Random Graph Coloring-Based Resource Allocation for Achieving User Level Fairness in Femtocellular LTE-A Networks

Abstract Increasing demand of high data rates and spectral efficiency is sailing next generation wireless networks toward smaller cells structure known as femtocells with air interference technology known as orthogonal frequency division multiple access. To mitigate the high cost of cellular long term evolution-advanced (LTE-A) operators and poor indoor coverage, femtocell network structure has been proposed for underlaying evolved Node-B. Resource allocation, interference management and user level fairness are among the main problems for underlaying femtocellular network deployment. Radio resource management problem becomes even more complicated, when randomly deployed femtocells serve large number of users within total available physical resource blocks (PRBs) of LTE-A networks. To solve the radio resource management problem efficiently for accommodating maximum number of users within total available PRBs, network interference in femtocellular network is modeled as Bernoulli random graph model. A bound over required number of PRBs in the network has been established based on number of users connected with each femtocell and their interference relation with other femtocells. In this paper we have proposed the priorities greedy graph coloring based resource allocation algorithm for femtocellular LTE-A networks. The proposed algorithm accommodate maximum number of users, satisfies the total available PRBs, interference and user level fairness in the femtocellular networks. Our simulation analysis shows the performance comparison between proposed and existing algorithms. The proposed algorithm perform better than existing algorithms in term of maximum number of users that can be served by femtocells fairly, using minimum number of PRBs. User level fairness index obtained in our proposed algorithm is more efficient compared to reported works. Our proposed algorithm improves the balance among interference, resource utilization and user-level fairness in the system within an efficient convergence time complexity of %$O(m^2n)%$ even in dense deployment of femtocellular networks with varying number of users, where, m is the number of users and n is number of femtocells in the networks. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Pratap, Ajay [verfasserIn] Misra, Rajiv [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Schlagwörter:	Multi-coloring Femtocell LTE-A PRB Bernoulli random graph

Übergeordnetes Werk:	Enthalten in: Wireless personal communications - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994, 98(2017), 2 vom: 08. Sept., Seite 1975-1995
Übergeordnetes Werk:	volume:98 ; year:2017 ; number:2 ; day:08 ; month:09 ; pages:1975-1995

Links:	Volltext

DOI / URN:	10.1007/s11277-017-4957-x

Katalog-ID:	SPR018601642

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520			\|a Abstract Increasing demand of high data rates and spectral efficiency is sailing next generation wireless networks toward smaller cells structure known as femtocells with air interference technology known as orthogonal frequency division multiple access. To mitigate the high cost of cellular long term evolution-advanced (LTE-A) operators and poor indoor coverage, femtocell network structure has been proposed for underlaying evolved Node-B. Resource allocation, interference management and user level fairness are among the main problems for underlaying femtocellular network deployment. Radio resource management problem becomes even more complicated, when randomly deployed femtocells serve large number of users within total available physical resource blocks (PRBs) of LTE-A networks. To solve the radio resource management problem efficiently for accommodating maximum number of users within total available PRBs, network interference in femtocellular network is modeled as Bernoulli random graph model. A bound over required number of PRBs in the network has been established based on number of users connected with each femtocell and their interference relation with other femtocells. In this paper we have proposed the priorities greedy graph coloring based resource allocation algorithm for femtocellular LTE-A networks. The proposed algorithm accommodate maximum number of users, satisfies the total available PRBs, interference and user level fairness in the femtocellular networks. Our simulation analysis shows the performance comparison between proposed and existing algorithms. The proposed algorithm perform better than existing algorithms in term of maximum number of users that can be served by femtocells fairly, using minimum number of PRBs. User level fairness index obtained in our proposed algorithm is more efficient compared to reported works. Our proposed algorithm improves the balance among interference, resource utilization and user-level fairness in the system within an efficient convergence time complexity of %$O(m^2n)%$ even in dense deployment of femtocellular networks with varying number of users, where, m is the number of users and n is number of femtocells in the networks.
