Efficient Computation of Multivariate Rayleigh and Exponential Distributions
We propose an efficient approach for the computation of cumulative distribution functions of {N} correlated Rayleigh or exponential random variables (RVs) for arbitrary covariance matrices, which arise in the design and analysis of many wireless systems. Compared to the approaches in the literatur...
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| Veröffentlicht in: | IEEE wireless communications letters 2019-04, Vol.8 (2), p.456-459 |
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| container_title | IEEE wireless communications letters |
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| creator | Isaac, Reneeta Sara Mehta, Neelesh B. |
| description | We propose an efficient approach for the computation of cumulative distribution functions of {N} correlated Rayleigh or exponential random variables (RVs) for arbitrary covariance matrices, which arise in the design and analysis of many wireless systems. Compared to the approaches in the literature, it employs a fast and accurate randomized quasi-Monte Carlo method that markedly reduces the computational complexity by several orders of magnitude as {N} or the correlation among the RVs increases. Numerical results show that an order of magnitude larger values of {N} can now be computed for. Its application to the performance analysis of selection combining is also shown. |
| doi_str_mv | 10.1109/LWC.2018.2875999 |
| format | Article |
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Compared to the approaches in the literature, it employs a fast and accurate randomized quasi-Monte Carlo method that markedly reduces the computational complexity by several orders of magnitude as <inline-formula> <tex-math notation="LaTeX">{N} </tex-math></inline-formula> or the correlation among the RVs increases. Numerical results show that an order of magnitude larger values of <inline-formula> <tex-math notation="LaTeX">{N} </tex-math></inline-formula> can now be computed for. Its application to the performance analysis of selection combining is also shown.]]></description><identifier>ISSN: 2162-2337</identifier><identifier>EISSN: 2162-2345</identifier><identifier>DOI: 10.1109/LWC.2018.2875999</identifier><identifier>CODEN: IWCLAF</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Computational complexity ; Computational efficiency ; Computer simulation ; Convergence ; correlated fading ; Correlation ; Covariance matrices ; Covariance matrix ; cumulative distribution function ; Distribution functions ; exponential ; Monte Carlo simulation ; Multivariate ; Probability density function ; Random variables ; Rayleigh ; Relays ; Wireless communication</subject><ispartof>IEEE wireless communications letters, 2019-04, Vol.8 (2), p.456-459</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2019</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c291t-30ed92d6770571b05a1f097da8aadf0ee8e04eb60aa14ba2903b148ceead04a83</citedby><cites>FETCH-LOGICAL-c291t-30ed92d6770571b05a1f097da8aadf0ee8e04eb60aa14ba2903b148ceead04a83</cites><orcidid>0000-0002-2145-9262 ; 0000-0002-3614-049X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8491394$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>315,781,785,797,27929,27930,54763</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8491394$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Isaac, Reneeta Sara</creatorcontrib><creatorcontrib>Mehta, Neelesh B.</creatorcontrib><title>Efficient Computation of Multivariate Rayleigh and Exponential Distributions</title><title>IEEE wireless communications letters</title><addtitle>LWC</addtitle><description><![CDATA[We propose an efficient approach for the computation of cumulative distribution functions of <inline-formula> <tex-math notation="LaTeX">{N} </tex-math></inline-formula> correlated Rayleigh or exponential random variables (RVs) for arbitrary covariance matrices, which arise in the design and analysis of many wireless systems. Compared to the approaches in the literature, it employs a fast and accurate randomized quasi-Monte Carlo method that markedly reduces the computational complexity by several orders of magnitude as <inline-formula> <tex-math notation="LaTeX">{N} </tex-math></inline-formula> or the correlation among the RVs increases. Numerical results show that an order of magnitude larger values of <inline-formula> <tex-math notation="LaTeX">{N} </tex-math></inline-formula> can now be computed for. Its application to the performance analysis of selection combining is also shown.]]