摘要
针对无线传感器网络(wireless sensor networks,WSNs)中降低节点间的通信开销的需求,提出一种基于成对广播同步协议(pairwise broadcast synchronization,PBS)改进的联合时钟同步和定位算法。在联合时钟同步和定位过程中,锚节点(位置已知,时钟需同步)侦听未知节点(位置未知,时钟需同步)与参考节点(位置已知,时钟为参考时钟)双向交换的时间信息,不用发送额外的信息。因此相比于传统基于双向信息交换方式的联合时钟同步和定位算法可以节省大量的通信开销,同时可以降低同步所需参考节点的数目。该算法不仅对未知节点的位置参数和时钟参数进行联合估计,同时也完成锚节点时钟参数的估计。经过仿真分析,估计值满足所推导的克拉美罗下限(cramer-rao lower bound,CRLB),且估计精度接近其他两种典型联合算法。综合考虑估计精度和通信开销,所提出的算法优于现有的联合时钟同步和定位算法。
Aiming at the demand of reducing the communication overhead in wireless sensor networks( WSNs),we propose a joint clock synchronization and localization algorithm based on modified pairwise broadcast synchronization( PBS) protocol. In our proposed scheme,anchor nodes( unknown clock bias and known position) overhear the timing message exchanges of reference node( known clock bias and known position) and unknown node( unknown clock bias and unknown position) without sending extra messages. So the proposed algorithm can reduce more communication overhead and require less reference nodes than those algorithms based on two-way message exchanges model. In the proposed algorithm,we obtain estimators of clock and localization parameters of unknown node,the estimators of clock parameters of anchor nodes. Via analyzing and simulating its estimation performance,we can find the estimation performance of the proposed algorithm meets these cramer-rao lower bound( CRLB) and is close to the estimation performance of other two available algorithms. Considering the tradeoff between the estimation performance and communication overhead,we can see that this algorithm performs better than the available joint clock synchronization and localization algorithms.
出处
《重庆邮电大学学报(自然科学版)》
CSCD
北大核心
2016年第1期30-36,共7页
Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition)
基金
国家自然科学基金项目(61172054
61362006)
广西自然科学基金项目(2014GXNSFAA118387
2013GXNSFAA019334)
桂林电子科技大学研究生创新项目(GDYCSZ201409)~~
关键词
无线传感器网络
联合时钟同步和定位
通信开销
wireless sensor networks
joint clock synchronization and localization
communication overhead