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author_variant	a p ap r m rm
matchkey_str	article:1572834X:2017----::admrpclrnbsdeoreloainoaheigsreefinsi
hierarchy_sort_str	2017
bklnumber	53.00
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allfields	10.1007/s11277-017-4957-x doi (DE-627)SPR018601642 (SPR)s11277-017-4957-x-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Pratap, Ajay verfasserin aut Random Graph Coloring-Based Resource Allocation for Achieving User Level Fairness in Femtocellular LTE-A Networks 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Increasing demand of high data rates and spectral efficiency is sailing next generation wireless networks toward smaller cells structure known as femtocells with air interference technology known as orthogonal frequency division multiple access. To mitigate the high cost of cellular long term evolution-advanced (LTE-A) operators and poor indoor coverage, femtocell network structure has been proposed for underlaying evolved Node-B. Resource allocation, interference management and user level fairness are among the main problems for underlaying femtocellular network deployment. Radio resource management problem becomes even more complicated, when randomly deployed femtocells serve large number of users within total available physical resource blocks (PRBs) of LTE-A networks. To solve the radio resource management problem efficiently for accommodating maximum number of users within total available PRBs, network interference in femtocellular network is modeled as Bernoulli random graph model. A bound over required number of PRBs in the network has been established based on number of users connected with each femtocell and their interference relation with other femtocells. In this paper we have proposed the priorities greedy graph coloring based resource allocation algorithm for femtocellular LTE-A networks. The proposed algorithm accommodate maximum number of users, satisfies the total available PRBs, interference and user level fairness in the femtocellular networks. Our simulation analysis shows the performance comparison between proposed and existing algorithms. The proposed algorithm perform better than existing algorithms in term of maximum number of users that can be served by femtocells fairly, using minimum number of PRBs. User level fairness index obtained in our proposed algorithm is more efficient compared to reported works. Our proposed algorithm improves the balance among interference, resource utilization and user-level fairness in the system within an efficient convergence time complexity of %$O(m^2n)%$ even in dense deployment of femtocellular networks with varying number of users, where, m is the number of users and n is number of femtocells in the networks. Multi-coloring (dpeaa)DE-He213 Femtocell (dpeaa)DE-He213 LTE-A (dpeaa)DE-He213 PRB (dpeaa)DE-He213 Bernoulli random graph (dpeaa)DE-He213 Misra, Rajiv verfasserin aut Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 98(2017), 2 vom: 08. Sept., Seite 1975-1995 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:98 year:2017 number:2 day:08 month:09 pages:1975-1995 https://dx.doi.org/10.1007/s11277-017-4957-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 98 2017 2 08 09 1975-1995
spelling	10.1007/s11277-017-4957-x doi (DE-627)SPR018601642 (SPR)s11277-017-4957-x-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Pratap, Ajay verfasserin aut Random Graph Coloring-Based Resource Allocation for Achieving User Level Fairness in Femtocellular LTE-A Networks 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Increasing demand of high data rates and spectral efficiency is sailing next generation wireless networks toward smaller cells structure known as femtocells with air interference technology known as orthogonal frequency division multiple access. To mitigate the high cost of cellular long term evolution-advanced (LTE-A) operators and poor indoor coverage, femtocell network structure has been proposed for underlaying evolved Node-B. Resource allocation, interference management and user level fairness are among the main problems for underlaying femtocellular network deployment. Radio resource management problem becomes even more complicated, when randomly deployed femtocells serve large number of users within total available physical resource blocks (PRBs) of LTE-A networks. To solve the radio resource management problem efficiently for accommodating maximum number of users within total available PRBs, network interference in femtocellular network is modeled as Bernoulli random graph model. A bound over required number of PRBs in the network has been established based on number of users connected with each femtocell and their interference relation with other femtocells. In this paper we have proposed the priorities greedy graph coloring based resource allocation algorithm for femtocellular LTE-A networks. The proposed algorithm accommodate maximum number of