research-article

Performance Assessment and Feasibility Analysis of IEEE 802.15.4m Wireless Sensor Networks in TV Grayspaces

Authors:

Andreas Achtzehn,

Marina Petrova,

Petri Mähönen,

Luciano BononiAuthors Info & Claims

ACM Transactions on Sensor Networks (TOSN), Volume 13, Issue 1

Article No.: 8, Pages 1 - 27

https://doi.org/10.1145/3021499

Published: 26 January 2017 Publication History

Abstract

In this article, we assess the viability of underlay sensor networks in frequencies used by an incumbent digital TV broadcasting system, that is, in the so-called TV grayspaces (TVGS). Grayspace operations are particularly interesting when other unlicensed bands are overcrowded, for example, due to high-volume WiFi operations. We simulate the operational characteristics of the recent IEEE 802.15.4m standard for low-rate wireless personal area networks to evaluate the performance degradation of an incumbent Digital Video Broadcasting - Terrestrial (DVB-T) system if a secondary network of low-power low-rate devices are co-deployed in the same frequency bands. Our results show that short sensor messages will not disrupt the DVB-T service due to the existing error-correction capabilities. Furthermore, if sufficient separation distances to primary transmitters are maintained, transmit powers are sufficient to achieve reasonable connectivity levels of the secondary network. In order to obtain realistic figures on the predicted feasibility of grayspace sensor networks, we study the deployment constraints of a hypothetical secondary network co-located with the TV broadcasting network of Germany. Our analysis shows that if we aim to support a minimum sensor-sensor distance, no universal coverage can be maintained in this country. While our quantitative results are specific to Germany, we deem them indicative for the expected results also in other potential deployments. We found that while a secondary wireless sensor network in TVGS is technically possible, the necessary constraints on operational parameters and service levels for TVGS co-existence will significantly limit its practical viability.

References

[1]

2015. World Radiocommunication Conference 2015 Agenda, Retrieved from https://www.itu.int/dms_pub/itu-r/oth/12/01/R12010000014A01PDFE.pdf.

[2]

Andreas Achtzehn, Janne Riihijärvi, and Petri Mähönen. 2014. Improving accuracy for TVWS geolocation databases: Results from measurement-driven estimation approaches. In Proceedings of the 2014 IEEE International Symposium on Dynamic Spectrum Access Networks (DYSPAN’14). IEEE, 392--403.

[3]

Andreas Achtzehn, Ljiljana Simic, Marina Petrova, and Petri Mähönen. 2015. Feasibility of secondary networks: Analysis methodology and quantitative study of cellular and Wi-Fi-like TVWS deployments. IEEE Trans. Mobile Comput. 14, 2 (Feb. 2015), 373--386.

[4]

Andreas Achtzehn, Ljiljana Simic, Marina Petrova, Petri Mähönen, Valentin Rakovic, Pero Latkoski, and Liljana Gavrilovska. 2013. Software tool for assessing secondary system opportunities in spectrum whitespaces. In Proceedings of the 14th International Symposium on “A World of Wireless, Mobile and Multimedia Networks” (WoWMoM’13). IEEE.

[5]

Amit Aggarwal, Swathi Kunta, and Pramode K. Verma. 2010. A proposed communications infrastructure for the smart grid. In Proceedings of the 2010 Innovative Smart Grid Technologies (ISGT). IEEE, 1--5.

[6]

I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci. 2002. Wireless sensor networks: A survey. Comput. Netw. 38, 4 (Mar. 2002), 393--422.

Digital Library

[7]

Andrea Bartoli, Mischa Dohler, Juan Hernández-Serrano, Apostolos Kountouris, and Dominique Barthel. 2011. Low-power low-rate goes long-range: The case for secure and cooperative machine-to-machine communications. In Proceedings of the 6th IFIP TC International Conference on Networking (NETWORKING’11). 219--230.

[8]

Luca Bedogni, Andreas Achtzehn, Marina Petrova, and Petri Mähönen. 2014a. Smart meters with TV gray spaces connectivity: A feasibility study for two reference network topologies. In Proceedings of the 2014 11th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON’14). IEEE, 537--545.

