SDR based indoor localization using ambient WiFi and GSM signals

Varun Nambiar; Edwin Vattapparamban; Ali I. Yurekli; Ismail Guvenc; Mohammad Mozaffari; Walid Saad

doi:10.1109/ICCNC.2017.7876262

SDR based indoor localization using ambient WiFi and GSM signals

Varun Nambiar
, Edwin Vattapparamban
, Ali I. Yurekli
, Ismail Guvenc
, Mohammad Mozaffari
, Walid Saad

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

15 Citations (Scopus)

Abstract

In this paper, experimental results with software defined radios (SDRs) for capturing and localizing WiFi and GSM users are developed. First, a detailed overview on various SDR equipment and software, such as embedded and networked USRPs, WiFi Pineapple, GNU Radio, OpenBTS, and Wireshark is presented. Sufficient details are provided on how to configure and operate the SDR equipment and the associated software. Measurement data is then collected from both WiFi and GSM signals, and least squares localization techniques are used for finding the target device's location. The obtained indoor localization accuracies are shown to be reasonable, considering that off-the-shelf equipment has been used with passive sniffing of a target user's signal strength.

Original language	English
Title of host publication	2017 International Conference on Computing, Networking and Communications, ICNC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	952-957
Number of pages	6
ISBN (Electronic)	9781509045884
DOIs	https://doi.org/10.1109/ICCNC.2017.7876262
Publication status	Published - 10 Mar 2017
Event	2017 International Conference on Computing, Networking and Communications, ICNC 2017 - Silicon Valley, United States Duration: 26 Jan 2017 → 29 Jan 2017

Publication series

Name	2017 International Conference on Computing, Networking and Communications, ICNC 2017

Conference

Conference	2017 International Conference on Computing, Networking and Communications, ICNC 2017
Country/Territory	United States
City	Silicon Valley
Period	26/01/17 → 29/01/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

Keywords

GSM
Internet of things (IoT)
OpenBTS
RSS
SDR
USRP E310
USRP N210
WiFi
indoor localization

Access to Document

10.1109/ICCNC.2017.7876262

Cite this

Nambiar, V., Vattapparamban, E., Yurekli, A. I., Guvenc, I., Mozaffari, M., & Saad, W. (2017). SDR based indoor localization using ambient WiFi and GSM signals. In 2017 International Conference on Computing, Networking and Communications, ICNC 2017 (pp. 952-957). Article 7876262 (2017 International Conference on Computing, Networking and Communications, ICNC 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCNC.2017.7876262

Nambiar, Varun ; Vattapparamban, Edwin ; Yurekli, Ali I. et al. / SDR based indoor localization using ambient WiFi and GSM signals. 2017 International Conference on Computing, Networking and Communications, ICNC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 952-957 (2017 International Conference on Computing, Networking and Communications, ICNC 2017).

@inproceedings{bb3727f3c6c44ec8bbbbaabf8996e584,

title = "SDR based indoor localization using ambient WiFi and GSM signals",

abstract = "In this paper, experimental results with software defined radios (SDRs) for capturing and localizing WiFi and GSM users are developed. First, a detailed overview on various SDR equipment and software, such as embedded and networked USRPs, WiFi Pineapple, GNU Radio, OpenBTS, and Wireshark is presented. Sufficient details are provided on how to configure and operate the SDR equipment and the associated software. Measurement data is then collected from both WiFi and GSM signals, and least squares localization techniques are used for finding the target device's location. The obtained indoor localization accuracies are shown to be reasonable, considering that off-the-shelf equipment has been used with passive sniffing of a target user's signal strength.",

keywords = "GSM, Internet of things (IoT), OpenBTS, RSS, SDR, USRP E310, USRP N210, WiFi, indoor localization",

author = "Varun Nambiar and Edwin Vattapparamban and Yurekli, \{Ali I.\} and Ismail Guvenc and Mohammad Mozaffari and Walid Saad",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 International Conference on Computing, Networking and Communications, ICNC 2017 ; Conference date: 26-01-2017 Through 29-01-2017",

