Cooperation-enabled energy efficient base station management for dense small cell networks

被引:5
作者
Chen, Yawen [1 ]
Wen, Xiangming [1 ]
Lu, Zhaoming [1 ]
Shao, Hua [1 ]
Jing, Wenpeng [1 ]
机构
[1] Beijing Univ Posts & Telecommun, Beijing Lab Adv Informat Networks, Beijing Key Lab Network Syst Architecture & Conve, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
Dense small cell networks; Sleep mode; Cooperative transmission; Energy efficiency; QoS; OPTIMIZATION; DOWNLINK;
D O I
10.1007/s11276-016-1234-y
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Dense small cell networks are deployed for future wireless communication to meet the ever-increasing mobile traffic demand. However, network densification will significantly increase the energy budget and lead to energy inefficiency due to the constant operation of network hardware. In this paper, we consider cooperation-enabled dynamic base station (BS) management for downlink dense small cell networks. By introducing two traffic-aware sleep modes, i.e., deep sleep mode and opportunistic sleep mode which are operating in different time and energy consumption scales, the network hardwares are turned to be the resources that can be occupied and released dynamically. Small cell BSs (SBSs) with zero or low load are completely switched off and reside in deep sleep mode during a predefined time interval. At each time slot, SBS dynamically turn some antennas and associated physical components into opportunistic sleep mode according to the short term traffic distribution, and the users are jointly served by the remaining antennas via cooperative transmission. The corresponding sleep mode decision making are presented respectively to find the optimal number of SBS and antennas that should be switched off. Numerical results are then presented to illustrate the superior performance in terms of energy efficiency gain. In summary, the proposed cooperation-aided sleep strategies for dense small cell networks take both traffic features and optimal cooperative transmission into account, and can achieve great energy saving while maintaining required quality of service.
引用
收藏
页码:1611 / 1628
页数:18
相关论文
共 30 条
  • [1] [Anonymous], 2010, PROC GLOBECOM 2010 M, P1
  • [2] [Anonymous], 2007, 2007 15 INT SOFTW TE
  • [3] SLEEP Mode Techniques for Small Cell Deployments
    Ashraf, Imran
    Boccardi, Federico
    Ho, Lester
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2011, 49 (08) : 72 - 79
  • [4] HOW MUCH ENERGY IS NEEDED TO RUN A WIRELESS NETWORK?
    Auer, Gunther
    Giannini, Vito
    Desset, Claude
    Godor, Istvan
    Skillermark, Per
    Olsson, Magnus
    Imran, Muhammad Ali
    Sabella, Dario
    Gonzalez, Manuel J.
    Blume, Oliver
    Fehske, Albrecht
    [J]. IEEE WIRELESS COMMUNICATIONS, 2011, 18 (05) : 40 - 49
  • [5] Network Densification: The Dominant Theme for Wireless Evolution into 5G
    Bhushan, Naga
    Li, Junyi
    Malladi, Durga
    Gilmore, Rob
    Brenner, Dean
    Damnjanovic, Aleksandar
    Sukhavasi, Ravi Teja
    Patel, Chirag
    Geirhofer, Stefan
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2014, 52 (02) : 82 - 89
  • [6] Boyd S, 2004, CONVEX OPTIMIZATION
  • [7] Dynamic Resource Provisioning for Energy Efficiency in Wireless Access Networks: A Survey and an Outlook
    Budzisz, Lukasz
    Ganji, Fatemeh
    Rizzo, Gianluca
    Marsan, Marco Ajmone
    Meo, Michela
    Zhang, Yi
    Koutitas, George
    Tassiulas, Leandros
    Lambert, Sofie
    Lannoo, Bart
    Pickavet, Mario
    Conte, Alberto
    Haratcherev, Ivaylo
    Wolisz, Adam
    [J]. IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2014, 16 (04): : 2259 - 2285
  • [8] Joint Network Optimization and Downlink Beamforming for CoMP Transmissions Using Mixed Integer Conic Programming
    Cheng, Yong
    Pesavento, Marius
    Philipp, Anne
    [J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2013, 61 (16) : 3972 - 3987
  • [9] CELL WILTING AND BLOSSOMING FOR ENERGY EFFICIENCY
    Conte, Alberto
    Feki, Afef
    Chiaraviglio, Luca
    Ciullo, Delia
    Meo, Michela
    Marsan, Marco Ajmone
    [J]. IEEE WIRELESS COMMUNICATIONS, 2011, 18 (05) : 50 - 57
  • [10] Debaillie B., 2011, PROC FUTURE NETWORK, P1