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On Monte Carlo Simulation of the Bit Error Rate
Simulation, point estimation, and interval estimation of the bit error rate are rigorously examined. Exact confidence intervals based on the F-distribution approximation for the binomial and negative binomial distributions are derived. Simulations demonstrate 1) that the analysis gives accurate conf...
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creator | Mazzeo, B. Rice, M. |
description | Simulation, point estimation, and interval estimation of the bit error rate are rigorously examined. Exact confidence intervals based on the F-distribution approximation for the binomial and negative binomial distributions are derived. Simulations demonstrate 1) that the analysis gives accurate confidence intervals for bit error rate estimators and 2) that the performance of the binomial and negative binomial estimators give similar performance. The negative binomial estimator has the advantage that an a priori estimate or guess of the true bit error probability is not required. |
doi_str_mv | 10.1109/icc.2011.5963099 |
format | conference_proceeding |
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Exact confidence intervals based on the F-distribution approximation for the binomial and negative binomial distributions are derived. Simulations demonstrate 1) that the analysis gives accurate confidence intervals for bit error rate estimators and 2) that the performance of the binomial and negative binomial estimators give similar performance. The negative binomial estimator has the advantage that an a priori estimate or guess of the true bit error probability is not required.</description><identifier>ISSN: 1550-3607</identifier><identifier>ISBN: 9781612842325</identifier><identifier>ISBN: 1612842321</identifier><identifier>EISSN: 1938-1883</identifier><identifier>EISBN: 161284233X</identifier><identifier>EISBN: 9781612842318</identifier><identifier>EISBN: 9781612842332</identifier><identifier>EISBN: 1612842313</identifier><identifier>DOI: 10.1109/icc.2011.5963099</identifier><language>eng</language><publisher>IEEE</publisher><subject>Approximation methods ; Bit error rate ; Equations ; Error probability ; IEEE Communications Society ; Maximum likelihood estimation ; Random variables</subject><ispartof>2011 IEEE International Conference on Communications (ICC), 2011, p.1-5</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5963099$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54555,54920,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5963099$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Mazzeo, B.</creatorcontrib><creatorcontrib>Rice, M.</creatorcontrib><title>On Monte Carlo Simulation of the Bit Error Rate</title><title>2011 IEEE International Conference on Communications (ICC)</title><addtitle>icc</addtitle><description>Simulation, point estimation, and interval estimation of the bit error rate are rigorously examined. Exact confidence intervals based on the F-distribution approximation for the binomial and negative binomial distributions are derived. Simulations demonstrate 1) that the analysis gives accurate confidence intervals for bit error rate estimators and 2) that the performance of the binomial and negative binomial estimators give similar performance. The negative binomial estimator has the advantage that an a priori estimate or guess of the true bit error probability is not required.</description><subject>Approximation methods</subject><subject>Bit error rate</subject><subject>Equations</subject><subject>Error probability</subject><subject>IEEE Communications Society</subject><subject>Maximum likelihood estimation</subject><subject>Random variables</subject><issn>1550-3607</issn><issn>1938-1883</issn><isbn>9781612842325</isbn><isbn>1612842321</isbn><isbn>161284233X</isbn><isbn>9781612842318</isbn><isbn>9781612842332</isbn><isbn>1612842313</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1j0tLAzEURuMLbGv3gpv8gZnmJnPzWGqpD6gUfIC7ktdgZDojmbjw37dgPZtvceCDQ8g1sBqAmUXyvuYMoEYjBTPmhExBAtcNF-LjlEzACF2B1uKMzI3S_47j-cEhskpIpi7JdBy_GENuBEzIYtPT56EvkS5t7gb6mnY_nS1p6OnQ0vIZ6V0qdJXzkOmLLfGKXLS2G-P8uDPyfr96Wz5W683D0_J2XSVQWCrPXAvOg7MoDiBzEnXQHiMy67wOyhgEHnyAIAI0jVTcGGbQOxukimJGbv5-U4xx-53Tzubf7TFc7AH06UZL</recordid><startdate>201106</startdate><enddate>201106</enddate><creator>Mazzeo, B.</creator><creator>Rice, M.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201106</creationdate><title>On Monte Carlo Simulation of the Bit Error Rate</title><author>Mazzeo, B. ; Rice, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-c0bf1bc1ba5333350b658d8c5e50abc8d799512dcd1d3d14467299095cbad67e3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Approximation methods</topic><topic>Bit error rate</topic><topic>Equations</topic><topic>Error probability</topic><topic>IEEE Communications Society</topic><topic>Maximum likelihood estimation</topic><topic>Random variables</topic><toplevel>online_resources</toplevel><creatorcontrib>Mazzeo, B.</creatorcontrib><creatorcontrib>Rice, M.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEL</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Mazzeo, B.</au><au>Rice, M.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>On Monte Carlo Simulation of the Bit Error Rate</atitle><btitle>2011 IEEE International Conference on Communications (ICC)</btitle><stitle>icc</stitle><date>2011-06</date><risdate>2011</risdate><spage>1</spage><epage>5</epage><pages>1-5</pages><issn>1550-3607</issn><eissn>1938-1883</eissn><isbn>9781612842325</isbn><isbn>1612842321</isbn><eisbn>161284233X</eisbn><eisbn>9781612842318</eisbn><eisbn>9781612842332</eisbn><eisbn>1612842313</eisbn><abstract>Simulation, point estimation, and interval estimation of the bit error rate are rigorously examined. Exact confidence intervals based on the F-distribution approximation for the binomial and negative binomial distributions are derived. Simulations demonstrate 1) that the analysis gives accurate confidence intervals for bit error rate estimators and 2) that the performance of the binomial and negative binomial estimators give similar performance. The negative binomial estimator has the advantage that an a priori estimate or guess of the true bit error probability is not required.</abstract><pub>IEEE</pub><doi>10.1109/icc.2011.5963099</doi><tpages>5</tpages></addata></record> |
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subjects | Approximation methods Bit error rate Equations Error probability IEEE Communications Society Maximum likelihood estimation Random variables |
title | On Monte Carlo Simulation of the Bit Error Rate |
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