research-article

Towards commoditized real-time spectrum monitoring

Authors:

Haitao ZhengAuthors Info & Claims

HotWireless '14: Proceedings of the 1st ACM workshop on Hot topics in wireless

Pages 25 - 30

https://doi.org/10.1145/2643614.2643615

Published: 11 September 2014 Publication History

Abstract

We are facing an increasingly difficult challenge in spectrum management: how to perform real-time spectrum monitoring with strong coverage of deployed regions. Today's spectrum measurements are carried out by government employees driving around with specialized hardware that is usually bulky and expensive, making the task of gathering real-time, large-scale spectrum monitoring data extremely difficult and cost prohibitive. In this paper, we propose a solution to the spectrum monitoring problem by leveraging the power of the masses, i.e. millions of wireless users, using low-cost, commoditized spectrum monitoring hardware. We envision an ecosystem where crowdsourced smartphone users perform automated and continuous spectrum measurements using their mobile devices, and report the results to a monitoring agency in real-time. We perform an initial feasibility study to verify the efficacy of our mobile monitoring platform compared to that of conventional monitoring devices like USRP GNU radios. Results indicate that commoditized real-time spectrum monitoring is indeed feasible in the near future. We conclude by presenting a set of open challenges and potential directions for follow-up research.

References

[1]

http://www.networkworld.com/article/2174194/smb/la-building--39-s-lights-interfere-with-cellular-network--fcc-says.html.

[2]

http://sdr.osmocom.org/trac/wiki/rtl-sdr.

[3]

BAHL, P., ET AL. White space networking with Wi-Fi like connectivity. In SIGCOMM (2009).

Digital Library

[4]

BERNSTEIN, M., BRANDT, J., MILLER, R., AND KARGER, D. Crowds in two seconds: Enabling realtime crowd-powered interfaces. In UIST (2011).

Digital Library

[5]

BIGHAM,J., ET AL. Vizwiz: nearly real-time answers to visual questions. In UIST (2010).

Digital Library

[6]

CHEN, H.-S., GAO, W., AND DAUT, D.G. Spectrum sensing using cyclostationary properties and application to ieee 802.22 wran. In GLOBECOM (2007).

[7]

FAGGIANI, A.A.O. Network sensing through smartphone-based crowdsourcing. In SenSys (2013).

Digital Library

[8]

FATEMIEH, O.,CHANDRA, R., AND GUNTER, C. Secure collaborative sensing for crowdsourcing spectrum data in white space networks. In DySPAN (2010).

[9]

GEMBER, A., ET AL. Obtaining in-context measurements of cellular network performance. In IMC (2012).

Digital Library

[10]

HASSANIEH,H., ET AL. Ghz-wide sensing and decoding using the sparse fourier transform. In INFOCOM (2014).

[11]

HUANG, J., ET AL. Anatomizing application performance differences on smartphones. In MobiSys (2010).

Digital Library

[12]

IYER, A.P., ET AL. SpecNet: Spectrum sensing sans frontières. In NSDI (2011).

Digital Library

[13]

KIM, H., AND SHIN, K.G. In-band spectrum sensing incognitive radio networks: energy detection or feature detection? In MobiCom (2008).

Digital Library

[14]

LASKA,J., ET AL. Compressive sensing for dynamic spectrum access networks: Techniques and tradeoffs. In DySPAN (2011).

[15]

LITTMAN, L., AND REVARE, B. New times, new methods: Upgrading spectrum enforcement. Silicon Flatirons Roundtable Series on Entrepreneurship, Innovation, and Public Policy, Feb.2014.

[16]

MEIKLE,R., AND CAMP, J. A global measurement study of context-based propagation and user mobility. In HotPlanet (2012).

Digital Library

[17]

PATRO,A., ET AL. WiSense: A client based framework for wireless diagnosis (Poster). In NSDI (2014).

[18]

RAHUL,H., ET AL. Learning to share: Narrow band-friendly wideband networks. In SIGCOMM (2008).

Digital Library

[19]

RAI, A., ET AL. Zee: Zero-effort crowd sourcing for indoor localization. In MobiCom (2012).

Digital Library

[20]

RASHIDI,M., ET AL.ANLLS based sub-nyquist rate spectrum sensing for wideband cognitive radio. In DySPAN (2011).

[21]

SEN,S., ET AL. Can they hear me now?: A case for a client-assisted approach to monitoring wide-area wireless networks. In IMC (2011).

Digital Library

[22]

THE NATIONAL TELECOMMUNICATIONS AND INFORMATION ADMINISTRATION. An Assessment of the Near-Term Viability of Accommodating Wireless Broadband Systems in the 1675--1710 MHz, 1755--1780 MHz, 3500--3650 MHz, and 4200--4220 MHz, 4380--4400 MHz Bands, October 2010.

[23]

YANG,L., ET AL. Enforcing dynamic spectrum access with spectrum permits. In MobiHoc (2012).

Digital Library

[24]

YANG,Z., ET AL . Locating in finger print space: Wireless indoor localization with little human intervention. In MobiCom (2012).

Digital Library

[25]

YOON,S., ET AL. Quicksense: Fast and energy-efficient channel sensing for dynamic spectrum access networks. In INFOCOM (2013).

[26]

YUCEK,T., AND ARSLAN,H.A survey of spectrum sensing algorithms for cognitive radio applications. Commun. Surveys Tuts. 11,1(2009),116--130.

Digital Library

[27]

ZHANG,X., ET AL. Propagation comparisons at vhf and uhf frequencies. In Radio and Wireless Symposium (2009).

Digital Library

[28]

ZHANG,Z., ET AL. On the validity of geosocial mobility traces. In HotNets (2013).