users, satisfies the total available PRBs, interference and user level fairness in the femtocellular networks. Our simulation analysis shows the performance comparison between proposed and existing algorithms. The proposed algorithm perform better than existing algorithms in term of maximum number of users that can be served by femtocells fairly, using minimum number of PRBs. User level fairness index obtained in our proposed algorithm is more efficient compared to reported works. Our proposed algorithm improves the balance among interference, resource utilization and user-level fairness in the system within an efficient convergence time complexity of %$O(m^2n)%$ even in dense deployment of femtocellular networks with varying number of users, where, m is the number of users and n is number of femtocells in the networks. Multi-coloring (dpeaa)DE-He213 Femtocell (dpeaa)DE-He213 LTE-A (dpeaa)DE-He213 PRB (dpeaa)DE-He213 Bernoulli random graph (dpeaa)DE-He213 Misra, Rajiv verfasserin aut Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 98(2017), 2 vom: 08. Sept., Seite 1975-1995 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:98 year:2017 number:2 day:08 month:09 pages:1975-1995 https://dx.doi.org/10.1007/s11277-017-4957-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 98 2017 2 08 09 1975-1995
allfields_unstemmed	10.1007/s11277-017-4957-x doi (DE-627)SPR018601642 (SPR)s11277-017-4957-x-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Pratap, Ajay verfasserin aut Random Graph Coloring-Based Resource Allocation for Achieving User Level Fairness in Femtocellular LTE-A Networks 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Increasing demand of high data rates and spectral efficiency is sailing next generation wireless networks toward smaller cells structure known as femtocells with air interference technology known as orthogonal frequency division multiple access. To mitigate the high cost of cellular long term evolution-advanced (LTE-A) operators and poor indoor coverage, femtocell network structure has been proposed for underlaying evolved Node-B. Resource allocation, interference management and user level fairness are among the main problems for underlaying femtocellular network deployment. Radio resource management problem becomes even more complicated, when randomly deployed femtocells serve large number of users within total available physical resource blocks (PRBs) of LTE-A networks. To solve the radio resource management problem efficiently for accommodating maximum number of users within total available PRBs, network interference in femtocellular network is modeled as Bernoulli random graph model. A bound over required number of PRBs in the network has been established based on number of users connected with each femtocell and their interference relation with other femtocells. In this paper we have proposed the priorities greedy graph coloring based resource allocation algorithm for femtocellular LTE-A networks. The proposed algorithm accommodate maximum number of users, satisfies the total available PRBs, interference and user level fairness in the femtocellular networks. Our simulation analysis shows the performance comparison between proposed and existing algorithms. The proposed algorithm perform better than existing algorithms in term of maximum number of users that can be served by femtocells fairly, using minimum number of PRBs. User level fairness index obtained in our proposed algorithm is more efficient compared to reported works. Our proposed algorithm improves the balance among interference, resource utilization and user-level fairness in the system within an efficient convergence time complexity of %$O(m^2n)%$ even in dense deployment of femtocellular networks with varying number of users, where, m is the number of users and n is number of femtocells in the networks. Multi-coloring (dpeaa)DE-He213 Femtocell (dpeaa)DE-He213 LTE-A (dpeaa)DE-He213 PRB (dpeaa)DE-He213 Bernoulli random graph (dpeaa)DE-He213 Misra, Rajiv verfasserin aut Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 98(2017), 2 vom: 08. Sept., Seite 1975-1995 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:98 year:2017 number:2 day:08 month:09 pages:1975-1995 https://dx.doi.org/10.1007/s11277-017-4957-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 98 2017 2 08 09 1975-1995