[9]

Luca Bedogni, Marco Di Felice, Fabio Malabocchia, and Luciano Bononi. 2014b. Indoor communication over TV gray spaces based on spectrum measurements. In Proceedings of the 2014 IEEE Wireless Communications and Networking Conference (WCNC’14). IEEE, 3218--3223.

[10]

Luca Bedogni, Angelo Trotta, Marco Di Felice, and Luciano Bononi. 2013. Machine-to-machine communication over TV white spaces for smart metering applications. In Proceedings of the 2013 22nd International Conference on Computer Communication and Networks (ICCCN’13). IEEE, 1--7.

[11]

Giuseppe Bianchi. 2000. Performance analysis of the IEEE 802.11 distributed coordination function. IEEE J. Select. Areas Commun. 18, 3 (2000), 535--547.

[12]

M. Brew, F. Darbari, L. H. Crockett, M. B. Waddell, M. Fitch, S. Weiss, and R. W. Stewart. 2011. UHF white space network for rural smart grid communications. In Proceedings of the IEEE International Conference on Smart Grid Communications (SmartGridComm’11). IEEE, 138--142.

[13]

C. Buratti. 2010. Performance analysis of IEEE 802.15.4 Beacon-enabled mode. IEEE Trans. Vehic. Technol. 59, 4 (2010), 2031--2045.

[14]

Chiara Buratti and Roberto Verdone. 2009. Performance analysis of IEEE 802.15.4 non Beacon-enabled mode. IEEE Trans. Vehic. Technol. 58, 7 (2009), 3480--3493.

[15]

E. Damosso and L. M. Correia. 1999. COST Action 231: Digital Mobile Radio Towards Future Generation Systems: Final Report. European Commission. Technical Report.

[16]

Department of Energy. 2010. Communications Requirements of Smart Grid Technologies. Technical Report.

[17]

ETSI. 2009. ETSI EN 300 744, Digital Video Broadcasting (DVB): Framing Structure, Channel Coding and Modulation for Digital Terrestrial Television. Technical Report.

[18]

Xi Fang, Satyajayant Misra, Guoliang Xue, and Dejun Yang. 2012. Smart grid—The new and improved power grid: A survey. IEEE Commun. Surv. Tutor. 14, 4 (Jan. 2012), 944--980.

[19]

T. G. Farr and M. Kobrick. 2000. The shuttle radar topography mission. In Proceedings of the Symposium on Space-Based Observation Technology.

[20]

FCC. 2012. Unlicensed Operation in the TV Broadcast Bands—Third Memorandum Opinion and Order. (2012). Retrieved from http://www.fcc.gov/document/tv-white-spaces-rule-changes.

[21]

R. Funada, F. Kojima, and H. Harada. 2012. IEEE 802.15.4m: The first low rate wireless personal area networks operating in TV white space. In Proceedings of the 18th IEEE International Conference on Networks (ICON). IEEE, 326--332.

[22]

Vehbi C. Gungor, Bin Lu, and Gerhard P. Hancke. 2010. Opportunities and challenges of wireless sensor networks in smart grid. IEEE Trans. Industr. Electron. 57, 10 (Oct. 2010), 3557--3564.

[23]

V. Cagri Gungor, Dilan Sahin, Taskin Kocak, Salih Ergut, Concettina Buccella, Carlo Cecati, and Gerhard P. Hancke. 2013. A survey on smart grid potential applications and communication requirements. IEEE Trans. Industr. Inf. 9, 1 (2013), 28--42.

[24]

Christian Hamacher. 2002. Guard Bands for Coexistence of UMTS and DVB in a Hybrid Radio System. Technical Report.

[25]

Kate Harrison, Shridhar Mubaraq Mishra, and Anant Saha. 2010. How much white-space capacity is there? In DySpan’10.

[26]

IEEE. IEEE Standard for Local and metropolitan area networks--Part 15.4: Low-Rate Wireless Personal Area Networks (LR-WPANs) Amendment 3: Physical Layer (PHY) Specifications for Low-Data-Rate, Wireless, Smart Metering Utility Networks.

[27]

IEEE. 2014. 802.15.4m-2014 - IEEE Standard for Local and metropolitan area networks, Part 15.4: Low-Rate Wireless Personal Area Networks (LR-WPANs)—Amendment 6: TV White Space Between 54 MHz and 862 MHz Physical Layer. (2014).

