Mobility prediction algorithm for mobile ad hoc network using pedestrian trajectory data
Mobility prediction algorithm for mobile ad hoc network using pedestrian trajectory data
复制标题
DOI：
10.1109/tencon.2004.1414684
复制
发表时间：
2004-11
期刊：
影响因子：
--
通讯作者：
W. Creixell;K. Sezaki
中科院分区：
文献类型：
--
作者：
W. Creixell;K. Sezaki
移动的自组网（adhoc networks，MANET）是近年来研究的热点。移动自组网是由人们可以携带的移动的节点组成的，由这些节点组成的网络具有高度变化的拓扑结构。节点根据人的移动模式移动，大量的网络任务受到节点移动性的影响。有理由认为，网络性能也受到移动性的高度影响。降低不确定性将对网络性能产生积极影响。在这项工作中，我们提出了一种方法来动态预测行人的位置。该方法使用递归最小二乘格型自适应滤波器来实现该目标，具有合理的低误差。
In the last years mobile ad hoc networks (MANET) has became a hot research subject. MANET is compound by mobile nodes that can be carried by people; the network formed by these nodes has then a highly changing topology. Nodes move according to people mobility patterns and a big number of the network tasks are influenced by nodes mobility. It is reasonable to think that network performance is also highly influenced by mobility. Reduce the uncertainty would have a positive impact on networks performance. In this work we propose a method to dynamically predict a pedestrian position. The method uses recursive least squares lattice adaptive filter to achieve that goal with reasonable low error.