allfieldsGer	10.1007/s11277-017-4957-x doi (DE-627)SPR018601642 (SPR)s11277-017-4957-x-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Pratap, Ajay verfasserin aut Random Graph Coloring-Based Resource Allocation for Achieving User Level Fairness in Femtocellular LTE-A Networks 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Increasing demand of high data rates and spectral efficiency is sailing next generation wireless networks toward smaller cells structure known as femtocells with air interference technology known as orthogonal frequency division multiple access. To mitigate the high cost of cellular long term evolution-advanced (LTE-A) operators and poor indoor coverage, femtocell network structure has been proposed for underlaying evolved Node-B. Resource allocation, interference management and user level fairness are among the main problems for underlaying femtocellular network deployment. Radio resource management problem becomes even more complicated, when randomly deployed femtocells serve large number of users within total available physical resource blocks (PRBs) of LTE-A networks. To solve the radio resource management problem efficiently for accommodating maximum number of users within total available PRBs, network interference in femtocellular network is modeled as Bernoulli random graph model. A bound over required number of PRBs in the network has been established based on number of users connected with each femtocell and their interference relation with other femtocells. In this paper we have proposed the priorities greedy graph coloring based resource allocation algorithm for femtocellular LTE-A networks. The proposed algorithm accommodate maximum number of users, satisfies the total available PRBs, interference and user level fairness in the femtocellular networks. Our simulation analysis shows the performance comparison between proposed and existing algorithms. The proposed algorithm perform better than existing algorithms in term of maximum number of users that can be served by femtocells fairly, using minimum number of PRBs. User level fairness index obtained in our proposed algorithm is more efficient compared to reported works. Our proposed algorithm improves the balance among interference, resource utilization and user-level fairness in the system within an efficient convergence time complexity of %$O(m^2n)%$ even in dense deployment of femtocellular networks with varying number of users, where, m is the number of users and n is number of femtocells in the networks. Multi-coloring (dpeaa)DE-He213 Femtocell (dpeaa)DE-He213 LTE-A (dpeaa)DE-He213 PRB (dpeaa)DE-He213 Bernoulli random graph (dpeaa)DE-He213 Misra, Rajiv verfasserin aut Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 98(2017), 2 vom: 08. Sept., Seite 1975-1995 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:98 year:2017 number:2 day:08 month:09 pages:1975-1995 https://dx.doi.org/10.1007/s11277-017-4957-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 98 2017 2 08 09 1975-1995
allfieldsSound	10.1007/s11277-017-4957-x doi (DE-627)SPR018601642 (SPR)s11277-017-4957-x-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Pratap, Ajay verfasserin aut Random Graph Coloring-Based Resource Allocation for Achieving User Level Fairness in Femtocellular LTE-A Networks 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Increasing demand of high data rates and spectral efficiency is sailing next generation wireless networks toward smaller cells structure known as femtocells with air interference technology known as orthogonal frequency division multiple access. To mitigate the high cost of cellular long term evolution-advanced (LTE-A) operators and poor indoor coverage, femtocell network structure has been proposed for underlaying evolved Node-B. Resource allocation, interference management and user level fairness are among the main problems for underlaying femtocellular network deployment. Radio resource management problem becomes even more complicated, when randomly deployed femtocells serve large number of users within total available physical resource blocks (PRBs) of LTE-A networks. To solve the radio resource management problem efficiently for accommodating maximum number of users within total available PRBs, network interference in femtocellular network is modeled as Bernoulli random graph model. A bound over required number of PRBs in the network has been established based on number of users connected with each femtocell and their interference relation with other femtocells. In this paper we have proposed the priorities greedy graph coloring based resource allocation algorithm for femtocellular LTE-A networks. The proposed algorithm accommodate maximum number of users, satisfies the total available PRBs, interference and user level fairness in the femtocellular networks. Our simulation analysis shows the performance comparison between proposed and existing algorithms. The proposed algorithm perform better than existing algorithms in term of maximum number of users that can be served by femtocells fairly, using minimum number of PRBs. User level fairness index obtained in our proposed algorithm is more efficient compared to reported works. Our proposed algorithm improves the balance among interference, resource utilization and user-level fairness in the system within an efficient convergence time complexity of %$O(m^2n)%$ even in dense deployment of femtocellular networks with varying number of users, where, m is the number of users and n is number of femtocells in the networks. Multi-coloring (dpeaa)DE-He213 Femtocell (dpeaa)DE-He213 LTE-A (dpeaa)DE-He213 PRB (dpeaa)DE-He213 Bernoulli random graph (dpeaa)DE-He213 Misra, Rajiv verfasserin aut Enthalten in Wireless personal communications Dordrecht [u.a.] : Springer Science + Business Media B.V, 1994 98(2017), 2 vom: 08. Sept., Seite 1975-1995 (DE-627)271179120 (DE-600)1479327-1 1572-834X nnns volume:98 year:2017 number:2 day:08 month:09 pages:1975-1995 https://dx.doi.org/10.1007/s11277-017-4957-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 98 2017 2 08 09 1975-1995