[28]

Md Habibul Islam, Choo Leng Koh, Ser Wah Oh, Xianming Qing, Yoke Yong Lai, Cavin Wang, Ying-Chang Liang, Bee Eng Toh, Francois Chin, Geok Leng Tan, and William Toh. 2008. Spectrum survey in Singapore: Occupancy measurements and analyses. In Proceedings of the 2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008), Vol. May. IEEE, 1--7.

[29]

ITU-R. The second digital dividend: Another bite for mobile? Retrieved from https://itunews.itu.int/En/3744-The-second-digital-dividend-Another-bite-for-mobile.note.aspx.

[30]

Jussi Kerttula and Riku Jäntti. 2011. DVB-t receiver performance measurements under secondary system interference. In Proceedings of COCORA 2011.

[31]

Brett Kilbourne and Klaus Bender. 2010. Spectrum for smart grid: Policy recommendations enabling current and future applications. In Proceedings of the 2010 1st IEEE International Conference on Smart Grid Communications (SmartGridComm’10). 578--582.

[32]

Jaebeom Kim, Jina Han, Zeeshan Hameed Mir, and Young-Bae Ko. 2016. Efficient topology construction and routing for IEEE 802.15.4m-based smart grid networks. Wireless Netw. (Jan. 2016).

Digital Library

[33]

A. G. Longley and P. L. Rice. 1968. Prediction of Tropospheric Radio Transmission Loss Over Irregular Terrain. A Computer Method. Technical Report. NTIS ESSA Tech. Rep. ERL 79-ITS 67.

[34]

J. A. Magliacane. 2010. Splat&excl;&colon; An RF Signal Propagation, Loss, and Terrain Analysis Tool. Retrieved from http://www. qsl.net/kd2bd/splat.html.

[35]

Ofcom. 2012. TV white spaces—A consultation on white space device requirements. (2012).

[36]

Palak P. Parikh, Mitalkumar G. Kanabar, and Tarlochan S. Sidhu. 2010. Opportunities and challenges of wireless communication technologies for smart grid applications. In IEEE PES General Meeting. IEEE, 1--7.

[37]

S. Pollin, M. Ergen, S. Ergen, B. Bougard, L. Der Perre, I. Moerman, A. Bahai, P. Varaiya, and F. Catthoor. 2008. Performance analysis of slotted carrier sense IEEE 802.15.4 medium access layer. IEEE Trans. Wireless Commun. 7, 9 (Sep. 2008), 3359--3371.

Digital Library

[38]

Jaap van de Beek, Janne Riihijärvi, Andreas Achtzehn, and Petri Mähönen. 2012. TV white space in Europe. IEEE Trans. Mobile Comput. 11, 2 (Feb. 2012), 178--188.

Digital Library

[39]

Ye Yan, Yi Qian, Hamid Sharif, and David Tipper. 2013. A survey on smart grid communication infrastructures: Motivations, requirements and challenges. (2013).

[40]

Xuhang Ying, Jincheng Zhang, Lichao Yan, Guanglin Zhang, Minghua Chen, and Ranveer Chandra. 2013. Exploring indoor white spaces in metropolises. In Proceedings of the 19th Annual International Conference on Mobile Computing 8 Networking (MobiCom’13). ACM Press, New York, New York, 255.

Digital Library

[41]

Y. Zhang, R. Yu, M. Nekovee, Y. Liu, S. Xie, and S. Gjessing. 2012. Cognitive machine-to-machine communications: Visions and potentials for the smart grid. IEEE Netw. 26, 3 (May 2012), 6--13.

