On the Nakagami-m Inverse Cumulative Distribution Function: Closed-Form Expression and Its Optimization by Backtracking Search Optimization Algorithm

Abstract The inverse cumulative distribution function (CDF) is utilized in several areas such as statistical applications, Monte Carlo methods and communication systems. In wireless communications, the Nakagami-m inverse CDF is widely used to obtain outage probabilities of systems. However, calculat...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Kabalci, Yasin [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2016

Schlagwörter:	Inverse cumulative distribution function Nakagami- distribution Evolutionary algorithm backtracking search optimization algorithm

Übergeordnetes Werk:	Enthalten in: Wireless personal communications - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994, 91(2016), 1 vom: 29. Juni, Seite 1-8
Übergeordnetes Werk:	volume:91 ; year:2016 ; number:1 ; day:29 ; month:06 ; pages:1-8

Links:	Volltext

DOI / URN:	10.1007/s11277-016-3439-x

Katalog-ID:	SPR018576591

Internformat


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520			\|a Abstract The inverse cumulative distribution function (CDF) is utilized in several areas such as statistical applications, Monte Carlo methods and communication systems. In wireless communications, the Nakagami-m inverse CDF is widely used to obtain outage probabilities of systems. However, calculation of the Nakagami-m inverse CDF is troublesome and there is no a closed-form expression. Simpler and more accurate approximation for the Nakagami-m inverse CDF is derived in this paper. Moreover, coefficients of the proposed approximation are optimized by using backtracking search optimization algorithm which is a new evolutionary algorithm to solve optimization problems. The obtained results show that the proposed approximation and exact values of the Nakagami-m inverse CDF are in well agreement for all cases.
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650		4	\|a distribution \|7 (dpeaa)DE-He213
650		4	\|a Evolutionary algorithm backtracking search optimization algorithm \|7 (dpeaa)DE-He213
773	0	8	\|i Enthalten in \|t Wireless personal communications \|d Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 \|g 91(2016), 1 vom: 29. Juni, Seite 1-8 \|w (DE-627)271179120 \|w (DE-600)1479327-1 \|x 1572-834X \|7 nnns
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912			\|a GBV_ILN_95
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912			\|a GBV_ILN_120
912			\|a GBV_ILN_138
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912			\|a GBV_ILN_213
912			\|a GBV_ILN_224
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912			\|a GBV_ILN_250
912			\|a GBV_ILN_281
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912			\|a GBV_ILN_602
912			\|a GBV_ILN_636
912			\|a GBV_ILN_702
912			\|a GBV_ILN_2001
912			\|a GBV_ILN_2003
912			\|a GBV_ILN_2004
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912			\|a GBV_ILN_2008
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912			\|a GBV_ILN_2011
912			\|a GBV_ILN_2014
912			\|a GBV_ILN_2015
912			\|a GBV_ILN_2020
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912			\|a GBV_ILN_2031
912			\|a GBV_ILN_2034
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912			\|a GBV_ILN_2050
912			\|a GBV_ILN_2055
912			\|a GBV_ILN_2057
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912			\|a GBV_ILN_2064
912			\|a GBV_ILN_2065
912			\|a GBV_ILN_2068
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912			\|a GBV_ILN_2086
912			\|a GBV_ILN_2088
912			\|a GBV_ILN_2093
912			\|a GBV_ILN_2106
912			\|a GBV_ILN_2107
912			\|a GBV_ILN_2108
912			\|a GBV_ILN_2110
912			\|a GBV_ILN_2111
912			\|a GBV_ILN_2112
912			\|a GBV_ILN_2113
912			\|a GBV_ILN_2116
912			\|a GBV_ILN_2118
912			\|a GBV_ILN_2119
912			\|a GBV_ILN_2122
912			\|a GBV_ILN_2129
912			\|a GBV_ILN_2143
912			\|a GBV_ILN_2144
912			\|a GBV_ILN_2147
912			\|a GBV_ILN_2148
912			\|a GBV_ILN_2152
912			\|a GBV_ILN_2153
912			\|a GBV_ILN_2188
912			\|a GBV_ILN_2190
912			\|a GBV_ILN_2232
912			\|a GBV_ILN_2336
912			\|a GBV_ILN_2446
912			\|a GBV_ILN_2470
912			\|a GBV_ILN_2472
912			\|a GBV_ILN_2507
912			\|a GBV_ILN_2522
912			\|a GBV_ILN_2548
912			\|a GBV_ILN_4012
912			\|a GBV_ILN_4035
912			\|a GBV_ILN_4037
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912			\|a GBV_ILN_4112
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912			\|a GBV_ILN_4334
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matchkey_str	article:1572834X:2016----::nhnkgmmnescmltvdsrbtofntocoefrepesoadtotmztobbct
