飞蜂窝网络中一种低复杂度的小区动态休眠方案研究
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- 论文作者：张沛 ; 王国祥
- 年：2016
- 作者机构：中国移动通信集团设计院有限公司山东分公司;
- 论文关键词：飞蜂窝网络 ; 休眠方案 ; 低复杂度 ; 人工神经网络算法
- 会议召开时间：2016-08-17
- 会议录名称：面向5G的LTE网络创新研讨会（2016）论文集
- 语种：中文
- 分类号：TN929.5
- 学会代码：DZYD
- 会议名称：面向5G的LTE网络创新研讨会(2016)
- 会议地点：中国北京
- 主办单位：TD产业联盟、《移动通信》杂志社
- 学会名称：中国电子科技集团公司第七研究所《移动通信》杂志社
- 页数：5
- 文件大小：974k
- 原文格式：O
- 会议级别：全国
摘要
小区休眠方案能够在网络流量较低的情况下,关闭某些基站来降低网络能耗,然而,飞蜂窝网络中的流量存在很强的随机性,导致现有的休眠方案在应对这种场景时存在复杂度过高的缺点。提出了一种低复杂度的小区动态休眠方案,利用人工神经网络算法对网络流量进行预测,在此基础上动态地实施小区休眠/激活。数值和仿真结果表明,本方案在有效提高网络能效的同时,还具有复杂度低的优点。
引文
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[2]Litjens R,L Jorguseski.Potential of energy-oriented network optimisation:Switching off over-capacity in off-peak hours in Personal Indoor and Mobile Radio Communications(PIMRC)[A].2010 IEEE 21st International Symposium[C].2010.
[3]Samulevicius S.Energy Savings in Mobile Broadband Network Based on Load Predictions:Opportunities and Potentials in Vehicular Technology Conference(VTC Spring)[A].2012.
[4]Ashraf I,F Boccardi,L Ho.SLEEP mode techniques for small cell deployments[J].Communications Magazine,2011,49(8):72-79.
[5]Marsan,M A.Optimal Energy Savings in Cellular Access Networks in Communications Workshops[A].ICC Workshops 2009 IEEE International Conference on[C].2009.
[6]Zhisheng Niu,Y W,Jie Gong,et al.Cell Zooming for Cost-Efficient greener cellular network[J].IEEE Communications Magazine,2010.
[7]Xiangnan Weng,D C,Zhisheng Niu.Energy-Efficient Cellular Network Planning under Insufficient Cell Zooming[Z].2011.
[8]Kyuho Son,H K,Yung Yi,et al.Base Station Operation and User Association Mechanisms for Energy-Delay Tradeoffs[J].IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS,2011.
[9]Saker L.Optimal Control of Wake Up Mechanisms of Femtocells in Heterogeneous Networks[J].Selected Areas in Communications IEEE Journal on,2012,30(3):664-672.
[10]IIER.Energy efficiency analysis of the reference systems areas of improvements and target breakdown[Z].
[11]Eunsung O.Toward dynamic energy-efficient operation of cellular network infrastructure[J].Communications Magazine IEEE,2011,49(6):56-61.
[12]Samarasinghe S.Neural networks for applied sciences and engineering:from fundamentals to complex pattern recognition[M].Auerbach Publications.
[13]IIER.Most Promising Tracks of Green Network Technologies[Z].