A Low-Cost Outdoor Fingerprinting Localization Scheme For Wireless Cellular Networks

doi:10.12142/ZTECOM.201903007

ZTE Communications ›› 2019, Vol. 17 ›› Issue (3): 42-49.DOI: 10.12142/ZTECOM.201903007

收稿日期:2019-05-18 出版日期:2019-09-29 发布日期:2019-12-06

A Low-Cost Outdoor Fingerprinting Localization Scheme For Wireless Cellular Networks

PEI Dengke, XU Xiaodong, QIN Xiaowei, LIU Dongliang, ZHAO Chunhua

Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, Anhui 230027, China

Received:2019-05-18 Online:2019-09-29 Published:2019-12-06
About author:PEI Dengke (pdke1@mail.ustc.end.cn) received the B.S. degree from China University of Geosciences, China in 2016. She is currently pursuing the B.E. degree at University of Science and Technology of China. Her research interest is localization and deep learning.|XU Xiaodong received his B.Eng. degree and Ph.D. degree in electronic and information engineering from University of Science and Technology of China (USTC) in 2000 and 2007, respectively. Since 2007, he has been a faculty member with the Department of Electronic Engineering and Information Science, USTC, where he is currently an associate professor. His research interests include array signal processing, wireless communications, and information-theoretic security.|QIN Xiaowei received the B.S. and Ph.D. degrees from the Department of Electrical Engineering and Information Science, University of Science and Technology of China (USTC) in 2000 and 2008, respectively. Since 2014, he has been a member of staff in Key Laboratory of Wireless-Optical Communications of Chinese Academy of Sciences at USTC. His research interests include optimization theory, service modeling in future heterogeneous networks, and big data in mobile communication networks.|LIU Dongliang received the B.S. degrees from the Telecommunications Engineering College, Beijing University of Posts and Telecommunications (BUPT), China, in 2004. Since 2006, he has been an Algorithms Researcher of the Algorithms Department in ZTE Corporation. His research interests include positioning theory, network optimization theory and big data in mobile communications.|ZHAO Chunhua received the M.S. degrees from the College of Electronic and Communication Engineering, Harbin Institute of Technology (HIT), China in 2002. Since then, she has been working on RRM algorithms design and network optimization in mobile communications. She has been an algorithms researcher at the Algorithms Department of ZTE Corporation since 2009. Her research interest is big data analytics for network optimizationeas of experimental regions are chosen as 100×100 in mobile communications.
Supported by:
This work was supported by the ZTE Industry-Academia-Research Cooperation Funds under Grant(No. 20160722-01)

摘要/Abstract

Abstract:

This paper considers outdoor fingerprinting localization in LTE cellular Networks, which can localize non-cooperative user equipment (UEs) that is unwilling to provide Global Positioning System (GPS) information. We propose a low-cost fingerprinting localization scheme that can improve the localization accuracy while reducing the computational complexity. Firstly, a data filtering strategy is employed to filter the fingerprints which are far from the target UE by using the Cell-ID, Timing Advance (TA) and eNodeB environment information, and the distribution of TA difference is analyzed to guide how to use TA rationally in the filtering strategy. Then, improved Weighted K Nearest Neighbors (WKNN) are implemented on the filtered fingerprints to give the final location prediction, and the WKNN is improved by removing the fingerprints that are still far away from the most of the K neighbors. Experiment results show that the performance is improved by the proposed localization scheme, and positioning errors corresponding to Cumulative Distribution Function (CDF) equaling to 67% and 95% are declined to 50 m and 150 m.

Key words: fingerprinting localization, TA, filtering strategy, improved WKNN

. [J]. ZTE Communications, 2019, 17(3): 42-49.

PEI Dengke, XU Xiaodong, QIN Xiaowei, LIU Dongliang, ZHAO Chunhua. A Low-Cost Outdoor Fingerprinting Localization Scheme For Wireless Cellular Networks[J]. ZTE Communications, 2019, 17(3): 42-49.

图/表 9

Figure 1. An architecture of fingerprinting localization for 4G system.

Table 1 Information of reference points

Longitude	Latitude	Severing Cell-ID	TA	Detectable eNodeBs	Cell-ID₁	…	Cell-ID_i	…	Cell-ID_N
$x$	$y$	Cell-ID_n	$m$	$l$	RSRP₁	…	RSRP_i	…	RSRP_N

Table 1 Information of reference points

Longitude	Latitude	Severing Cell-ID	TA	Detectable eNodeBs	Cell-ID₁	…	Cell-ID_i	…	Cell-ID_N
$x$	$y$	Cell-ID_n	$m$	$l$	RSRP₁	…	RSRP_i	…	RSRP_N

Figure 2. The proposed fingerprinting localization scheme.

Figure 3. Filtering Results.

Table 2 Positioning error with different filtering strategies…

Figure 4. Positioning error with different filtering strategies.

Table 3 Comparison of different matching algorithms.

		67% error/m	95% error/m	Mean error/m
$100 × 100$ m²	WKNN SVM BPNN	23 23 25	43 45 56	18 19 22
$400 × 400$ m²	WKNN SVM BPNN	27 29 39	79 73 77	27 27 35
$1 000 × 1 000$ m²	WKNN SVM BPNN	30 46 70	100 155 191	33 49 70

Table 3 Comparison of different matching algorithms.

		67% error/m	95% error/m	Mean error/m
$100 × 100$ m²	WKNN SVM BPNN	23 23 25	43 45 56	18 19 22
$400 × 400$ m²	WKNN SVM BPNN	27 29 39	79 73 77	27 27 35
$1 000 × 1 000$ m²	WKNN SVM BPNN	30 46 70	100 155 191	33 49 70

Table 4 Comparison between WKNN and the improved WKNN

Experimental areas	Matching algorithm	67% error/m	95% error/m
35 000 ×35 000 m²	WKNN	46	147
35 000 ×35 000 m²	Improved WKNN	44	139

Table 5 Localization in different districts

	67% error/m	95% error/m	Mean error/m
District A	44	140	50
District B	44	132	48
District C	43	127	50

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A Low-Cost Outdoor Fingerprinting Localization Scheme For Wireless Cellular Networks

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