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allfields	10.1007/s11277-016-3439-x doi (DE-627)SPR018576591 (SPR)s11277-016-3439-x-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Kabalci, Yasin verfasserin aut On the Nakagami-m Inverse Cumulative Distribution Function: Closed-Form Expression and Its Optimization by Backtracking Search Optimization Algorithm 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The inverse cumulative distribution function (CDF) is utilized in several areas such as statistical applications, Monte Carlo methods and communication systems. In wireless communications, the Nakagami-m inverse CDF is widely used to obtain outage probabilities of systems. However, calculation of the Nakagami-m inverse CDF is troublesome and there is no a closed-form expression. Simpler and more accurate approximation for the Nakagami-m inverse CDF is derived in this paper. Moreover, coefficients of the proposed approximation are optimized by using backtracking search optimization algorithm which is a new evolutionary algorithm to solve optimization problems. The obtained results show that the proposed approximation and exact values of the Nakagami-m inverse CDF are in well agreement for all cases. Inverse cumulative distribution function (dpeaa)DE-He213 Nakagami- (dpeaa)DE-He213 distribution (dpeaa)DE-He213 Evolutionary algorithm backtracking search optimization algorithm (dpeaa)DE-He213 Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 91(2016), 1 vom: 29. Juni, Seite 1-8 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:91 year:2016 number:1 day:29 month:06 pages:1-8 https://dx.doi.org/10.1007/s11277-016-3439-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 53.00 ASE AR 91 2016 1 29 06 1-8
spelling	10.1007/s11277-016-3439-x doi (DE-627)SPR018576591 (SPR)s11277-016-3439-x-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Kabalci, Yasin verfasserin aut On the Nakagami-m Inverse Cumulative Distribution Function: Closed-Form Expression and Its Optimization by Backtracking Search Optimization Algorithm 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The inverse cumulative distribution function (CDF) is utilized in several areas such as statistical applications, Monte Carlo methods and communication systems. In wireless communications, the Nakagami-m inverse CDF is widely used to obtain outage probabilities of systems. However, calculation of the Nakagami-m inverse CDF is troublesome and there is no a closed-form expression. Simpler and more accurate approximation for the Nakagami-m inverse CDF is derived in this paper. Moreover, coefficients of the proposed approximation are optimized by using backtracking search optimization algorithm which is a new evolutionary algorithm to solve optimization problems. The obtained results show that the proposed approximation and exact values of the Nakagami-m inverse CDF are in well agreement for all cases. Inverse cumulative distribution function (dpeaa)DE-He213 Nakagami- (dpeaa)DE-He213 distribution (dpeaa)DE-He213 Evolutionary algorithm backtracking search optimization algorithm (dpeaa)DE-He213 Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 91(2016), 1 vom: 29. Juni, Seite 1-8 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:91 year:2016 number:1 day:29 month:06 pages:1-8 https://dx.doi.org/10.1007/s11277-016-3439-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 53.00 ASE AR 91 2016 1 29 06 1-8
allfields_unstemmed	10.1007/s11277-016-3439-x doi (DE-627)SPR018576591 (SPR)s11277-016-3439-x-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Kabalci, Yasin verfasserin aut On the Nakagami-m Inverse Cumulative Distribution Function: Closed-Form Expression and Its Optimization by Backtracking Search Optimization Algorithm 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The inverse cumulative distribution function (CDF) is utilized in several areas such as statistical applications, Monte Carlo methods and communication systems. In wireless communications, the Nakagami-m inverse CDF is widely used to obtain outage probabilities of systems. However, calculation of the Nakagami-m inverse CDF is troublesome and there is no a closed-form expression. Simpler and more accurate approximation for the Nakagami-m inverse CDF is derived in this paper. Moreover, coefficients of the proposed approximation are optimized by using backtracking search optimization algorithm which is a new evolutionary algorithm to solve optimization problems. The obtained results show that the proposed approximation and exact values of the Nakagami-m inverse CDF are in well agreement for all cases. Inverse cumulative distribution function (dpeaa)DE-He213 Nakagami- (dpeaa)DE-He213 distribution (dpeaa)DE-He213 Evolutionary algorithm backtracking search optimization algorithm (dpeaa)DE-He213 Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 91(2016), 1 vom: 29. Juni, Seite 1-8 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:91 year:2016 number:1 day:29 month:06 pages:1-8 https://dx.doi.org/10.1007/s11277-016-3439-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 53.00 ASE AR 91 2016 1 29 06 1-8