year = "2017",

month = mar,

day = "10",

doi = "10.1109/ICCNC.2017.7876262",

language = "English",

series = "2017 International Conference on Computing, Networking and Communications, ICNC 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "952--957",

booktitle = "2017 International Conference on Computing, Networking and Communications, ICNC 2017",

address = "United States",

}

Nambiar, V, Vattapparamban, E, Yurekli, AI, Guvenc, I, Mozaffari, M & Saad, W 2017, SDR based indoor localization using ambient WiFi and GSM signals. in 2017 International Conference on Computing, Networking and Communications, ICNC 2017., 7876262, 2017 International Conference on Computing, Networking and Communications, ICNC 2017, Institute of Electrical and Electronics Engineers Inc., pp. 952-957, 2017 International Conference on Computing, Networking and Communications, ICNC 2017, Silicon Valley, United States, 26/01/17. https://doi.org/10.1109/ICCNC.2017.7876262

SDR based indoor localization using ambient WiFi and GSM signals. / Nambiar, Varun; Vattapparamban, Edwin; Yurekli, Ali I. et al.
2017 International Conference on Computing, Networking and Communications, ICNC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 952-957 7876262 (2017 International Conference on Computing, Networking and Communications, ICNC 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - SDR based indoor localization using ambient WiFi and GSM signals

AU - Nambiar, Varun

AU - Vattapparamban, Edwin

AU - Yurekli, Ali I.

AU - Guvenc, Ismail

AU - Mozaffari, Mohammad

AU - Saad, Walid

PY - 2017/3/10

Y1 - 2017/3/10

N2 - In this paper, experimental results with software defined radios (SDRs) for capturing and localizing WiFi and GSM users are developed. First, a detailed overview on various SDR equipment and software, such as embedded and networked USRPs, WiFi Pineapple, GNU Radio, OpenBTS, and Wireshark is presented. Sufficient details are provided on how to configure and operate the SDR equipment and the associated software. Measurement data is then collected from both WiFi and GSM signals, and least squares localization techniques are used for finding the target device's location. The obtained indoor localization accuracies are shown to be reasonable, considering that off-the-shelf equipment has been used with passive sniffing of a target user's signal strength.

AB - In this paper, experimental results with software defined radios (SDRs) for capturing and localizing WiFi and GSM users are developed. First, a detailed overview on various SDR equipment and software, such as embedded and networked USRPs, WiFi Pineapple, GNU Radio, OpenBTS, and Wireshark is presented. Sufficient details are provided on how to configure and operate the SDR equipment and the associated software. Measurement data is then collected from both WiFi and GSM signals, and least squares localization techniques are used for finding the target device's location. The obtained indoor localization accuracies are shown to be reasonable, considering that off-the-shelf equipment has been used with passive sniffing of a target user's signal strength.

KW - GSM

KW - Internet of things (IoT)

KW - OpenBTS

KW - RSS

KW - SDR

KW - USRP E310

KW - USRP N210

KW - WiFi

KW - indoor localization

UR - https://www.scopus.com/pages/publications/85017381307

U2 - 10.1109/ICCNC.2017.7876262

DO - 10.1109/ICCNC.2017.7876262

M3 - Conference contribution

AN - SCOPUS:85017381307

T3 - 2017 International Conference on Computing, Networking and Communications, ICNC 2017

SP - 952

EP - 957

BT - 2017 International Conference on Computing, Networking and Communications, ICNC 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2017 International Conference on Computing, Networking and Communications, ICNC 2017

Y2 - 26 January 2017 through 29 January 2017

ER -

Nambiar V, Vattapparamban E, Yurekli AI, Guvenc I, Mozaffari M, Saad W. SDR based indoor localization using ambient WiFi and GSM signals. In 2017 International Conference on Computing, Networking and Communications, ICNC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 952-957. 7876262. (2017 International Conference on Computing, Networking and Communications, ICNC 2017). doi: 10.1109/ICCNC.2017.7876262

SDR based indoor localization using ambient WiFi and GSM signals

Abstract

Publication series

Conference

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this