language	English
source	Enthalten in Wireless personal communications 98(2017), 2 vom: 08. Sept., Seite 1975-1995 volume:98 year:2017 number:2 day:08 month:09 pages:1975-1995
sourceStr	Enthalten in Wireless personal communications 98(2017), 2 vom: 08. Sept., Seite 1975-1995 volume:98 year:2017 number:2 day:08 month:09 pages:1975-1995
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Multi-coloring Femtocell LTE-A PRB Bernoulli random graph
dewey-raw	620
isfreeaccess_bool	false
container_title	Wireless personal communications
authorswithroles_txt_mv	Pratap, Ajay @@aut@@ Misra, Rajiv @@aut@@
publishDateDaySort_date	2017-09-08T00:00:00Z
hierarchy_top_id	271179120
dewey-sort	3620
id	SPR018601642
language_de	englisch
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author	Pratap, Ajay
spellingShingle	Pratap, Ajay ddc 620 bkl 53.00 misc Multi-coloring misc Femtocell misc LTE-A misc PRB misc Bernoulli random graph Random Graph Coloring-Based Resource Allocation for Achieving User Level Fairness in Femtocellular LTE-A Networks
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topic_title	620 ASE 53.00 bkl Random Graph Coloring-Based Resource Allocation for Achieving User Level Fairness in Femtocellular LTE-A Networks Multi-coloring (dpeaa)DE-He213 Femtocell (dpeaa)DE-He213 LTE-A (dpeaa)DE-He213 PRB (dpeaa)DE-He213 Bernoulli random graph (dpeaa)DE-He213
topic	ddc 620 bkl 53.00 misc Multi-coloring misc Femtocell misc LTE-A misc PRB misc Bernoulli random graph
topic_unstemmed	ddc 620 bkl 53.00 misc Multi-coloring misc Femtocell misc LTE-A misc PRB misc Bernoulli random graph
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title	Random Graph Coloring-Based Resource Allocation for Achieving User Level Fairness in Femtocellular LTE-A Networks
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title_full	Random Graph Coloring-Based Resource Allocation for Achieving User Level Fairness in Femtocellular LTE-A Networks
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title_sort	random graph coloring-based resource allocation for achieving user level fairness in femtocellular lte-a networks
title_auth	Random Graph Coloring-Based Resource Allocation for Achieving User Level Fairness in Femtocellular LTE-A Networks
abstract	Abstract Increasing demand of high data rates and spectral efficiency is sailing next generation wireless networks toward smaller cells structure known as femtocells with air interference technology known as orthogonal frequency division multiple access. To mitigate the high cost of cellular long term evolution-advanced (LTE-A) operators and poor indoor coverage, femtocell network structure has been proposed for underlaying evolved Node-B. Resource allocation, interference management and user level fairness are among the main problems for underlaying femtocellular network deployment. Radio resource management problem becomes even more complicated, when randomly deployed femtocells serve large number of users within total available physical resource blocks (PRBs) of LTE-A networks. To solve the radio resource management problem efficiently for accommodating maximum number of users within total available PRBs, network interference in femtocellular network is modeled as Bernoulli random graph model. A bound over required number of PRBs in the network has been established based on number of users connected with each femtocell and their interference relation with other femtocells. In this paper we have proposed the priorities greedy graph coloring based resource allocation algorithm for femtocellular LTE-A networks. The proposed algorithm accommodate maximum number of users, satisfies the total available PRBs, interference and user level fairness in the femtocellular networks. Our simulation analysis shows the performance comparison between proposed and existing algorithms. The proposed algorithm perform better than existing algorithms in term of maximum number of users that can be served by femtocells fairly, using minimum number of PRBs. User level fairness index obtained in our proposed algorithm is more efficient compared to reported works. Our proposed algorithm improves the balance among interference, resource utilization and user-level fairness in the system within an efficient convergence time complexity of %$O(m^2n)%$ even in dense deployment of femtocellular networks with varying number of users, where, m is the number of users and n is number of femtocells in the networks.
