Coverage and Energy Modeling of HetNet Under Base Station On‐Off Model
Small cell networks, as an important evolution path for next‐generation cellular networks, have drawn much attention. Different from the traditional base stations (BSs) always‐on model, we proposed a BSs on‐off model, where a new, simple expression for the probabilities of active BSs in a heterogene...
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Published in | ETRI journal Vol. 37; no. 3; pp. 450 - 459 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Electronics and Telecommunications Research Institute (ETRI)
01.06.2015
한국전자통신연구원 |
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Abstract | Small cell networks, as an important evolution path for next‐generation cellular networks, have drawn much attention. Different from the traditional base stations (BSs) always‐on model, we proposed a BSs on‐off model, where a new, simple expression for the probabilities of active BSs in a heterogeneous network is derived. This model is more suitable for application in practical networks. Based on this, we develop an analytical framework for the performance evaluation of small cell networks, adopting stochastic geometry theory. We derive the system coverage probability; average energy efficiency (AEE) and average uplink power consumption (AUPC) for different association strategies; maximum biased received power (MaBRP); and minimum association distance (MiAD). It is analytically shown that MaBRP is beneficial for coverage but will have some loss in energy saving. On the contrary, MiAD is not advocated from the point of coverage but is more energy efficient. The simulation results show that the use of range expansion in MaBRP helps to save energy but that this is not so in MiAD. Furthermore, we can achieve an optimal AEE by establishing an appropriate density of small cells. |
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AbstractList | Small cell networks, as an important evolution path for next‐generation cellular networks, have drawn much attention. Different from the traditional base stations (BSs) always‐on model, we proposed a BSs on‐off model, where a new, simple expression for the probabilities of active BSs in a heterogeneous network is derived. This model is more suitable for application in practical networks. Based on this, we develop an analytical framework for the performance evaluation of small cell networks, adopting stochastic geometry theory. We derive the system coverage probability; average energy efficiency (AEE) and average uplink power consumption (AUPC) for different association strategies; maximum biased received power (MaBRP); and minimum association distance (MiAD). It is analytically shown that MaBRP is beneficial for coverage but will have some loss in energy saving. On the contrary, MiAD is not advocated from the point of coverage but is more energy efficient. The simulation results show that the use of range expansion in MaBRP helps to save energy but that this is not so in MiAD. Furthermore, we can achieve an optimal AEE by establishing an appropriate density of small cells. Small cell networks, as an important evolution path for next-generation cellular networks, have drawn much attention. Different from the traditional base stations (BSs) always-on model, we proposed a BSs on-off model, where a new, simple expression for the probabilities of active BSs in a heterogeneous network is derived. This model is more suitable for application in practical networks. Based on this, we develop an analytical framework for the performance evaluation of small cell networks, adopting stochastic geometry theory. We derive the system coverage probability; average energy efficiency (AEE) and average uplink power consumption (AUPC) for different association strategies; maximum biased received power (MaBRP); and minimum association distance (MiAD). It is analytically shown that MaBRP is beneficial for coverage but will have some loss in energy saving. On the contrary, MiAD is not advocated from the point of coverage but is more energy efficient. The simulation results show that the use of range expansion in MaBRP helps to save energy but that this is not so in MiAD. Furthermore, we can achieve an optimal AEE by establishing an appropriate density of small cells. KCI Citation Count: 3 |
Author | Song, Sida Chang, Yongyu Wang, Xianling Yang, Dacheng |
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Cites_doi | 10.1109/TWC.2012.081612.111361 10.1109/LCOMM.2012.042512.120426 10.1109/icc.2012.6364656 10.1109/MCOM.2013.6476878 10.1109/TWC.2013.040413.121174 10.1109/wcnc.2012.6213945 10.1109/TWC.2012.060412.111829 10.1109/JSAC.2011.110903 10.1109/JSAC.2009.090902 10.1561/1300000006 10.1109/icc.2013.6655259 10.1109/LCOMM.2014.030114.140241 10.1109/TWC.2011.091411.110249 10.1109/TCOMM.2011.100411.100541 |
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Notes | Sida Song (corresponding author buptsongstar@gmail.com and Dacheng Yang are with the Wireless Theory & Technology Laboratory (WT&T), the School of Information and Communications Engineering, Beijing University of Posts and Telecommunications, China. Yongyu Chang yangdc@bupt.edu.cn yychang@bupt.edu.cn Xianling Wang baggiorio18@gmail.com http://etrij.etri.re.kr/etrij/journal/article/article.do?volume=37&issue=3&page=450 G704-001110.2015.37.3.010 |
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SubjectTerms | association strategy base station on‐off HetNet Poisson point process Small cell stochastic geometry 전자/정보통신공학 |
Title | Coverage and Energy Modeling of HetNet Under Base Station On‐Off Model |
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