</recordid><startdate>202405</startdate><enddate>202405</enddate><creator>Sanchez, Jose David Vega</creator><creator>Lopez-Martinez, F. Javier</creator><creator>Paris, Jose F.</creator><creator>Romero-Jerez, Juan M.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><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></search><sort><creationdate>202405</creationdate><title>The Multi-Cluster Fluctuating Two-Ray Fading Model</title><author>Sanchez, Jose David Vega ; Lopez-Martinez, F. Javier ; Paris, Jose F. ; Romero-Jerez, Juan M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c287t-2915c58a1e7880477fbc5999adff4da51abd4271aa615df3da8e1ead4e7708cb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Analytical models</topic><topic>Channel models</topic><topic>Clusters</topic><topic>Distribution functions</topic><topic>Fading</topic><topic>Fading channels</topic><topic>fluctuating two-ray</topic><topic>Formulations</topic><topic>Generalized fading channels</topic><topic>Mathematical models</topic><topic>Mixtures</topic><topic>moment generating function</topic><topic>multipath propagation</topic><topic>Probability density function</topic><topic>Probability density functions</topic><topic>Rician channels</topic><topic>wireless channel modeling</topic><topic>Wireless communication</topic><topic>Wireless communication systems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sanchez, Jose David Vega</creatorcontrib><creatorcontrib>Lopez-Martinez, F. 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 & 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> |
fulltext | fulltext_linktorsrc |
identifier | ISSN: 1536-1276 |
ispartof | IEEE transactions on wireless communications, 2024-05, Vol.23 (5), p.4199-4213 |
issn | 1536-1276 1558-2248 |
language | eng |
recordid | cdi_ieee_primary_10268918 |
source | IEEE Electronic Library (IEL) |
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 |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-08T12%3A48%3A07IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_RIE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=The%20Multi-Cluster%20Fluctuating%20Two-Ray%20Fading%20Model&rft.jtitle=IEEE%20transactions%20on%20wireless%20communications&rft.au=Sanchez,%20Jose%20David%20Vega&rft.date=2024-05&rft.volume=23&rft.issue=5&rft.spage=4199&rft.epage=4213&rft.pages=4199-4213&rft.issn=1536-1276&rft.eissn=1558-2248&rft.coden=ITWCAX&rft_id=info:doi/10.1109/TWC.2023.3315732&rft_dat=%3Cproquest_RIE%3E3053297941%3C/proquest_RIE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3053297941&rft_id=info:pmid/&rft_ieee_id=10268918&rfr_iscdi=true |