On distinguishing the multiple radio paths in RSS-based ranging

Dian ZHANG*, Yunhuai LIU, Xiaonan GUO, Min GAO, Lionel M. NI

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

29 Citations (Scopus)

Abstract

Among the various ranging techniques, Radio Signal Strength (RSS) based approaches attract intensive research interests because of its low cost and wide applicability. RSS-based ranging is apt to be affected by the multipath phenomenon which allows the radio signals to reach the destination through multiple propagation paths. To address this issue, previous works try to profile the environment and refer this profile in run-time. In practical dynamic environments, however, the profile frequently changes and the painful retraining is needed. Rather than such static ways of profiling the environments, in this paper, we try to accommodate the environmental dynamics automatically in real-time. The key observation is that given a pair of nodes, the RSS at different spectrum channels will be different. This difference carries the valuable phase information of the radio signals. By analyzing these RSS values, we are able to identify the amplitude of signals solely from the Line-of-Sight (LOS) path. This LOS amplitude is a simple function of the path length (the physical distance). We find that the analysis is a typical non-linear curvature fitting problem that has no general routing algorithms. We prove this problem format is ill-conditioned which has no stable and trustable solutions. To deal with this issue, we further explore the practical considerations for the problem and reform it to a greatly improved conditioning shape. We solve the problem by numerical iterations and implement these ideas in a real-time indoor tracking system called MuD. MuD employs only three TelosB nodes as anchors. The experiment results show that in a dynamic environment where five people move around, the averaged localization error is 1 meter. Compared with the traditional RSS-based approaches in dynamic environment, the accuracy improves up to 10 times.

Original languageEnglish
Title of host publication2012 Proceedings IEEE INFOCOM, INFOCOM 2012
Place of PublicationPiscataway
PublisherIEEE
Pages2201-2209
Number of pages9
ISBN (Electronic)9781467307758
ISBN (Print)9781467307734
DOIs
Publication statusPublished - 4 Jun 2012
Externally publishedYes
EventIEEE Conference on Computer Communications, INFOCOM 2012 - Orlando, FL, United States
Duration: 25 Mar 201230 Mar 2012

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X

Conference

ConferenceIEEE Conference on Computer Communications, INFOCOM 2012
CountryUnited States
CityOrlando, FL
Period25/03/1230/03/12

Fingerprint

Routing algorithms
Anchors
Costs
Experiments

Keywords

  • Receivers
  • Distance measurement
  • Radio transmitters
  • Mathematical model
  • Hardware
  • Training
  • Radio propagation

Cite this

ZHANG, D., LIU, Y., GUO, X., GAO, M., & NI, L. M. (2012). On distinguishing the multiple radio paths in RSS-based ranging. In 2012 Proceedings IEEE INFOCOM, INFOCOM 2012 (pp. 2201-2209). [6195605] (Proceedings - IEEE INFOCOM). Piscataway: IEEE. https://doi.org/10.1109/INFCOM.2012.6195605
ZHANG, Dian ; LIU, Yunhuai ; GUO, Xiaonan ; GAO, Min ; NI, Lionel M. / On distinguishing the multiple radio paths in RSS-based ranging. 2012 Proceedings IEEE INFOCOM, INFOCOM 2012. Piscataway : IEEE, 2012. pp. 2201-2209 (Proceedings - IEEE INFOCOM).
@inproceedings{d556384c6a6b44df8a7b5de8dbf6752b,
title = "On distinguishing the multiple radio paths in RSS-based ranging",
abstract = "Among the various ranging techniques, Radio Signal Strength (RSS) based approaches attract intensive research interests because of its low cost and wide applicability. RSS-based ranging is apt to be affected by the multipath phenomenon which allows the radio signals to reach the destination through multiple propagation paths. To address this issue, previous works try to profile the environment and refer this profile in run-time. In practical dynamic environments, however, the profile frequently changes and the painful retraining is needed. Rather than such static ways of profiling the environments, in this paper, we try to accommodate the environmental dynamics automatically in real-time. The key observation is that given a pair of nodes, the RSS at different spectrum channels will be different. This difference carries the valuable phase information of the radio signals. By analyzing these RSS values, we are able to identify the amplitude of signals solely from the Line-of-Sight (LOS) path. This LOS amplitude is a simple function of the path length (the physical distance). We find that the analysis is a typical non-linear curvature fitting problem that has no general routing algorithms. We prove this problem format is ill-conditioned which has no stable and trustable solutions. To deal with this issue, we further explore the practical considerations for the problem and reform it to a greatly improved conditioning shape. We solve the problem by numerical iterations and implement these ideas in a real-time indoor tracking system called MuD. MuD employs only three TelosB nodes as anchors. The experiment results show that in a dynamic environment where five people move around, the averaged localization error is 1 meter. Compared with the traditional RSS-based approaches in dynamic environment, the accuracy improves up to 10 times.",
keywords = "Receivers, Distance measurement, Radio transmitters, Mathematical model, Hardware, Training, Radio propagation",
author = "Dian ZHANG and Yunhuai LIU and Xiaonan GUO and Min GAO and NI, {Lionel M.}",
year = "2012",
month = "6",
day = "4",
doi = "10.1109/INFCOM.2012.6195605",
language = "English",
isbn = "9781467307734",
series = "Proceedings - IEEE INFOCOM",
publisher = "IEEE",
pages = "2201--2209",
booktitle = "2012 Proceedings IEEE INFOCOM, INFOCOM 2012",

