Weighted k-nearest neighbour model for indoor VLC positioning
Weighted k-nearest neighbour model for indoor VLC positioning
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DOI：
10.1049/iet-com.2016.0961
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发表时间：
2017-04-20
影响因子：
1.6
通讯作者：
Burton, Andrew
中科院分区：
文献类型：
--
作者：
Manh The Van;Nguyen Van Tuan;Burton, Andrew
这项研究介绍了一个加权K-Neart的邻居模型，用于在可见光通信（VLC）系统中定位。与VLC中的常规现有技术相比，新模型提供了更高的准确性，例如三材料。在提出的模型中，基于K-NN（称为参考点）的位置估算接收器的当前位置，并记录在查找表中。从实际接收器到参考点的欧几里得距离加权以提高准确性。仿真结果表明，所提出的模型分别在有或没有环境光干扰的情况下优于36和50％的精度，优于36％和50％的精度。
This study introduces a weighted k-nearest neighbour model for user positioning in a visible light communications (VLC) system. The new model offers a higher degree of accuracy compared with conventionally existing techniques in VLC, such as trilateration. In the proposed model, the current position of the receiver is estimated based on the positions of the k-NN (known as reference points) pre-defined and recorded in a lookup table. The Euclidean distances from the actual receiver to the reference points are weighted in order to improve accuracy. Simulation results show that the proposed model outperforms the trilateration method by 36 and 50% accuracy with and without ambient light interference, respectively.