></description><subject>Computational complexity</subject><subject>Computational efficiency</subject><subject>Computer simulation</subject><subject>Convergence</subject><subject>correlated fading</subject><subject>Correlation</subject><subject>Covariance matrices</subject><subject>Covariance matrix</subject><subject>cumulative distribution function</subject><subject>Distribution functions</subject><subject>exponential</subject><subject>Monte Carlo simulation</subject><subject>Multivariate</subject><subject>Probability density function</subject><subject>Random variables</subject><subject>Rayleigh</subject><subject>Relays</subject><subject>Wireless communication</subject><issn>2162-2337</issn><issn>2162-2345</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE1LxDAQhoMouKx7F7wUPHedSb-So9T1AyqCKB7DtE01S7etSSruv7dlZefyzuF9ZuBh7BJhjQjypvjI1xxQrLnIEinlCVtwTHnIozg5Pe5Rds5Wzm1hmhSQo1iwYtM0pjK680He74bRkzd9F_RN8Dy23vyQNeR18Er7VpvPr4C6Otj8Dn03EYba4M44b005zpS7YGcNtU6v_nPJ3u83b_ljWLw8POW3RVhxiT6MQNeS12mWQZJhCQlhAzKrSRDVDWgtNMS6TIEI45K4hKjEWFRaUw0xiWjJrg93B9t_j9p5te1H200vFecIwEWMcwsOrcr2zlndqMGaHdm9QlCzNjVpU7M29a9tQq4OiNFaH-silhjJOPoDSABpZw</recordid><startdate>20190401</startdate><enddate>20190401</enddate><creator>Isaac, Reneeta Sara</creator><creator>Mehta, Neelesh B.</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>7SP</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-2145-9262</orcidid><orcidid>https://orcid.org/0000-0002-3614-049X</orcidid></search><sort><creationdate>20190401</creationdate><title>Efficient Computation of Multivariate Rayleigh and Exponential Distributions</title><author>Isaac, Reneeta Sara ; Mehta, Neelesh B.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c291t-30ed92d6770571b05a1f097da8aadf0ee8e04eb60aa14ba2903b148ceead04a83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Computational complexity</topic><topic>Computational efficiency</topic><topic>Computer simulation</topic><topic>Convergence</topic><topic>correlated fading</topic><topic>Correlation</topic><topic>Covariance matrices</topic><topic>Covariance matrix</topic><topic>cumulative distribution function</topic><topic>Distribution functions</topic><topic>exponential</topic><topic>Monte Carlo simulation</topic><topic>Multivariate</topic><topic>Probability density function</topic><topic>Random variables</topic><topic>Rayleigh</topic><topic>Relays</topic><topic>Wireless communication</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Isaac, Reneeta Sara</creatorcontrib><creatorcontrib>Mehta, Neelesh B.</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>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>IEEE wireless communications letters</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Isaac, Reneeta Sara</au><au>Mehta, Neelesh B.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Efficient Computation of Multivariate Rayleigh and Exponential Distributions</atitle><jtitle>IEEE wireless communications letters</jtitle><stitle>LWC</stitle><date>2019-04-01</date><risdate>2019</risdate><volume>8</volume><issue>2</issue><spage>456</spage><epage>459</epage><pages>456-459</pages><issn>2162-2337</issn><eissn>2162-2345</eissn><coden>IWCLAF</coden><abstract><![CDATA[We propose an efficient approach for the computation of cumulative distribution functions of <inline-formula> <tex-math notation="LaTeX">{N} </tex-math></inline-formula> correlated Rayleigh or exponential random variables (RVs) for arbitrary covariance matrices, which arise in the design and analysis of many wireless systems. Compared to the approaches in the literature, it employs a fast and accurate randomized quasi-Monte Carlo method that markedly reduces the computational complexity by several orders of magnitude as <inline-formula> <tex-math notation="LaTeX">{N} </tex-math></inline-formula> or the correlation among the RVs increases. Numerical results show that an order of magnitude larger values of <inline-formula> <tex-math notation="LaTeX">{N} </tex-math></inline-formula> can now be computed for. Its application to the performance analysis of selection combining is also shown.]]></abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/LWC.2018.2875999</doi><tpages>4</tpages><orcidid>https://orcid.org/0000-0002-2145-9262</orcidid><orcidid>https://orcid.org/0000-0002-3614-049X</orcidid></addata></record> |
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| source | IEEE Electronic Library (IEL) |
| subjects | Computational complexity Computational efficiency Computer simulation Convergence correlated fading Correlation Covariance matrices Covariance matrix cumulative distribution function Distribution functions exponential Monte Carlo simulation Multivariate Probability density function Random variables Rayleigh Relays Wireless communication |
| title | Efficient Computation of Multivariate Rayleigh and Exponential Distributions |
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