Femtocell网络中的节能选择性激活

Michael Lin, S. Silvestri, N. Bartolini, T. L. Porta
{"title":"Femtocell网络中的节能选择性激活","authors":"Michael Lin, S. Silvestri, N. Bartolini, T. L. Porta","doi":"10.1109/MASS.2015.16","DOIUrl":null,"url":null,"abstract":"Provisioning the capacity of wireless networks is difficult when peak load is significantly higher than average load, for example, in public spaces like airports or train stations. Service providers can use femtocells and small cells to increase local capacity, but deploying enough femtocells to serve peak loads requires a large number of femtocells that will remain idle most of the time, which wastes a significant amount of power. To reduce the energy consumption of over-provisioned femtocell networks, we formulate a femtocell selective activation problem, which we formalize as an integer nonlinear optimization problem. Then we introduce Green Femto, a distributed femtocell selective activation algorithm that deactivates idle femtocells to save power and activates them on-the-fly as the number of users increases. We prove that Green Femto converges to a locally Pareto optimal solution and demonstrate its performance using extensive simulations of an LTE wireless system. Overall, we find that Green Femto requires up to 55% fewer femtocells to serve a given user load, relative to an existing femtocell power-saving procedure, and comes within 15% of a globally optimal solution.","PeriodicalId":436496,"journal":{"name":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Energy-Efficient Selective Activation in Femtocell Networks\",\"authors\":\"Michael Lin, S. Silvestri, N. Bartolini, T. L. Porta\",\"doi\":\"10.1109/MASS.2015.16\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Provisioning the capacity of wireless networks is difficult when peak load is significantly higher than average load, for example, in public spaces like airports or train stations. Service providers can use femtocells and small cells to increase local capacity, but deploying enough femtocells to serve peak loads requires a large number of femtocells that will remain idle most of the time, which wastes a significant amount of power. To reduce the energy consumption of over-provisioned femtocell networks, we formulate a femtocell selective activation problem, which we formalize as an integer nonlinear optimization problem. Then we introduce Green Femto, a distributed femtocell selective activation algorithm that deactivates idle femtocells to save power and activates them on-the-fly as the number of users increases. We prove that Green Femto converges to a locally Pareto optimal solution and demonstrate its performance using extensive simulations of an LTE wireless system. Overall, we find that Green Femto requires up to 55% fewer femtocells to serve a given user load, relative to an existing femtocell power-saving procedure, and comes within 15% of a globally optimal solution.\",\"PeriodicalId\":436496,\"journal\":{\"name\":\"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-10-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MASS.2015.16\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MASS.2015.16","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

当峰值负载明显高于平均负载时,例如在机场或火车站等公共场所,提供无线网络的容量是困难的。服务提供商可以使用飞行基站和小型基站来增加本地容量,但部署足够的飞行基站来服务峰值负载需要大量的飞行基站,而这些基站大部分时间都处于闲置状态,这将浪费大量的电力。为了减少过度配置的移动蜂窝网络的能量消耗,我们提出了一个移动蜂窝选择激活问题,并将其形式化为一个整数非线性优化问题。然后,我们介绍了Green Femto,这是一种分布式的飞蜂窝选择性激活算法,它可以停用闲置的飞蜂窝以节省电力,并随着用户数量的增加而动态激活它们。我们证明了Green Femto收敛于局部Pareto最优解,并通过LTE无线系统的大量模拟演示了其性能。总的来说,我们发现Green Femto在给定的用户负载下,与现有的femtocell节能程序相比,需要的femtocell最多减少55%,并且在全局最优解决方案的15%以内。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Energy-Efficient Selective Activation in Femtocell Networks
Provisioning the capacity of wireless networks is difficult when peak load is significantly higher than average load, for example, in public spaces like airports or train stations. Service providers can use femtocells and small cells to increase local capacity, but deploying enough femtocells to serve peak loads requires a large number of femtocells that will remain idle most of the time, which wastes a significant amount of power. To reduce the energy consumption of over-provisioned femtocell networks, we formulate a femtocell selective activation problem, which we formalize as an integer nonlinear optimization problem. Then we introduce Green Femto, a distributed femtocell selective activation algorithm that deactivates idle femtocells to save power and activates them on-the-fly as the number of users increases. We prove that Green Femto converges to a locally Pareto optimal solution and demonstrate its performance using extensive simulations of an LTE wireless system. Overall, we find that Green Femto requires up to 55% fewer femtocells to serve a given user load, relative to an existing femtocell power-saving procedure, and comes within 15% of a globally optimal solution.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Dynamic Provisioning for High Energy Efficiency and Resource Utilization in Cloud RANs An Energy Efficient and Restricted Tour Construction for Mobile Sink in Wireless Sensor Networks MQCC: Maximum Queue Congestion Control for Multipath Networks with Blockage Context-Aware Crowd-Sensing in Opportunistic Mobile Social Networks Study of Hadoop-MapReduce on Google N-Gram Datasets
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1