New RSSI-Based LoRa Localization Algorithms for Very Noisy Outdoor Environment

Ka Ho Lam; Chi Chung Cheung; Wah Ching Lee

doi:10.1109/COMPSAC.2018.10340

New RSSI-Based LoRa Localization Algorithms for Very Noisy Outdoor Environment

Ka Ho Lam, Chi Chung Cheung, Wah Ching Lee

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

36 Citations (Scopus)

Abstract

It have been proved that LoRa networks are suitable to do the localization for outdoor environment [1] [2]. Through the performance investigation in simulation models and real experiments, it showed that the performance of RSSI-based LoRa localization algorithms in [1] is compatible to The Global Positioning System (GPS), the most popular outdoor localization system. However, in very noisy outdoor environment, the performance of the algorithms degrades significantly because the effect of noisy nodes (anchor nodes that are highly affected by noise) cannot be totally avoided in localization. Based on this observation, we propose two new RSSI-based LoRa localization algorithms to further improve the accuracy of the localization for very noisy outdoor environment. One new algorithm iteratively removes all noisy nodes and use the remaining anchor nodes to process the localization; while the other new algorithm uses density clustering to get the best estimation. Our performance investigation shows that the proposed algorithms outperform the algorithms in [1] significantly in terms of the localization error if the outdoor environment is very noisy.

Original language	English
Title of host publication	Proceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018
Editors	Claudio Demartini, Sorel Reisman, Ling Liu, Edmundo Tovar, Hiroki Takakura, Ji-Jiang Yang, Chung-Horng Lung, Sheikh Iqbal Ahamed, Kamrul Hasan, Thomas Conte, Motonori Nakamura, Zhiyong Zhang, Toyokazu Akiyama, William Claycomb, Stelvio Cimato
Publisher	IEEE Computer Society
Pages	794-799
Number of pages	6
ISBN (Electronic)	9781538626665
DOIs	https://doi.org/10.1109/COMPSAC.2018.10340
Publication status	Published - 23 Jul 2018
Event	42nd IEEE Computer Software and Applications Conference, COMPSAC 2018 - Tokyo, Japan Duration: 23 Jul 2018 → 27 Jul 2018

Publication series

Name	Proceedings - International Computer Software and Applications Conference
Volume	2
ISSN (Print)	0730-3157

Conference

Conference	42nd IEEE Computer Software and Applications Conference, COMPSAC 2018
Country/Territory	Japan
City	Tokyo
Period	23/07/18 → 27/07/18

Keywords

Localization system
LoRa technology
Smart environment
Urban networking

ASJC Scopus subject areas

Software
Computer Science Applications

More information

10.1109/COMPSAC.2018.10340

http://hdl.handle.net/10397/107199

Cite this

Lam, K. H., Cheung, C. C., & Lee, W. C. (2018). New RSSI-Based LoRa Localization Algorithms for Very Noisy Outdoor Environment. In C. Demartini, S. Reisman, L. Liu, E. Tovar, H. Takakura, J.-J. Yang, C.-H. Lung, S. I. Ahamed, K. Hasan, T. Conte, M. Nakamura, Z. Zhang, T. Akiyama, W. Claycomb, & S. Cimato (Eds.), Proceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018 (pp. 794-799). Article 8377968 (Proceedings - International Computer Software and Applications Conference; Vol. 2). IEEE Computer Society. https://doi.org/10.1109/COMPSAC.2018.10340

Lam, Ka Ho ; Cheung, Chi Chung ; Lee, Wah Ching. / New RSSI-Based LoRa Localization Algorithms for Very Noisy Outdoor Environment. Proceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018. editor / Claudio Demartini ; Sorel Reisman ; Ling Liu ; Edmundo Tovar ; Hiroki Takakura ; Ji-Jiang Yang ; Chung-Horng Lung ; Sheikh Iqbal Ahamed ; Kamrul Hasan ; Thomas Conte ; Motonori Nakamura ; Zhiyong Zhang ; Toyokazu Akiyama ; William Claycomb ; Stelvio Cimato. IEEE Computer Society, 2018. pp. 794-799 (Proceedings - International Computer Software and Applications Conference).

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title = "New RSSI-Based LoRa Localization Algorithms for Very Noisy Outdoor Environment",

abstract = "It have been proved that LoRa networks are suitable to do the localization for outdoor environment [1] [2]. Through the performance investigation in simulation models and real experiments, it showed that the performance of RSSI-based LoRa localization algorithms in [1] is compatible to The Global Positioning System (GPS), the most popular outdoor localization system. However, in very noisy outdoor environment, the performance of the algorithms degrades significantly because the effect of noisy nodes (anchor nodes that are highly affected by noise) cannot be totally avoided in localization. Based on this observation, we propose two new RSSI-based LoRa localization algorithms to further improve the accuracy of the localization for very noisy outdoor environment. One new algorithm iteratively removes all noisy nodes and use the remaining anchor nodes to process the localization; while the other new algorithm uses density clustering to get the best estimation. Our performance investigation shows that the proposed algorithms outperform the algorithms in [1] significantly in terms of the localization error if the outdoor environment is very noisy.",

