Detection of short-term radio signal disturbances in industrial Wireless Sensor Networks

Marina Eskola, Tapio Heikkilä

Research output: Contribution to journalArticleScientificpeer-review

Abstract

The performance of wireless sensor networks (WSNs) in industrial environments may be degraded due to harsh radio signal propagation conditions. Short-term signal disturbances are of major concern due to incoming and outgoing trucks, moving around forklifts and workers, as well as large concrete and metal surfaces. We studied the effects of some environmental disturbances on the quality of the transmitted signals. We consider directly measurable transmission quality parameters Received Signal Strength Indicator (RSSI) and Bit-Error-Rate (BER) as well as statistical characteristics of the received signal magnitude. We used software defined radio (SDR) as the receiver to capture the transmitted signals and analyzed the statistical properties of the captured signals with Matlab/Simulink tools. Our studies led us to a method which aims to identify the short-term radio disturbances by calculating the probability density function (PDF) of the received signal magnitude and analyzing the parameters of the PDFs. The results show that tracking the changes of the PDF of the received signal magnitudes contributes to recognize and characterize the temporal changes in the radio link environment and in that way to choose the right actions in order to overcome the communication problems.
Original languageEnglish
Pages (from-to)201-208
JournalJournal of Networks
Volume10
Issue number4
DOIs
Publication statusPublished - 2015
MoE publication typeA1 Journal article-refereed

Fingerprint

Wireless sensor networks
Probability density function
Radio links
Bit error rate
Trucks
Concretes
Communication
Metals

Keywords

  • radio distrubances
  • Wireless Sensor Networks
  • Rician distribution
  • Software Defined Radio
  • industrial measurements

Cite this

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title = "Detection of short-term radio signal disturbances in industrial Wireless Sensor Networks",
abstract = "The performance of wireless sensor networks (WSNs) in industrial environments may be degraded due to harsh radio signal propagation conditions. Short-term signal disturbances are of major concern due to incoming and outgoing trucks, moving around forklifts and workers, as well as large concrete and metal surfaces. We studied the effects of some environmental disturbances on the quality of the transmitted signals. We consider directly measurable transmission quality parameters Received Signal Strength Indicator (RSSI) and Bit-Error-Rate (BER) as well as statistical characteristics of the received signal magnitude. We used software defined radio (SDR) as the receiver to capture the transmitted signals and analyzed the statistical properties of the captured signals with Matlab/Simulink tools. Our studies led us to a method which aims to identify the short-term radio disturbances by calculating the probability density function (PDF) of the received signal magnitude and analyzing the parameters of the PDFs. The results show that tracking the changes of the PDF of the received signal magnitudes contributes to recognize and characterize the temporal changes in the radio link environment and in that way to choose the right actions in order to overcome the communication problems.",
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Detection of short-term radio signal disturbances in industrial Wireless Sensor Networks. / Eskola, Marina; Heikkilä, Tapio.

In: Journal of Networks, Vol. 10, No. 4, 2015, p. 201-208.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Detection of short-term radio signal disturbances in industrial Wireless Sensor Networks

AU - Eskola, Marina

AU - Heikkilä, Tapio

PY - 2015

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N2 - The performance of wireless sensor networks (WSNs) in industrial environments may be degraded due to harsh radio signal propagation conditions. Short-term signal disturbances are of major concern due to incoming and outgoing trucks, moving around forklifts and workers, as well as large concrete and metal surfaces. We studied the effects of some environmental disturbances on the quality of the transmitted signals. We consider directly measurable transmission quality parameters Received Signal Strength Indicator (RSSI) and Bit-Error-Rate (BER) as well as statistical characteristics of the received signal magnitude. We used software defined radio (SDR) as the receiver to capture the transmitted signals and analyzed the statistical properties of the captured signals with Matlab/Simulink tools. Our studies led us to a method which aims to identify the short-term radio disturbances by calculating the probability density function (PDF) of the received signal magnitude and analyzing the parameters of the PDFs. The results show that tracking the changes of the PDF of the received signal magnitudes contributes to recognize and characterize the temporal changes in the radio link environment and in that way to choose the right actions in order to overcome the communication problems.

AB - The performance of wireless sensor networks (WSNs) in industrial environments may be degraded due to harsh radio signal propagation conditions. Short-term signal disturbances are of major concern due to incoming and outgoing trucks, moving around forklifts and workers, as well as large concrete and metal surfaces. We studied the effects of some environmental disturbances on the quality of the transmitted signals. We consider directly measurable transmission quality parameters Received Signal Strength Indicator (RSSI) and Bit-Error-Rate (BER) as well as statistical characteristics of the received signal magnitude. We used software defined radio (SDR) as the receiver to capture the transmitted signals and analyzed the statistical properties of the captured signals with Matlab/Simulink tools. Our studies led us to a method which aims to identify the short-term radio disturbances by calculating the probability density function (PDF) of the received signal magnitude and analyzing the parameters of the PDFs. The results show that tracking the changes of the PDF of the received signal magnitudes contributes to recognize and characterize the temporal changes in the radio link environment and in that way to choose the right actions in order to overcome the communication problems.

KW - radio distrubances

KW - Wireless Sensor Networks

KW - Rician distribution

KW - Software Defined Radio

KW - industrial measurements

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