Digital Library

Cited By

Luo ZHuang QChen XWang RWu FChen GZhang Q(2024)Spectrum Sensing Everywhere: Wide-Band Spectrum Sensing With Low-Cost UWB NodesIEEE/ACM Transactions on Networking10.1109/TNET.2023.334297732:3(2112-2127)Online publication date: Jun-2024
https://doi.org/10.1109/TNET.2023.3342977
Tadik SGraves KVarner MAnderson CJohnson DKasera SPatwari NVan der Merwe JDurgin G(2024)Digital Spectrum Twins for Enhanced Spectrum Sharing and Other Radio ApplicationsIEEE Journal of Radio Frequency Identification10.1109/JRFID.2023.33272128(376-391)Online publication date: 2024
https://doi.org/10.1109/JRFID.2023.3327212
Doke KOkoro BZare AZheleva M(2024)VIA: Establishing the link between spectrum sensor capabilities and data analytics performanceIEEE INFOCOM 2024 - IEEE Conference on Computer Communications10.1109/INFOCOM52122.2024.10621266(2229-2238)Online publication date: 20-May-2024
https://doi.org/10.1109/INFOCOM52122.2024.10621266
Show More Cited By

Index Terms

Towards commoditized real-time spectrum monitoring
1. Networks
  1. Network services
    1. Network monitoring

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Published In

cover image ACM Conferences

HotWireless '14: Proceedings of the 1st ACM workshop on Hot topics in wireless

September 2014

66 pages

ISBN:9781450330763

DOI:10.1145/2643614

Program Chairs:
Shyam Gollakota
Washington University
,
Deepak Ganesan
University of Massachusetts-Amherst

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 September 2014

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MobiCom'14

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SIGMOBILE

MobiCom'14: The 20th Annual International Conference on Mobile Computing and Networking

September 11, 2014

Hawaii, Maui, USA

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HotWireless '14 Paper Acceptance Rate 10 of 10 submissions, 100%;

Overall Acceptance Rate 30 of 42 submissions, 71%

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Cited By

Luo ZHuang QChen XWang RWu FChen GZhang Q(2024)Spectrum Sensing Everywhere: Wide-Band Spectrum Sensing With Low-Cost UWB NodesIEEE/ACM Transactions on Networking10.1109/TNET.2023.334297732:3(2112-2127)Online publication date: Jun-2024
https://doi.org/10.1109/TNET.2023.3342977
Tadik SGraves KVarner MAnderson CJohnson DKasera SPatwari NVan der Merwe JDurgin G(2024)Digital Spectrum Twins for Enhanced Spectrum Sharing and Other Radio ApplicationsIEEE Journal of Radio Frequency Identification10.1109/JRFID.2023.33272128(376-391)Online publication date: 2024
https://doi.org/10.1109/JRFID.2023.3327212
Doke KOkoro BZare AZheleva M(2024)VIA: Establishing the link between spectrum sensor capabilities and data analytics performanceIEEE INFOCOM 2024 - IEEE Conference on Computer Communications10.1109/INFOCOM52122.2024.10621266(2229-2238)Online publication date: 20-May-2024
https://doi.org/10.1109/INFOCOM52122.2024.10621266
Doke KAbedi AHollingsworth MZheleva MSahai AGrunwald DGremban K(2024)Towards Data-Driven Policies in Spectrum Management2024 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)10.1109/DySPAN60163.2024.10632821(163-168)Online publication date: 13-May-2024
https://doi.org/10.1109/DySPAN60163.2024.10632821
Wang JWang WWang XWang JWang WWang X(2024)Spectrum Dynamics: Modeling, Analysis, and Design of Spectrum Activity Surveillance in DSA-Enabled SystemsEncountering Mobile Data Dynamics in Heterogeneous Wireless Networks10.1007/978-3-031-62906-8_5(123-170)Online publication date: 3-Jun-2024
https://doi.org/10.1007/978-3-031-62906-8_5
Wang JWang WWang XWang JWang WWang X(2024)IntroductionEncountering Mobile Data Dynamics in Heterogeneous Wireless Networks10.1007/978-3-031-62906-8_1(1-12)Online publication date: 3-Jun-2024
https://doi.org/10.1007/978-3-031-62906-8_1
Ahmed MBansal AYuan KKumar SSteenkiste PCosta XHassanieh HAsadi ACox LPerino DWidmer JGiustiniano D(2023)Battery-free Wideband Spectrum Mapping using Commodity RFID TagsProceedings of the 29th Annual International Conference on Mobile Computing and Networking10.1145/3570361.3592508(1-16)Online publication date: 2-Oct-2023
https://dl.acm.org/doi/10.1145/3570361.3592508
Zeng YCalvo-Palomino RGiustiniano DBovet GBanerjee S(2023)Adaptive Uplink Data Compression in Spectrum Crowdsensing SystemsIEEE/ACM Transactions on Networking10.1109/TNET.2023.323937831:5(2207-2221)Online publication date: Oct-2023
https://doi.org/10.1109/TNET.2023.3239378
Shatov VLübke MSu YFranchi N(2023)On Integrated Cooperative Radio Sensing for Spatial Electromagnetic Analysis in 6G2023 IEEE Future Networks World Forum (FNWF)10.1109/FNWF58287.2023.10520344(1-8)Online publication date: 13-Nov-2023
https://doi.org/10.1109/FNWF58287.2023.10520344
Luo ZHuang QWang RChen HTao XChen GZhang QGummeson JLee SGao JXing G(2022)WISEProceedings of the 20th ACM Conference on Embedded Networked Sensor Systems10.1145/3560905.3568541(651-666)Online publication date: 6-Nov-2022
https://dl.acm.org/doi/10.1145/3560905.3568541
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