keywords = "Localization system, LoRa technology, Smart environment, Urban networking",

author = "Lam, {Ka Ho} and Cheung, {Chi Chung} and Lee, {Wah Ching}",

year = "2018",

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editor = "Claudio Demartini and Sorel Reisman and Ling Liu and Edmundo Tovar and Hiroki Takakura and Ji-Jiang Yang and Chung-Horng Lung and Ahamed, {Sheikh Iqbal} and Kamrul Hasan and Thomas Conte and Motonori Nakamura and Zhiyong Zhang and Toyokazu Akiyama and William Claycomb and Stelvio Cimato",

booktitle = "Proceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018",

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note = "42nd IEEE Computer Software and Applications Conference, COMPSAC 2018 ; Conference date: 23-07-2018 Through 27-07-2018",

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Lam, KH, Cheung, CC & Lee, WC 2018, New RSSI-Based LoRa Localization Algorithms for Very Noisy Outdoor Environment. in C Demartini, S Reisman, L Liu, E Tovar, H Takakura, J-J Yang, C-H Lung, SI Ahamed, K Hasan, T Conte, M Nakamura, Z Zhang, T Akiyama, W Claycomb & S Cimato (eds), Proceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018., 8377968, Proceedings - International Computer Software and Applications Conference, vol. 2, IEEE Computer Society, pp. 794-799, 42nd IEEE Computer Software and Applications Conference, COMPSAC 2018, Tokyo, Japan, 23/07/18. https://doi.org/10.1109/COMPSAC.2018.10340

New RSSI-Based LoRa Localization Algorithms for Very Noisy Outdoor Environment. / Lam, Ka Ho; Cheung, Chi Chung; Lee, Wah Ching.
Proceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018. ed. / Claudio Demartini; Sorel Reisman; Ling Liu; Edmundo Tovar; Hiroki Takakura; Ji-Jiang Yang; Chung-Horng Lung; Sheikh Iqbal Ahamed; Kamrul Hasan; Thomas Conte; Motonori Nakamura; Zhiyong Zhang; Toyokazu Akiyama; William Claycomb; Stelvio Cimato. IEEE Computer Society, 2018. p. 794-799 8377968 (Proceedings - International Computer Software and Applications Conference; Vol. 2).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AU - Lam, Ka Ho

AU - Cheung, Chi Chung

AU - Lee, Wah Ching

PY - 2018/7/23

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N2 - It have been proved that LoRa networks are suitable to do the localization for outdoor environment [1] [2]. Through the performance investigation in simulation models and real experiments, it showed that the performance of RSSI-based LoRa localization algorithms in [1] is compatible to The Global Positioning System (GPS), the most popular outdoor localization system. However, in very noisy outdoor environment, the performance of the algorithms degrades significantly because the effect of noisy nodes (anchor nodes that are highly affected by noise) cannot be totally avoided in localization. Based on this observation, we propose two new RSSI-based LoRa localization algorithms to further improve the accuracy of the localization for very noisy outdoor environment. One new algorithm iteratively removes all noisy nodes and use the remaining anchor nodes to process the localization; while the other new algorithm uses density clustering to get the best estimation. Our performance investigation shows that the proposed algorithms outperform the algorithms in [1] significantly in terms of the localization error if the outdoor environment is very noisy.

AB - It have been proved that LoRa networks are suitable to do the localization for outdoor environment [1] [2]. Through the performance investigation in simulation models and real experiments, it showed that the performance of RSSI-based LoRa localization algorithms in [1] is compatible to The Global Positioning System (GPS), the most popular outdoor localization system. However, in very noisy outdoor environment, the performance of the algorithms degrades significantly because the effect of noisy nodes (anchor nodes that are highly affected by noise) cannot be totally avoided in localization. Based on this observation, we propose two new RSSI-based LoRa localization algorithms to further improve the accuracy of the localization for very noisy outdoor environment. One new algorithm iteratively removes all noisy nodes and use the remaining anchor nodes to process the localization; while the other new algorithm uses density clustering to get the best estimation. Our performance investigation shows that the proposed algorithms outperform the algorithms in [1] significantly in terms of the localization error if the outdoor environment is very noisy.

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KW - Urban networking

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Lam KH, Cheung CC, Lee WC. New RSSI-Based LoRa Localization Algorithms for Very Noisy Outdoor Environment. In Demartini C, Reisman S, Liu L, Tovar E, Takakura H, Yang JJ, Lung CH, Ahamed SI, Hasan K, Conte T, Nakamura M, Zhang Z, Akiyama T, Claycomb W, Cimato S, editors, Proceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018. IEEE Computer Society. 2018. p. 794-799. 8377968. (Proceedings - International Computer Software and Applications Conference). doi: 10.1109/COMPSAC.2018.10340

New RSSI-Based LoRa Localization Algorithms for Very Noisy Outdoor Environment

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