abstractGer	Abstract Increasing demand of high data rates and spectral efficiency is sailing next generation wireless networks toward smaller cells structure known as femtocells with air interference technology known as orthogonal frequency division multiple access. To mitigate the high cost of cellular long term evolution-advanced (LTE-A) operators and poor indoor coverage, femtocell network structure has been proposed for underlaying evolved Node-B. Resource allocation, interference management and user level fairness are among the main problems for underlaying femtocellular network deployment. Radio resource management problem becomes even more complicated, when randomly deployed femtocells serve large number of users within total available physical resource blocks (PRBs) of LTE-A networks. To solve the radio resource management problem efficiently for accommodating maximum number of users within total available PRBs, network interference in femtocellular network is modeled as Bernoulli random graph model. A bound over required number of PRBs in the network has been established based on number of users connected with each femtocell and their interference relation with other femtocells. In this paper we have proposed the priorities greedy graph coloring based resource allocation algorithm for femtocellular LTE-A networks. The proposed algorithm accommodate maximum number of users, satisfies the total available PRBs, interference and user level fairness in the femtocellular networks. Our simulation analysis shows the performance comparison between proposed and existing algorithms. The proposed algorithm perform better than existing algorithms in term of maximum number of users that can be served by femtocells fairly, using minimum number of PRBs. User level fairness index obtained in our proposed algorithm is more efficient compared to reported works. Our proposed algorithm improves the balance among interference, resource utilization and user-level fairness in the system within an efficient convergence time complexity of %$O(m^2n)%$ even in dense deployment of femtocellular networks with varying number of users, where, m is the number of users and n is number of femtocells in the networks.
abstract_unstemmed	Abstract Increasing demand of high data rates and spectral efficiency is sailing next generation wireless networks toward smaller cells structure known as femtocells with air interference technology known as orthogonal frequency division multiple access. To mitigate the high cost of cellular long term evolution-advanced (LTE-A) operators and poor indoor coverage, femtocell network structure has been proposed for underlaying evolved Node-B. Resource allocation, interference management and user level fairness are among the main problems for underlaying femtocellular network deployment. Radio resource management problem becomes even more complicated, when randomly deployed femtocells serve large number of users within total available physical resource blocks (PRBs) of LTE-A networks. To solve the radio resource management problem efficiently for accommodating maximum number of users within total available PRBs, network interference in femtocellular network is modeled as Bernoulli random graph model. A bound over required number of PRBs in the network has been established based on number of users connected with each femtocell and their interference relation with other femtocells. In this paper we have proposed the priorities greedy graph coloring based resource allocation algorithm for femtocellular LTE-A networks. The proposed algorithm accommodate maximum number of users, satisfies the total available PRBs, interference and user level fairness in the femtocellular networks. Our simulation analysis shows the performance comparison between proposed and existing algorithms. The proposed algorithm perform better than existing algorithms in term of maximum number of users that can be served by femtocells fairly, using minimum number of PRBs. User level fairness index obtained in our proposed algorithm is more efficient compared to reported works. Our proposed algorithm improves the balance among interference, resource utilization and user-level fairness in the system within an efficient convergence time complexity of %$O(m^2n)%$ even in dense deployment of femtocellular networks with varying number of users, where, m is the number of users and n is number of femtocells in the networks.
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title_short	Random Graph Coloring-Based Resource Allocation for Achieving User Level Fairness in Femtocellular LTE-A Networks
url	https://dx.doi.org/10.1007/s11277-017-4957-x
remote_bool	true
author2	Misra, Rajiv
author2Str	Misra, Rajiv
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doi_str	10.1007/s11277-017-4957-x
up_date	2024-07-03T20:52:42.146Z
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