allfieldsGer	10.1007/s11277-016-3439-x doi (DE-627)SPR018576591 (SPR)s11277-016-3439-x-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Kabalci, Yasin verfasserin aut On the Nakagami-m Inverse Cumulative Distribution Function: Closed-Form Expression and Its Optimization by Backtracking Search Optimization Algorithm 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The inverse cumulative distribution function (CDF) is utilized in several areas such as statistical applications, Monte Carlo methods and communication systems. In wireless communications, the Nakagami-m inverse CDF is widely used to obtain outage probabilities of systems. However, calculation of the Nakagami-m inverse CDF is troublesome and there is no a closed-form expression. Simpler and more accurate approximation for the Nakagami-m inverse CDF is derived in this paper. Moreover, coefficients of the proposed approximation are optimized by using backtracking search optimization algorithm which is a new evolutionary algorithm to solve optimization problems. The obtained results show that the proposed approximation and exact values of the Nakagami-m inverse CDF are in well agreement for all cases. Inverse cumulative distribution function (dpeaa)DE-He213 Nakagami- (dpeaa)DE-He213 distribution (dpeaa)DE-He213 Evolutionary algorithm backtracking search optimization algorithm (dpeaa)DE-He213 Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 91(2016), 1 vom: 29. Juni, Seite 1-8 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:91 year:2016 number:1 day:29 month:06 pages:1-8 https://dx.doi.org/10.1007/s11277-016-3439-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 53.00 ASE AR 91 2016 1 29 06 1-8
allfieldsSound	10.1007/s11277-016-3439-x doi (DE-627)SPR018576591 (SPR)s11277-016-3439-x-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Kabalci, Yasin verfasserin aut On the Nakagami-m Inverse Cumulative Distribution Function: Closed-Form Expression and Its Optimization by Backtracking Search Optimization Algorithm 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The inverse cumulative distribution function (CDF) is utilized in several areas such as statistical applications, Monte Carlo methods and communication systems. In wireless communications, the Nakagami-m inverse CDF is widely used to obtain outage probabilities of systems. However, calculation of the Nakagami-m inverse CDF is troublesome and there is no a closed-form expression. Simpler and more accurate approximation for the Nakagami-m inverse CDF is derived in this paper. Moreover, coefficients of the proposed approximation are optimized by using backtracking search optimization algorithm which is a new evolutionary algorithm to solve optimization problems. The obtained results show that the proposed approximation and exact values of the Nakagami-m inverse CDF are in well agreement for all cases. Inverse cumulative distribution function (dpeaa)DE-He213 Nakagami- (dpeaa)DE-He213 distribution (dpeaa)DE-He213 Evolutionary algorithm backtracking search optimization algorithm (dpeaa)DE-He213 Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 91(2016), 1 vom: 29. Juni, Seite 1-8 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:91 year:2016 number:1 day:29 month:06 pages:1-8 https://dx.doi.org/10.1007/s11277-016-3439-x lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 53.00 ASE AR 91 2016 1 29 06 1-8
language	English
source	Enthalten in Wireless personal communications 91(2016), 1 vom: 29. Juni, Seite 1-8 volume:91 year:2016 number:1 day:29 month:06 pages:1-8
sourceStr	Enthalten in Wireless personal communications 91(2016), 1 vom: 29. Juni, Seite 1-8 volume:91 year:2016 number:1 day:29 month:06 pages:1-8
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Inverse cumulative distribution function Nakagami- distribution Evolutionary algorithm backtracking search optimization algorithm
dewey-raw	620
isfreeaccess_bool	false
container_title	Wireless personal communications
authorswithroles_txt_mv	Kabalci, Yasin @@aut@@
publishDateDaySort_date	2016-06-29T00:00:00Z
hierarchy_top_id	271179120
dewey-sort	3620
id	SPR018576591
language_de	englisch
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author	Kabalci, Yasin
spellingShingle	Kabalci, Yasin ddc 620 bkl 53.00 misc Inverse cumulative distribution function misc Nakagami- misc distribution misc Evolutionary algorithm backtracking search optimization algorithm On the Nakagami-m Inverse Cumulative Distribution Function: Closed-Form Expression and Its Optimization by Backtracking Search Optimization Algorithm
authorStr	Kabalci, Yasin
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topic_title	620 ASE 53.00 bkl On the Nakagami-m Inverse Cumulative Distribution Function: Closed-Form Expression and Its Optimization by Backtracking Search Optimization Algorithm Inverse cumulative distribution function (dpeaa)DE-He213 Nakagami- (dpeaa)DE-He213 distribution (dpeaa)DE-He213 Evolutionary algorithm backtracking search optimization algorithm (dpeaa)DE-He213
topic	ddc 620 bkl 53.00 misc Inverse cumulative distribution function misc Nakagami- misc distribution misc Evolutionary algorithm backtracking search optimization algorithm
