Indoor Wi-Fi fingerprint localization method based on CSI tensor decomposition

Mu ZHOU; Yuexin LONG; Qiaolin PU; Yong WANG; Wei HE

doi:10.11959/j.issn.1000-436x.2021218

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Indoor Wi-Fi fingerprint localization method based on CSI tensor decomposition

Papers | 更新时间：2024-06-05

- Indoor Wi-Fi fingerprint localization method based on CSI tensor decomposition
- Journal on Communications Vol. 42, Issue 11, Pages: 159-171(2021)
- 作者机构：
  
  1. 重庆邮电大学通信与信息工程学院，重庆 400065
  2. 重庆邮电大学移动通信技术重庆市重点实验室，重庆 400065
- 作者简介：
- 基金信息：
  
  The Science and Technology Research Program of Chongqing Municipal Education Commission(KJZD-K202000605);The Science and Technology Research Program of Chongqing Municipal Education Commission(KJQN201900603);Chongqing Natural Science Foundation Project(cstc2020jcyj-msxmX0842);Chongqing Natural Science Foundation Project(cstc2020jcyj-msxmX0865);The National Natural Science Foundation of China(61901076);The National Natural Science Foundation of China(61704015);Postgraduate Scientific Research and Innovation Project of Chongqing(CYS21293)
- DOI：10.11959/j.issn.1000-436x.2021218
  CLC： TN92
- Online First：2021-11，
  
  Published：25 November 2021
- 稿件说明：
移动端阅览
Mu ZHOU, Yuexin LONG, Qiaolin PU, et al. Indoor Wi-Fi fingerprint localization method based on CSI tensor decomposition[J]. Journal on Communications, 2021, 42(11): 159-171.
DOI：

Mu ZHOU, Yuexin LONG, Qiaolin PU, et al. Indoor Wi-Fi fingerprint localization method based on CSI tensor decomposition[J]. Journal on Communications, 2021, 42(11): 159-171. DOI： 10.11959/j.issn.1000-436x.2021218.

摘要

针对指纹库规模的增大导致CSI指纹的训练成本和处理复杂性显著增加的问题，提出了一种基于CSI张量分解的室内Wi-Fi指纹定位方法。首先，将基于平行因子分析模型的张量分解算法和交替最小二乘迭代算法相结合以减少环境噪声的干扰；其次，利用张量小波分解算法对降噪后的张量进行特征提取以得到CSI位置指纹；最后，基于偏最小二乘回归算法建立定位模型以实现位置估计。实验结果表明，所提算法在定位误差4 m内的置信概率为94.88%，验证了其在拟合CSI 位置指纹和位置坐标关系的同时具有较好的定位性能。

Abstract

Aiming at the problem that as the scale of the fingerprint database increases

the training cost and processing complexity of CSI fingerprints will also greatly increase

an indoor Wi-Fi fingerprint localization method based on CSI tensor decomposition was proposed.Firstly

the tensor decomposition algorithm based on the PARAFAC (parallel factor) analysis model and the ALS (alternate least squares) iterative algorithm were combined to reduce the interference of the environment.Then

the tensor wavelet decomposition algorithm was used to extract the feature and obtain the CSI fingerprint.Finally

a localization model was established based on the PLSR (partial least squares regression) algorithm to realize the location estimation.Experimental results show that the confidence probability of the proposed method is 94.88% within 4 m localization error

which verifies that the proposed method has good localization performance while fitting the relationship between CSI location fingerprints and location coordinates.

关键词

Keywords

references

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