}

ZHANG, D, LIU, Y, GUO, X, GAO, M & NI, LM 2012, On distinguishing the multiple radio paths in RSS-based ranging. in 2012 Proceedings IEEE INFOCOM, INFOCOM 2012., 6195605, Proceedings - IEEE INFOCOM, IEEE, Piscataway, pp. 2201-2209, IEEE Conference on Computer Communications, INFOCOM 2012, Orlando, FL, United States, 25/03/12. https://doi.org/10.1109/INFCOM.2012.6195605

On distinguishing the multiple radio paths in RSS-based ranging. / ZHANG, Dian; LIU, Yunhuai; GUO, Xiaonan; GAO, Min; NI, Lionel M.

2012 Proceedings IEEE INFOCOM, INFOCOM 2012. Piscataway : IEEE, 2012. p. 2201-2209 6195605 (Proceedings - IEEE INFOCOM).

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

TY - GEN

T1 - On distinguishing the multiple radio paths in RSS-based ranging

AU - ZHANG, Dian

AU - LIU, Yunhuai

AU - GUO, Xiaonan

AU - GAO, Min

AU - NI, Lionel M.

PY - 2012/6/4

Y1 - 2012/6/4

N2 - Among the various ranging techniques, Radio Signal Strength (RSS) based approaches attract intensive research interests because of its low cost and wide applicability. RSS-based ranging is apt to be affected by the multipath phenomenon which allows the radio signals to reach the destination through multiple propagation paths. To address this issue, previous works try to profile the environment and refer this profile in run-time. In practical dynamic environments, however, the profile frequently changes and the painful retraining is needed. Rather than such static ways of profiling the environments, in this paper, we try to accommodate the environmental dynamics automatically in real-time. The key observation is that given a pair of nodes, the RSS at different spectrum channels will be different. This difference carries the valuable phase information of the radio signals. By analyzing these RSS values, we are able to identify the amplitude of signals solely from the Line-of-Sight (LOS) path. This LOS amplitude is a simple function of the path length (the physical distance). We find that the analysis is a typical non-linear curvature fitting problem that has no general routing algorithms. We prove this problem format is ill-conditioned which has no stable and trustable solutions. To deal with this issue, we further explore the practical considerations for the problem and reform it to a greatly improved conditioning shape. We solve the problem by numerical iterations and implement these ideas in a real-time indoor tracking system called MuD. MuD employs only three TelosB nodes as anchors. The experiment results show that in a dynamic environment where five people move around, the averaged localization error is 1 meter. Compared with the traditional RSS-based approaches in dynamic environment, the accuracy improves up to 10 times.

AB - Among the various ranging techniques, Radio Signal Strength (RSS) based approaches attract intensive research interests because of its low cost and wide applicability. RSS-based ranging is apt to be affected by the multipath phenomenon which allows the radio signals to reach the destination through multiple propagation paths. To address this issue, previous works try to profile the environment and refer this profile in run-time. In practical dynamic environments, however, the profile frequently changes and the painful retraining is needed. Rather than such static ways of profiling the environments, in this paper, we try to accommodate the environmental dynamics automatically in real-time. The key observation is that given a pair of nodes, the RSS at different spectrum channels will be different. This difference carries the valuable phase information of the radio signals. By analyzing these RSS values, we are able to identify the amplitude of signals solely from the Line-of-Sight (LOS) path. This LOS amplitude is a simple function of the path length (the physical distance). We find that the analysis is a typical non-linear curvature fitting problem that has no general routing algorithms. We prove this problem format is ill-conditioned which has no stable and trustable solutions. To deal with this issue, we further explore the practical considerations for the problem and reform it to a greatly improved conditioning shape. We solve the problem by numerical iterations and implement these ideas in a real-time indoor tracking system called MuD. MuD employs only three TelosB nodes as anchors. The experiment results show that in a dynamic environment where five people move around, the averaged localization error is 1 meter. Compared with the traditional RSS-based approaches in dynamic environment, the accuracy improves up to 10 times.

KW - Receivers

KW - Distance measurement

KW - Radio transmitters

KW - Mathematical model

KW - Hardware

KW - Training

KW - Radio propagation

UR - http://www.scopus.com/inward/record.url?scp=84861580930&partnerID=8YFLogxK

U2 - 10.1109/INFCOM.2012.6195605

DO - 10.1109/INFCOM.2012.6195605

M3 - Conference paper (refereed)

AN - SCOPUS:84861580930

SN - 9781467307734

T3 - Proceedings - IEEE INFOCOM

SP - 2201

EP - 2209

BT - 2012 Proceedings IEEE INFOCOM, INFOCOM 2012

PB - IEEE

CY - Piscataway

ER -

ZHANG D, LIU Y, GUO X, GAO M, NI LM. On distinguishing the multiple radio paths in RSS-based ranging. In 2012 Proceedings IEEE INFOCOM, INFOCOM 2012. Piscataway: IEEE. 2012. p. 2201-2209. 6195605. (Proceedings - IEEE INFOCOM). https://doi.org/10.1109/INFCOM.2012.6195605