A Signal Separation Method for Physical Wireless Parameter Conversion Sensor Networks Using K-Shortest Path

Shuhei Yamasaki, Minato Oriuchi, O. Takyu, K. Shirai, T. Fujii, M. Ohta, F. Sasamori, S. Handa
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Abstract

Addressing low delay and high traffic performance is a technique necessary for wireless sensor networks (WSN). Although physical wireless parameter conversion sensor networks (PhyC-SN) achieve simultaneous information gathering from multiple sensors, separating the gathered mixed sensing results becomes a difficult problem. The proposed method utilizes an approach used in multi target tracking (MTT) in order to separate the mixed data points into a set of sequential ones. Particularly, we regard the data separation problem as path planning problems. In short, we consider paths by connecting data points observed at the adjacent time, and find a set of continuous paths consisting of data points of the same sensor. Following the problem, the same number of paths as sensors are obtained, so all sensing results can be correctly discriminated and labeled over all times in WSN. Therefore, we focus on a $k$-shortest pass method of MTT. In this paper, we show the accuracy of signal separation through simulation experiments and evaluate it in terms of the precision rate quantitatively.
基于k -最短路径的物理无线参数转换传感器网络信号分离方法
解决低延迟和高流量性能是实现无线传感器网络的必要技术。物理无线参数转换传感器网络(physical wireless parameter conversion sensor network, physical - sn)实现了对多个传感器的信息同时采集,但对采集到的混合传感结果进行分离是一个难题。该方法利用多目标跟踪(MTT)中的一种方法,将混合数据点分离成一组连续的数据点。特别地,我们把数据分离问题看作是路径规划问题。简而言之,我们通过连接相邻时间观测到的数据点来考虑路径,并找到由同一传感器的数据点组成的一组连续路径。根据该问题,获得与传感器相同数量的路径,从而在WSN中始终能够正确地区分和标记所有的传感结果。因此,我们重点研究了MTT的k次最短传递方法。本文通过仿真实验证明了信号分离的准确性,并从精度率方面对其进行了定量评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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