topic_unstemmed	ddc 620 bkl 53.00 misc Inverse cumulative distribution function misc Nakagami- misc distribution misc Evolutionary algorithm backtracking search optimization algorithm
topic_browse	ddc 620 bkl 53.00 misc Inverse cumulative distribution function misc Nakagami- misc distribution misc Evolutionary algorithm backtracking search optimization algorithm
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title	On the Nakagami-m Inverse Cumulative Distribution Function: Closed-Form Expression and Its Optimization by Backtracking Search Optimization Algorithm
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title_full	On the Nakagami-m Inverse Cumulative Distribution Function: Closed-Form Expression and Its Optimization by Backtracking Search Optimization Algorithm
author_sort	Kabalci, Yasin
journal	Wireless personal communications
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title_sort	on the nakagami-m inverse cumulative distribution function: closed-form expression and its optimization by backtracking search optimization algorithm
title_auth	On the Nakagami-m Inverse Cumulative Distribution Function: Closed-Form Expression and Its Optimization by Backtracking Search Optimization Algorithm
abstract	Abstract The inverse cumulative distribution function (CDF) is utilized in several areas such as statistical applications, Monte Carlo methods and communication systems. In wireless communications, the Nakagami-m inverse CDF is widely used to obtain outage probabilities of systems. However, calculation of the Nakagami-m inverse CDF is troublesome and there is no a closed-form expression. Simpler and more accurate approximation for the Nakagami-m inverse CDF is derived in this paper. Moreover, coefficients of the proposed approximation are optimized by using backtracking search optimization algorithm which is a new evolutionary algorithm to solve optimization problems. The obtained results show that the proposed approximation and exact values of the Nakagami-m inverse CDF are in well agreement for all cases.
abstractGer	Abstract The inverse cumulative distribution function (CDF) is utilized in several areas such as statistical applications, Monte Carlo methods and communication systems. In wireless communications, the Nakagami-m inverse CDF is widely used to obtain outage probabilities of systems. However, calculation of the Nakagami-m inverse CDF is troublesome and there is no a closed-form expression. Simpler and more accurate approximation for the Nakagami-m inverse CDF is derived in this paper. Moreover, coefficients of the proposed approximation are optimized by using backtracking search optimization algorithm which is a new evolutionary algorithm to solve optimization problems. The obtained results show that the proposed approximation and exact values of the Nakagami-m inverse CDF are in well agreement for all cases.
abstract_unstemmed	Abstract The inverse cumulative distribution function (CDF) is utilized in several areas such as statistical applications, Monte Carlo methods and communication systems. In wireless communications, the Nakagami-m inverse CDF is widely used to obtain outage probabilities of systems. However, calculation of the Nakagami-m inverse CDF is troublesome and there is no a closed-form expression. Simpler and more accurate approximation for the Nakagami-m inverse CDF is derived in this paper. Moreover, coefficients of the proposed approximation are optimized by using backtracking search optimization algorithm which is a new evolutionary algorithm to solve optimization problems. The obtained results show that the proposed approximation and exact values of the Nakagami-m inverse CDF are in well agreement for all cases.
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title_short	On the Nakagami-m Inverse Cumulative Distribution Function: Closed-Form Expression and Its Optimization by Backtracking Search Optimization Algorithm
url	https://dx.doi.org/10.1007/s11277-016-3439-x
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doi_str	10.1007/s11277-016-3439-x
up_date	2024-07-03T20:42:05.726Z
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In wireless communications, the Nakagami-m inverse CDF is widely used to obtain outage probabilities of systems. However, calculation of the Nakagami-m inverse CDF is troublesome and there is no a closed-form expression. Simpler and more accurate approximation for the Nakagami-m inverse CDF is derived in this paper. Moreover, coefficients of the proposed approximation are optimized by using backtracking search optimization algorithm which is a new evolutionary algorithm to solve optimization problems. 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On the Nakagami-m Inverse Cumulative Distribution Function: Closed-Form Expression and Its Optimization by Backtracking Search Optimization Algorithm

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