Cited By

Askhedkar AChaudhari B(2023)Energy efficient LoRa transmission over TV white spacesInternational Journal of Information Technology10.1007/s41870-023-01453-x15:8(4337-4347)Online publication date: 12-Sep-2023
https://doi.org/10.1007/s41870-023-01453-x
Thakur ADe S(2022)On Deploying Secondary Networks in Co-Channel Bands with DTV NetworksIEEE Transactions on Vehicular Technology10.1109/TVT.2022.316822771:7(7791-7804)Online publication date: Jul-2022
https://doi.org/10.1109/TVT.2022.3168227
Zhao ZVuran MBatur DEkici E(2019)Shades of White: Impacts of Population Dynamics and TV Viewership on Available TV SpectrumIEEE Transactions on Vehicular Technology10.1109/TVT.2019.289286768:3(2427-2442)Online publication date: Mar-2019
https://doi.org/10.1109/TVT.2019.2892867
Show More Cited By

Index Terms

Performance Assessment and Feasibility Analysis of IEEE 802.15.4m Wireless Sensor Networks in TV Grayspaces
1. Networks

Recommendations

Markov decision process-based analysis of rechargeable nodes in wireless sensor networks
SpringSim '10: Proceedings of the 2010 Spring Simulation Multiconference

Wireless Sensor Networks (WSNs) are popular nowadays for applications ranging from environmental monitoring to object tracking and surveillance. But the sensors which are deployed are energy constrained. The nodes in WSNs deplete of their very limited ...
Relay Node Placement in Wireless Sensor Networks

A wireless sensor network consists of many low-cost, low-power sensor nodes, which can perform sensing, simple computation, and transmission of sensed information. Long distance transmission by sensor nodes is not energy efficient since energy ...
Sensor scheduling for p-percent coverage in wireless sensor networks

We study sensor scheduling problems of p-percent coverage in this paper and propose two scheduling algorithms to prolong network lifetime due to the fact that for some applications full coverage is not necessary and different subareas of the monitored ...

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Sensor Networks

ACM Transactions on Sensor Networks Volume 13, Issue 1

February 2017

242 pages

ISSN:1550-4859

EISSN:1550-4867

DOI:10.1145/3027492

Editor:
Chenyang Lu
Department of Computer Science and Engineering / School of Engineering and Applied Sciences / Washington University / 1 Brookings Drive / St. Louis, MO 63130

Issue’s Table of Contents

Copyright © 2017 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]

Publisher

Association for Computing Machinery

New York, NY, United States

Journal Family

ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 26 January 2017

Accepted: 01 November 2016

Revised: 01 October 2016

Received: 01 October 2015

Published in TOSN Volume 13, Issue 1

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

6
Total Citations
View Citations
204
Total Downloads

Downloads (Last 12 months)5
Downloads (Last 6 weeks)0

Reflects downloads up to 16 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Askhedkar AChaudhari B(2023)Energy efficient LoRa transmission over TV white spacesInternational Journal of Information Technology10.1007/s41870-023-01453-x15:8(4337-4347)Online publication date: 12-Sep-2023
https://doi.org/10.1007/s41870-023-01453-x
Thakur ADe S(2022)On Deploying Secondary Networks in Co-Channel Bands with DTV NetworksIEEE Transactions on Vehicular Technology10.1109/TVT.2022.316822771:7(7791-7804)Online publication date: Jul-2022
https://doi.org/10.1109/TVT.2022.3168227
Zhao ZVuran MBatur DEkici E(2019)Shades of White: Impacts of Population Dynamics and TV Viewership on Available TV SpectrumIEEE Transactions on Vehicular Technology10.1109/TVT.2019.289286768:3(2427-2442)Online publication date: Mar-2019
https://doi.org/10.1109/TVT.2019.2892867
Bedogni LFelice MBononi L(2019)Dynamic Spectrum Access for Machine to Machine Communications: Opportunities, Standards, and Open IssuesHandbook of Cognitive Radio10.1007/978-981-10-1394-2_57(1821-1848)Online publication date: 22-Feb-2019
https://doi.org/10.1007/978-981-10-1394-2_57
Montori FBedogni LDi Felice MBononi L(2018)Machine-to-machine wireless communication technologies for the Internet of Things: Taxonomy, comparison and open issuesPervasive and Mobile Computing10.1016/j.pmcj.2018.08.00250(56-81)Online publication date: Oct-2018
https://doi.org/10.1016/j.pmcj.2018.08.002
Bedogni LDi Felice MBononi L(2018)Dynamic Spectrum Access for Machine to Machine Communications: Opportunities, Standards, and Open IssuesHandbook of Cognitive Radio10.1007/978-981-10-1389-8_57-1(1-28)Online publication date: 28-May-2018
https://doi.org/10.1007/978-981-10-1389-8_57-1

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Issue’s Table of Contents