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

Marina Eskola, Tapio Heikkilä

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    4 Citations (Scopus)

    Abstract

    The performance of wireless sensor networks (WSNs) in industrial applications may be degraded due to harsh radio signal propagation conditions. Mobile heavy machines and large metal and concrete surfaces usually worsen the signal fading effects resulting in deep fades. We have studied the effects of certain industrial environmental disturbances on the quality of the transmitted signals in real-life industrial environments. 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 transmission problems related to signal multipath propagation by calculating the probability density function (PDF) of the received signal and comparing it to the simulated theoretical Rician distributions. The results show that tracking the transformations of the PDF of the received signal helps to recognize the temporal changes in radio link environment and in that way can help to choose the right actions in order to overcome the communication problems
    Original languageEnglish
    Title of host publicationProceedings
    Subtitle of host publicationInternational Symposium on Performance Evaluation of Computer and Telecommunication Systems, SPECTS 2014
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Number of pages7
    ISBN (Print)978-147995745-3
    DOIs
    Publication statusPublished - 2014
    MoE publication typeA4 Article in a conference publication
    EventInternational Symposium on Performance Evaluation of Computer and Telecommunication Systems, SPECTS 2014 - Monterey, CA, United States
    Duration: 6 Jul 201410 Jul 2014

    Conference

    ConferenceInternational Symposium on Performance Evaluation of Computer and Telecommunication Systems, SPECTS 2014
    CountryUnited States
    CityMonterey, CA
    Period6/07/1410/07/14

    Fingerprint

    Probability density function
    Wireless sensor networks
    Radio links
    Multipath propagation
    Industrial applications
    Concretes
    Communication
    Metals

    Keywords

    • industrial measurements
    • radio disturbances
    • Rician density
    • software defined radio
    • wireless sensor networks

    Cite this

    Eskola, M., & Heikkilä, T. (2014). Detection of short-term radio signal disturbances in industrial Wireless Sensor Networks. In Proceedings: International Symposium on Performance Evaluation of Computer and Telecommunication Systems, SPECTS 2014 IEEE Institute of Electrical and Electronic Engineers . https://doi.org/10.1109/SPECTS.2014.6880001
    Eskola, Marina ; Heikkilä, Tapio. / Detection of short-term radio signal disturbances in industrial Wireless Sensor Networks. Proceedings: International Symposium on Performance Evaluation of Computer and Telecommunication Systems, SPECTS 2014. IEEE Institute of Electrical and Electronic Engineers , 2014.
    @inproceedings{338fe51d958142488f340e3166a622a1,
    title = "Detection of short-term radio signal disturbances in industrial Wireless Sensor Networks",
    abstract = "The performance of wireless sensor networks (WSNs) in industrial applications may be degraded due to harsh radio signal propagation conditions. Mobile heavy machines and large metal and concrete surfaces usually worsen the signal fading effects resulting in deep fades. We have studied the effects of certain industrial environmental disturbances on the quality of the transmitted signals in real-life industrial environments. 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 transmission problems related to signal multipath propagation by calculating the probability density function (PDF) of the received signal and comparing it to the simulated theoretical Rician distributions. The results show that tracking the transformations of the PDF of the received signal helps to recognize the temporal changes in radio link environment and in that way can help to choose the right actions in order to overcome the communication problems",
    keywords = "industrial measurements, radio disturbances, Rician density, software defined radio, wireless sensor networks",
    author = "Marina Eskola and Tapio Heikkil{\"a}",
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    year = "2014",
    doi = "10.1109/SPECTS.2014.6880001",
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    Eskola, M & Heikkilä, T 2014, Detection of short-term radio signal disturbances in industrial Wireless Sensor Networks. in Proceedings: International Symposium on Performance Evaluation of Computer and Telecommunication Systems, SPECTS 2014. IEEE Institute of Electrical and Electronic Engineers , International Symposium on Performance Evaluation of Computer and Telecommunication Systems, SPECTS 2014, Monterey, CA, United States, 6/07/14. https://doi.org/10.1109/SPECTS.2014.6880001

    Detection of short-term radio signal disturbances in industrial Wireless Sensor Networks. / Eskola, Marina; Heikkilä, Tapio.

    Proceedings: International Symposium on Performance Evaluation of Computer and Telecommunication Systems, SPECTS 2014. IEEE Institute of Electrical and Electronic Engineers , 2014.

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    TY - GEN

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

    AU - Eskola, Marina

    AU - Heikkilä, Tapio

    N1 - HUO: Part of SummerSim 2014 multiconference

    PY - 2014

    Y1 - 2014

    N2 - The performance of wireless sensor networks (WSNs) in industrial applications may be degraded due to harsh radio signal propagation conditions. Mobile heavy machines and large metal and concrete surfaces usually worsen the signal fading effects resulting in deep fades. We have studied the effects of certain industrial environmental disturbances on the quality of the transmitted signals in real-life industrial environments. 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 transmission problems related to signal multipath propagation by calculating the probability density function (PDF) of the received signal and comparing it to the simulated theoretical Rician distributions. The results show that tracking the transformations of the PDF of the received signal helps to recognize the temporal changes in radio link environment and in that way can help to choose the right actions in order to overcome the communication problems

    AB - The performance of wireless sensor networks (WSNs) in industrial applications may be degraded due to harsh radio signal propagation conditions. Mobile heavy machines and large metal and concrete surfaces usually worsen the signal fading effects resulting in deep fades. We have studied the effects of certain industrial environmental disturbances on the quality of the transmitted signals in real-life industrial environments. 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 transmission problems related to signal multipath propagation by calculating the probability density function (PDF) of the received signal and comparing it to the simulated theoretical Rician distributions. The results show that tracking the transformations of the PDF of the received signal helps to recognize the temporal changes in radio link environment and in that way can help to choose the right actions in order to overcome the communication problems

    KW - industrial measurements

    KW - radio disturbances

    KW - Rician density

    KW - software defined radio

    KW - wireless sensor networks

    U2 - 10.1109/SPECTS.2014.6880001

    DO - 10.1109/SPECTS.2014.6880001

    M3 - Conference article in proceedings

    SN - 978-147995745-3

    BT - Proceedings

    PB - IEEE Institute of Electrical and Electronic Engineers

    ER -

    Eskola M, Heikkilä T. Detection of short-term radio signal disturbances in industrial Wireless Sensor Networks. In Proceedings: International Symposium on Performance Evaluation of Computer and Telecommunication Systems, SPECTS 2014. IEEE Institute of Electrical and Electronic Engineers . 2014 https://doi.org/10.1109/SPECTS.2014.6880001