期刊文献+

基于虚拟MIMO的无线传感网数据传输策略 被引量:4

Data Transmission Strategy for Wireless Sensor Network Based on Virtual MIMO
下载PDF
导出
摘要 基于无线传感网的虚拟多输入多输出(multi-input multi-output,MIMO)技术,结合分簇多跳传输模式进行全网的数据传输,根据分簇算法得到每一个簇的簇头,利用协作传输方式,将数据传输至相邻簇头.在进行数据传输时,综合考虑网络的电路能耗与传输能耗,推导出簇间传输的最小能耗为发送方簇的协作节点个数Mt的表达式,从而得到到达汇聚节点的最优路径.基于最小簇间能耗的协作虚拟MIMO多跳传输策略不需要接收端协同,避免了接收端协同的复杂性,同时从整个网络生存周期角度出发,节省更多的网络能耗.仿真结果表明,该策略在轮次增加或者簇间距离变化的情况下,都能得到较好的节能效果,从而延长网络的生存周期. Data transmission for the entire network based on virtual MIMO (multi-input-multi-output) wireless sensor network structure in multi-hop clusters was studied in the system. Each cluster's head was formed according to the clustering algorithm, and data transmitted to the adjacent cluster's head by cooperative communication. The circuit energy consumption and the transmission energy consumption were both considered when data was transmitted in the system, so that M,, with the minimum energy consumption and the best numbers of cooperative nodes in the transmitter cluster, was acquired, and the optimal path to the Sink node obtained. The proposed strategy does not need the receiver's collaboration so that it is free of the complexity to coordinate the receiver and much energy-efficient from the perspective of the network life cycle. Simulation results show that the proposed strategy has good energy-saving effect and network lifecycle extending results whether with increased rounds or varied inter-cluster distance.
作者 冯陈伟
出处 《厦门理工学院学报》 2015年第3期51-56,共6页 Journal of Xiamen University of Technology
基金 国家自然科学基金项目(61202013) 福建省自然科学基金项目(2015J01670) 福建省中青年教师教育科研项目(JA14233)
关键词 无线传感网 数据传输 多跳传输 协作通信 虚拟MIMO wireless sensor network data transmission multi-hop transmission cooperative communication virtual MIMO
  • 相关文献

参考文献11

  • 1PAULRAJ A, NABAR R, GORE D. Introduction to space-time wireless communications [ M ]. London: Cambridge University Press, 2003.
  • 2CUI S, GOLDSMITH A J, BAHAI A. Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks [ J]. IEEE Journal on Selected Areas in Communications, 2004, 22(6): 1 089-1 098.
  • 3CUI S, GOLDSMITH A J, BAHAI A. Energy-constrained modulation optimization [ J ]. IEEE Transactions on Wireless Communications, 2005,4(5) : 2 349-2 360.
  • 4HUSSAIN S, AZIM A, PARK J H. Energy efficient virtual MIMO communication for wireless sensor networks [ J ]. Telecommunication Systems, 2009, 42 (1/2) : 139-149.
  • 5XUE J, ZHANG T, YAN Y, et al. Cooperation-based ant colony algorithm in WSN [J]. Journal of Networks, 2013, 8(4) 939-946.
  • 6秦智超,周正,赵小川,章杨.认知无线传感器网络中基于GSC的协作传输机制[J].通信学报,2013,34(9):158-165. 被引量:4
  • 7邱云周,沈杰,董少龙,刘海涛.基于无线传感网的虚拟MIMO的能量有效性研究[J].计算机工程,2007,33(17):1-3. 被引量:4
  • 8HEINZELMAN W R, CHANDRAKASAN A, BALAKRISHNAN H; Energy-efficient communication protocol for wireless microsensor networks [ C ] //Proceedings of the 33rd Hawaii International Conference on System Sciences. Cambridge : IEEE, 2000.
  • 9DAI L, CHEN W, CIMINI L J, et al. Fairness improves throughput in energy-constrained cooperative ad-hoc networks [ J]. IEEE Transactions on Wireless Communications, 2009, 8 (7): 3 679-3 691.
  • 10LI B, WANG W, YIN Q, et al. A new cooperative transmission metric in wireless sensor networks to minimize energy consumption per unit transmit distance [ J]. IEEE Communications Letters, 2012, 16 (5) : 626-629.

二级参考文献27

  • 1Paulraj A,Nabar R,Gore D.Introduction to Space-time Communi-cations[M].Cambride,U.K.:Cambridge Univ.Press,2003.
  • 2Cui S,Goldsmith A J,Bahai A.Energy-efficiency of MIMO and Cooperative MIMO Techniques in Sensor Networks[J].IEEE Journ.of Select.Areas.Commun.,2003,22(6).
  • 3Nosratinia A,Hunter T E,Hedayat A.Cooperative Communication in Wireless Networks[J].IEEE Comm Mag.,2004,42(10):74-80.
  • 4Jayaweera S K.An Energy-efficient Virtual MIMO Communications Architecture Based on V-BLAST Processing for Distributed Wireless Sensor Networks[C]//Proc.of the 1st Annual Conf.on Sensor and Ad Hoc Commun.and Networks,Santa Clara,Calif,USA.2004.
  • 5Jayaweera S K.Energy Analysis of MIMO Techniques in Wireless Sensor Networks[C]//Proc.of the 38th Annual Conf.on Inform.Sci.and Syst.,Princeton,NJ.2004.
  • 6Jayaweera S L,Chebolu M L.Virtual MIMO and Distributed Signal Processing for Sensor Networks--An Integrated Approach[C]// IEEE International Conference on Communications.2005-02:1214-1218.
  • 7Cui S,Goldsmith A J,Bahai A.Modulation Optimization Under Energy Constraints[C]//Proc.of IEEE International Conference on Communications,AK.2003:2805-2811.
  • 8Cui S,Goldsmith A J,Bahai A.Energy-constrained Modulation Optimization[J].IEEE Trans.on Wireless Commun.,2004:4(5),2349-2360.
  • 9Vucetic B,Yuan J H.Space-time Coding[M].England:John Wiley & Sons Ltd.,2003.
  • 10Rappaport T S.Wireless Communication Principles and Pratice[M].[S.l.]:Publishing House of Electronics Industry,2001.

共引文献10

同被引文献29

引证文献4

二级引证文献5

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部